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Björkman, Börje. "Nytt i institutionens skriftserier." HumaNetten, no. 18 (November 27, 2015): 53. http://dx.doi.org/10.15626/hn.20061805.
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Senaste nytt i institutionens skriftserier:
Kristina Jansson, Saisir l’insaisissable: les formes et les traductions du discours indirect libre dans des romans suédois et français. Acta Wexionensia nr 86/2006.
Lars Olsson (red), Invandring, invandrare och etniska relationer i Sverige 1945-2005. Årsbok från forskningsmiljön AMER. Acta Wexionensia nr 79/2005.
Johan Svanberg, Minnen av migrationen. Arbetskraftsinvandring från Jugoslavien till Svenska Fläktfabriken i Växjö kring 1970. Acta Wexionensia nr 80/2006.
Hägerdal, Hans, Candrasangkala: The Balinese Art of Dating Events. Rapporter från Växjö universitet: Humaniora
Sofia Ask, Gunilla Byrman, Solveig Hammarbäck, Maria Lindgren, Per Stille (red.), Lekt och lärt. Vänskrift till Jan Einarsson 2006. Rapporter från Växjö universitet: Humaniora, Nr 16/2006.
Scripta minora Nr 47: Meike Krüger, Spuren des kollektiven Gedächtnisses im Roman Faserland von Christian Kracht.
Scripta minora Nr 48: Corina Löwe, ”Eigentlich können wir uns jeden Tag entscheiden, jemand anderer zu sein” Metamorphosen von Geschlechtsanatomie und -identität, dargestellt an den Romanfiguren in Sibylle Bergs Roman Amerika.
Scripta minora Nr 49: Gunilla Byrman och Jan Einarsson (red.), Två uppsatser i nordiska språk (Lovisa Alvtörn: En människas språkhistoria. I ljuset av ett vidgat lektbegrepp. Astrid Skoglund: ”Om sättet att tillhopa gå”. Jämförelse mellan två sexualvetenskapliga texter från två skilda sekel)
Scripta minora Nr 50: Arvid Jurjaks, I en bländande verklighet. Om sol och hetta i Albert Camus Främlingen.
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Nilsson, Carl-Gustaf, Seppo Heinonen, and Jens A. Gudmundsson. "Gynekologi edited by Per Olof Janson, Britt-Marie Landgren." Acta Obstetricia et Gynecologica Scandinavica 91, no. 2 (January 18, 2012): 276–77. http://dx.doi.org/10.1111/j.1600-0412.2011.01317.x.
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Tómas Geirsson, Reynir, Ganesh Acharya, and Mats Brännström. "Per Olof Janson: In memory of a remarkable man." Acta Obstetricia et Gynecologica Scandinavica 100, no. 1 (December 13, 2020): 182. http://dx.doi.org/10.1111/aogs.14050.
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Khan, T., N. Cleaton, and T. Sheeran. "THU0594 A CASE OF TAKAYASU’S ARTERITIS IN A PATIENT WITH TUBERCULOUS LYMPHADENITIS." Annals of the Rheumatic Diseases 79, Suppl 1 (June 2020): 539.3–539. http://dx.doi.org/10.1136/annrheumdis-2020-eular.6542.
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Background:Takayasu’s arteritis (TA) is a large vessel vasculitis that principally affects the aorta and its main branches. The incidence has been reported at between 1.2 – 2.3 cases per million per year, more commonly in the Asian population. The age of onset is typically between tenth and fourth decade; between 80 and 90 percent of the cases are female.The relationship between Mycobacterium Tuberculosis (mTB) and TA has long been considered; both demonstrate chronic inflammatory changes on histological examination and some granuloma formation in arterial walls. There is increasing evidence implicating mTB in the pathogenesis of TA through molecular mimicry between the mycobacterium heat shock protein -65 (mHSP-65) and the human homologue HSP -60 (hHSP-60). However, no definitive link between the two diseases has been explained.Objectives:Case presentation.Results:A 23-year-old lady was referred to our outpatient rheumatology clinic with a twelve-month history of persistently enlarged cervical lymph nodes on the left side for which she had received six months of anti-Tuberculosis medication. She had been referred to the respiratory physicians who had diagnosed presumed Tuberculous Lymphadenitis, with caseating granulomas demonstrated on biopsy, positive acid-fast bacilli smear but a negative culture. The patient had been initiated six months of anti-Tuberculosis medication; however, her lymphadenopathy showed no improvement. More recently she described a five-month history of weakness, paraesthesia and claudication symptoms in her left upper limb with episodes of dizziness and blurred vision, episodes occurring 2-3 times per day and lasting between a few minutes to a few hours.Her examination at this presentation revealed an unrecordable blood pressure in the left upper limb and 104/67mmHg in the right. There was significant tender lymphadenopathy of the left cervical lymph nodes and diminished pulses in the left upper limb. Right sided pulses were normal. The rest of her examination was normal.Investigations at presentation revealed elevated inflammatory markers with C- reactive protein (CRP) of 116mg/dL and erythrocyte sedimentation rate (ESR) of 128mm/h. Complete blood count (CBC) found her to be anaemic with a haemoglobin of 100g/L, with a mean cell volume of 71.3fl, and have elevated platelet count of 649x 109/L. Recent computerized tomography scan with contrast of the thorax demonstrated features consistent with Takayasu Arteritis. Marked left subclavian stenosis was found on magnetic resonance imaging. High dose prednisolone at 60mg once daily along with Azathioprine 2mg/kg/day was started with a follow up appointment in two weeks.Conclusion:There is increasing evidence implicating mTB in the development of TA and a few cases recognising this link have been reported. We report a case of TA in a patient recently diagnosed and treated for Tuberculous lymphadenitis who then developed symptoms of TA. There should be a low threshold for suspecting a diagnosis of Takayasu’s arteritis in patients previously or actively infected with Mycobacterium Tuberculosis. Further research exploring the relationship between mTB and TA is required.References:[1]Espinoza JL, Ai S, Matsumura I. New Insights on the Pathogenesis of Takayasu Arteritis: Revisiting the Microbial Theory. Pathogens. 2018;7(3):73.[2]Aggarwal A, Chag M, Sinha N, et al. Takayasu’s arteritis: role of Mycobacterium tuberculosis and its 65 kDa heat shock protein. International Journal of Cardiology. 1996; 55: 49–55.[3]Reshkova V, Kalinova D, Rashkov R. Takayasu’s Arteritis associated with Tuberculosis Infections. Journal of Neurology and Neuroscience. 2016; 3:114.[4]Moritz K, Jansson Hilte F, Antje Kangowski, Christian Kneitz, Emil C. Reisinger. Tuberculosis and Takayasu arteritis: case-based review Rheumatology International 2019 39:345–351[5]D Misra, A Wakhlu, V Agarwal, D Danda. Recent advances in the management of Takayasu arteritis International Journal of Rheumatic Diseases 2019; 22: 60–68Disclosure of Interests:None declared
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Foti, R., G. Cardinale, L. Costa, F. Franceschini, F. Ciccia, A. Marchesoni, G. Guggino, et al. "AB0681 COMPARISON BETWEEN DEMOGRAPHIC AND CLINICAL CHARACTERISTICS OF PREDOMINANT AXIAL VS MAINLY PERIPHERAL SPONDYLOARTHRITIS (SpA) PATIENTS, ENROLLED IN THE ONGOING SIRENA STUDY." Annals of the Rheumatic Diseases 79, Suppl 1 (June 2020): 1636.1–1636. http://dx.doi.org/10.1136/annrheumdis-2020-eular.1066.
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Background:SIRENA is an Italian, prospective Registry in Spondyloarthritis (SpA) patients, naïve to conventional, targeted and biological DMARDs. Patients are diagnosed, newly or confirmed, according to ASAS criteria and classified in subjects with predominant axial(AX) or with mainly peripheral manifestations(PER).Objectives:To compare descriptively AX vs PER subgroups of patients.Methods:Demographic data, diagnostic delay and subtypes of SpA as well as clinical features and comorbidities are collected.Results:282 patients were enrolled: 101 (35.8%) AX and 181 (64.2%) PER. Baseline data are shown in Table 1. There were more obese patients in AX (21.4% AX vs 16.1% PER) and more overweight ones in PER (19.4% AX vs 23.8% PER). The % of subjects with diagnostic delay was higher in AX (65.7% vs 53.9% PER) and the delay longer (mean of 73.1 months vs 47.8). In both groups, main reason of the delay was incorrect referrals (41.5% for AX and 45.3% for PER). Noteworthy the fact that in PER, the 75.7% of patients had a newly diagnosed SpA. In PER, the most frequent SpA type was PsA (82.3%), followed by undifferentiated SpA (8.8%) and enteropathic SpA (7.5%), while in AX, 49.5% were ankylosing spondylitis, 21.8% nr-ax-SpA and only 4% PsA. The majority of PER patients reported as first symptom peripheral arthritis (80/181), psoriasis (57/181) and enthesitis while in AX referred inflammatory back pain (80/101). High percentages of comorbidities were reported: psoriasis (65.8%) and cardiometabolic diseases (34.8%) were higher in PER while depression/anxiety and GI diseases were higher in AX (Table 2). At the baseline, the mean PhGA score (0-100) was 51.5 for AX and 43.8 for PER.Conclusion:SIRENA study highlights relevant differences in AX vs PER patients, expecially in terms of diagnostic delay, clinical presentation and comorbidities.Table 1.MeanAX n=101MeanPER n=181Age (years)47.352.8Sex (female/male - %)50.5/49.547.5/52.5Weight (Kg)73.073.9BMI25.325.4Diagnostic Delay (yes - %)65.7%53.9%Time of delay (mean - months)71.347.8Newly SpA diagnosis (%)55.5%75.7%Table 2.A) First Symptom(more than 1 symptom referred)AX n=101N. PatientsPER n=181N. PatientsArthritis23122Enthesitis1654Dactylitis728Inflammatory Back Pain8034Psoriasis skin1057Psoriasis nails219Uveitis41IBD79B) Comorbidities(more than 1 comorbidity referred)% Patients% PatientsCardiometabolic20.8%34.8% -Hypertension19.8%30.9% -Dyslipidemia17.8%11.6% -Diabetes6.0%7.7% -MetS5.0%6.6%Psoriasis22.8%65.8%Gastrointestinal20.8 (16.9% CD)12.8 (4.4% CD)Depression/Anxiety11.9%2.2%Endocrine6.9%11.1%Osteoporosis3%5.5%Hepatic4% (3% NAFLD)4.4% (2.2% NAFLD)Infections3%3.9%Malignancies0%4.4%Acknowledgments:This study was sponsored by Janssen Italy.We thank the Investigators and their staff at all of the study sites.Disclosure of Interests:Rosario Foti Speakers bureau: Abbvie, BMS, ROCHE, Janssen, Celgene, Gabriella Cardinale: None declared, Luisa Costa: None declared, Franco Franceschini Consultant of: Eli-Lilly, Janssen, Pfizer, Sanofi-Genzyme, UCB Pharma, GSK, Francesco Ciccia Grant/research support from: Pfizer, Novartis, Celgene, Janssen, Consultant of: Lilly, Novartis, Pfizer, Janssen, Roche, Celgene, Speakers bureau: Pfizer, Novartis, Celgene, Janssen, Roche, Abiogen, BMS, Antonio Marchesoni Speakers bureau: Abbvie, Pfizer, UCB, Novartis, Celgene, Eli Lilly, Giuliana Guggino Grant/research support from: Pfizer, Celgene, Speakers bureau: Celgene, Sandoz, Pfizer, Maurizio Rossini Speakers bureau: AbbVie, Abiogen, Amgen, BMS, Eli-Lilly, Novartis, Pfizer, Sanofi, Sandoz and UCB, Ennio Lubrano: None declared, Mauro Galeazzi: None declared, Mariasole Chimenti: None declared, Gerolamo Bianchi Grant/research support from: Celgene, Consultant of: Amgen, Janssen, Merck Sharp & Dohme, Novartis, UCB, Speakers bureau: Abbvie, Abiogen, Alfa-Sigma, Amgen, BMS, Celgene, Chiesi, Eli Lilly, GSK, Janssen, Medac, Merck Sharp & Dohme, Novartis, Pfizer, Roche, Sanofi Genzyme, Servier, UCB, Giuseppe Galfo: None declared, Silvia Marelli Employee of: Janssen, Ennio Favalli Speakers bureau: BMS, Eli-Lilly, MSD, UCB, Pfizer, Sanofi-Genzyme, Novartis and Abbvie
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Isnardi, C. A., E. E. Civit De Garignani, A. García Ciccarelli, J. Sanchez Alcover, R. Garcia Salinas, S. Magri, E. Albiero, et al. "AB0214 SURVIVAL, EFFICACY AND SAFETY OF GOLIMUMAB IN PATIENTS WITH RHEUMATOID ARTHRITIS AND SPONDYLOARTHRITIS: DATA FROM AN ARGENTINEAN COHORT." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 1133–34. http://dx.doi.org/10.1136/annrheumdis-2021-eular.1399.
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Background:Golimumab is a human monoclonal antibody directed against TNFα in its soluble and transmembrane forms. It can be used subcutaneously or intravenously and has shown efficacy for use in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) and ankylosing spondylitis (AS).Objectives:The aim of this study was to evaluate the efficacy, safety, and cumulative survival of golimumab in patients with RA, PsA and AS from different rheumatology centers in Argentina.Methods:We performed a longitudinal study of consecutive adults with RA (ACR/EULAR 2010 criteria), PsA (CASPAR criteria) and AS (ASAS 2009 criteria), who have started treatment with subcutaneous or intravenous golimumab according to medical indication in each center. Data was obtained by review of medical records. Sociodemographic and clinical data, musculoskeletal manifestations, comorbidities, previous treatments were recorded. In reference to golimumab treatment, start date, route of administration and concomitant treatments were identified. Disease activity was assessed using DAS28 for RA patients, DAPSA and MDA for PsA and BASDAI for AS. The presence of adverse events (AE) was recorded. If golimumab was stopped, date and cause was documented. Patients were followed up until golimumab discontinuation, loss of follow-up, or study completion (November 30, 2020). Statistical analysis: Chi2 test or Fischer exact test and T test or Mann Whitney and ANOVA or Kruskal Wallis, as appropriate. The incidence of EA was assessed in events every 100 patient/year. Kaplan-Meier curves and log Rank analysis. Cox proportional regression.Results:One hundred eighty two patients were included, 116 with a diagnosis of RA, 30 with PsA and 36 with AS. Most of them (70.9%) were female with a median (m) age of 55 years (IQR 43.8-64) and m disease duration of 7 years (IQR 4-12.7) at treatment initiation. Al least one prior biological DMARD or a small molecule was received by 63 patients (34.6%). The most frequent indication cause was conventional DMARD failure. In 94.8% of the patients Golimumab was administered subcutaneously, and in 80.8% in association with conventional DMARDs, the most frequently used was methotrexate. Total follow-up was 318.1 patients/year.Golimumab treatment showed clinical improvement in all three groups of patients. In RA patients DAS28 significantly decreased during the first 12 months of follow-up, m 5.9 (IQR 4.9-6.6) at baseline, 3.8 (IQR 2.6-4.6) at 6 months and 2.8 (IQR 2.1-3.6) at 12 months, p <0.0001. In PsA, m DAPSA-ESR value was 32.2 (IQR 24.2-47.7), 10.1 (IQR 5.8-18.3) and 11.2 (IQR 3.4-24) at baseline, 6 and 12 months, respectably (p <0.0001). In AS, m BASDAI was 6.2 (IQR 4.8-7.3), 2.8 (IQR 1.7-4.1) and 2.2 (IQR 1.1-3.2), at baseline, 6 and 12 months respectively (p <0.0001).The incidence of adverse events was 6.6 per 100 patients/year, being infections the most frequents ones. During follow-up, 50 patients (27.5%) discontinued golimumab, the most frequent cause was treatment failure (68%), followed by lack of health insurance (16%) and adverse events (10%). Golimumab persistence was 79% and 57.6% at 12 and 24 months, respectively. Treatment survival was 50.2 months (95% CI 44.4-55.9). Patients who had received prior treatment with biological DMARDs or small molecules showed lower survival (Figure 1). In the multivariate analysis, adjusting for age, sex and disease duration, those patients showed twice the risk of suspending treatment (HR 2.01, 95% CI 1.1-3.7).Figure 1.Golimumab survival according to prior b-DMARD o small molecule treatment.Conclusion:Golimumab treatment in real life patients in Argentina has shown good efficacy and safety. Drug survival was over 4 years and almost 80% were still using golimumab after one year. Prior treatment with other b-DMARDs o small molecules was associated with lower treatment survival.Disclosure of Interests:Carolina Ayelen Isnardi Speakers bureau: Bristol Myers Squibb, Janssen, Grant/research support from: Pfizer, Emma Estela Civit De Garignani Speakers bureau: Abbvie, Novartis, Agustín García Ciccarelli Speakers bureau: Janssen, Novartis, Consultant of: Novartis, Grant/research support from: Janssen, Novartis, Jimena Sanchez Alcover: None declared, Rodrigo Garcia Salinas Speakers bureau: Abbvie, AMGEN, Bristol-Myers Squibb, Eli Lilly, GSK, Janssen Cilag, Montpellier-UCB, Novartis, Roche – Genentech, Sanofi, Merck Serono., Sebastian Magri Speakers bureau: Abbvie, AMGEN, Bristol-Myers Squibb, Eli Lilly, GSK, Janssen Cilag, Montpellier-UCB, Novartis, Roche – Genentech, Sanofi, Merck Serono., Eduardo Albiero Consultant of: Janssen, Carla Gobbi Speakers bureau: Pfizer, Consultant of: Pfizer, Janssen, Edson Velozo Speakers bureau: Janssen, Novartis, Pfizer, Consultant of: Abbvie, Janssen, Novartis, Grant/research support from: Janssen, Novartis, Pfizer, Enrique Soriano Speakers bureau: AbbVie, Novartis, Bristol MS, Novartis, Eli Lilly, Genzyme, Pfizer, Amgen, and Roche, Consultant of: Novartis, AbbVie, Pfizer, Eli Lilly, Sanofi, Sandoz, Amgen., Grant/research support from: Roche, Novartis, AbbVie, Glaxo Smith Kline, BMS, Martín Brom: None declared, Johana Zacariaz Grant/research support from: Bristol Myers Squibb, Ingrid Strusberg Speakers bureau: Gema Biotech SAU, BMS, Abbvie, Consultant of: Gema Biotech SAU, Abbvie, Janssen, Grant/research support from: Abbvie, Lilly, Galápagos, Servier, GSK, Merck Serono, Marcos BARAVALLE Speakers bureau: Montepellier, Consultant of: Abbvie, Janssen, Grant/research support from: Abbvie, Lilly, Galápagos, Servier, GSK, Merck Serono, Sol Castaños Speakers bureau: Abbvie, Lilly, Galápagos, Servier, GSK, Merck Serono, Liliana Morales Speakers bureau: Lilly, Consultant of: Janssen, Grant/research support from: Abbvie, Lilly, Galápagos, Servier, GSK, Merck Serono, Sergio Paira: None declared, Romina Calvo: None declared, Alberto Ortiz: None declared, Rodolfo Perez Alamino Speakers bureau: Pfizer, Abbvie, Amgen, Bristol-Myers-Squibb, Lilly, Janssen, Novartis, Hernan Maldonado Ficco Speakers bureau: Pfizer, Abbvie, Jansen, Novartis, Bago, Bristol, Eli Lilly., Consultant of: Pfizer, Abbvie, Novartis, Jansen, Bago, Eli Lilly., Gustavo Citera Speakers bureau: Abbvie, BMS, Lilly, Jansen, Gema, Pfizer, Roche, Grant/research support from: Pfizer
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Teeple, A., and E. Muser. "Cost per Responder Analysis of Guselkumab Versus Certolizumab Pegol Using Efficacy Results from Pivotal Clinical Trials in Patients with Moderate to Severe Plaque Psoriasis." SKIN The Journal of Cutaneous Medicine 2 (December 17, 2018): S80. http://dx.doi.org/10.25251/skin.2.supp.81.
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Vij, Ravi, Justin King, Mark A. Fiala, Neeraj Kumar Singh, Mohammed Sauban, Zakir Husain, Anjanasree V. Lakshminarayana, et al. "Clinical Validation of Treatment Response Predictions Using a Genomics Driven Computational Biology Modelling Multiple Myeloma Algorithm." Blood 132, Supplement 1 (November 29, 2018): 1893. http://dx.doi.org/10.1182/blood-2018-99-118686.
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Abstract Background: Multiple myeloma (MM) is an incurable and heterogeneous haematological malignancy in which immune suppression and complex biology affect the disease and its response to treatment. Several new treatments have been approved for MM in recent years providing numerous options for patients with relapsed/refractory disease. However, there is no validated method for selecting the best treatment combination for each patient, making patient management difficult. The ability to predict treatment response based on disease characteristics could improve clinically outcomes. Aim: This was a validation of a genomics-informed response prediction using computational biology modelling (CBM) in patients with relapsed/refractory MM. Methods: Input data from fluorescence in-situ hybridization (FISH), karyotype, and a MM specific next generation sequencing capture array were analysed using CBM. This was a retrospective review of patients which were treated with different combinations based on patient/physician choice. The CBM uses PubMed and other online resources to generate patient-specific protein network maps of activated and inactivated pathways. The specific drug combination for each patient was simulated and the quantitative drug effect was measured on a composite MM disease inhibition score (i.e., cell proliferation, viability, apoptosis and paraproteins). The predicted outcomes were then compared to the clinical response (≥PR or < PR per IMWG) to assess the accuracy of this CBM predictive approach. Results: 27 patients were selected for the study; 3 failed CBM due to missing inputs and in 3 clinical response was not able to be assessed, leaving 21 eligible for the analysis. The median age at presentation was 57 years (range 37-76) and 52% were male. The median prior lines of MM therapy was 5 (range 1-15). 38% were refractory to bortezomib, 62% to lenalidomide, 52% to carfilzomib, 57% to pomalidomide, and 43% to daratumumab. 81% had a prior autologous stem cell transplant. The treatments modelled included IMiD-based regimens (n = 9), PI-based regimens (n = 6), chemo-based regimens (n = 3), selinexor (n = 2), PI/IMiD combination regimens (n = 1). Sixteen were clinical responders and 5 were non-responders. CBM predictions matched for 17 of 21 treatments overall, 15 of 16 clinical responders and 2 of 5 non-responders. The statistics of prediction accuracy against clinical outcome are presented in Table 1. Interestingly, the CBM identified drugs within the combination regimens which may not have impacted efficacy. For example, the CBM predicted that one patient treated with bortezomib, venetoclax, and dexamethasone would have had similar response if venetoclax had been omitted from the regimen. Conclusion: We have demonstrated that a CBM approach, which incorporates genomics, can help predict response in patients with relapsed or refractory MM. Prospective studies using the CBM as part of treatment decision-making will help determine its application into clinical settings. Disclosures Vij: Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jansson: Honoraria, Membership on an entity's Board of Directors or advisory committees. Singh:Cellworks Research India Private Limited: Employment. Sauban:Cellworks Research India Private Limited: Employment. Husain:Cellworks Research India Private Limited: Employment. Lakshminarayana:Cellworks Research India Private Limited: Employment. Talawdekar:Cellworks Research India Private Limited: Employment. Mitra:Cellworks Research India Private Limited: Employment. Abbasi:Cell Works Group Inc.: Employment. Vali:Cell Works Group Inc.: Employment.
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Schöning, Udo. "La Fortune.Thèmes,représentations,discours, Études rassemblées par Yasmina Foehr-Janssens et Emmanuelle Métry." Zeitschrift für romanische Philologie (ZrP) 120, no. 4 (December 2004): 645–46. http://dx.doi.org/10.1515/zrph.2004.645.
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Sata, Hiroshi, Hirohiko Shibayama, Ikuhiro Maeda, Yoko Habuchi, Eiji Nakatani, Kentaro Fukushima, Jiro Fujita, et al. "Clinical Meanings of Quantitative PCR of Patient-Specific Immunoglobulin VDJ Regions Using Various Materials of Myeloma Patients." Blood 124, no. 21 (December 6, 2014): 2049. http://dx.doi.org/10.1182/blood.v124.21.2049.2049.
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Abstract Introduction; The PCR with patient-specific, allele-specific oligonucleotide primers for individual IgH VDJ regions (ASO-PCR) is considered the most sensitive method to detect minimal residual disease (MRD) levels in patients with multiple myeloma (MM). In this study, we quantified the ASO-PCR products by using peripheral blood mononuclear cells (PBMNCs) as well as bone marrow mononuclear cells (BMMNCs). We also quantified the ASO-PCR products in mRNAs from CD20+38- B-cells in BM to examine whether there are clonogenic cells in relatively earlier B-cell fraction as well as cell-free DNAs from the sera to examine whether there are DNA fragments from MM cells in PB. Materials and methods; We have analyzed 30 MM cases. After an informed consent, patient-oriented PCR primers were designed from sequence information of immunoglobulin heavy chain (IgH) variable regions of myeloma cells of each patient. Results; The median age in this cohort was 64.5 years (36-83); the ratio of men to women was 16:14; and the numbers of IgG-, IgA-, and Bence Jones protein (BJP)- type patients were 18, 7, and 5, respectively. The patient-specific ASO primers could be designed in 25 cases, but not in 3 BJP-type cases or 2 IgG-type cases. We could quantify the ASO-PCR products in 20 of 30 BMMNCs samples at diagnosis. The ASO-PCR levels (IgH/β−actin levels)in BMMNCs correlated with those in PBMNCs, but not to the percent of plasma cells in BM or the values for M-protein. However, the ASO-PCR levels were decreased after the treatment and reflected tumor burden well individually. The ASO-PCR levels in PBMNCs showed a statistically significant correlation with those in BMMNCs at diagnosis (Spearman’s ρ= 0.98, P<0.001), 6 months (Spearman’s ρ= 0.83, P = 0.020) and 12 months (Spearman’s ρ= 1.90, P = 0.001). Therefore, ASO-PCR using PBMNCs as well as BMMNCs is suitable for MRD evaluation. We could detect the patient-specific IgH DNA sequences in cell-free DNA extracted from the sera and quantify the ASO-PCR products. The sequences of the ASO-PCR product were identical to the originally designed sequence, suggesting that detection of the ASO-PCR products in cell-free DNA could reflect the persistence of myeloma cells somewhere in body. The ASO-PCR products for CD20+CD38- B-cells in BM were relatively low but were clearly detected in 17 cases at diagnosis. The ASO-PCR levels in CD20+CD38- B-cells in BM showed good correlation with both values of ASO-PCR in BMMNCs (Spearman’s ρ= 1.35, P <0.001) and in PBMNCs (Spearman’s ρ= 1.09, P <0.001). Thus, the evaluation of relatively earlier B-cell stages of myeloma cells seems to be of interst, including for the possible existence of MM clones in CD20+CD38- B-cell population in BM. Discussion; Our findings that we could quantify the ASO-PCR products in PBMNCs, BM CD20+CD38- B-cells, cell-free DNA as well as BMMNCs strongly suggest wide sources of clinical materials to analyze. There were statistically significant correlations in values of the ASO-PCR products between BMMNCs and PBMNCs, therefore suggesting the possibility that clonogenic plasma cells or myeloma precursor cells might circulate in peripheral blood. We expect the possibility that PBMNCs will be a good source to monitor MRD. We could also detect and quantify the ASO-PCR products in cell-free DNA from the sera. To the best of our knowledge, this is the first report that IgH DNA fragments from MM cells circulate in the sera. Furthermore, we could detect and quantify the ASO-PCR products in CD20+CD38- B-cells in BM at diagnosis. These results indicated that clonogenic MM cells could exist not only in the CD20-CD38high plasma cell fraction but also in the CD20+CD38- B-cell fraction, which might include myeloma stem or initiating cells. Thus, we could consider the treatment strategies to include anti-CD20 antibodies against the clonogenic CD20+CD38- B-cell population. In conclusion, our ASO-PCR using various clinical materials is supposed to be useful for detecting MRD in the patients with MM as well as for clarifying the pathogenesis of MM. Disclosures Sata: Celgen: Research Funding; Takeda: Research Funding; Janssen: Research Funding. Shibayama:Celgen: Research Funding; Takeda: Research Funding; Janssen: Research Funding. Habuchi:Celgen: Research Funding; Takeda: Research Funding; Janssen: Research Funding. Fukushima:Celgen: Research Funding; Takeda: Research Funding; Janssen: Research Funding. Fujita:Celgen: Research Funding; Takeda: Research Funding; Janssen: Research Funding. Ezoe:Celgen: Research Funding; Takeda: Research Funding; Janssen: Research Funding. Tadokoro:Celgen: Research Funding; Takeda: Research Funding; Janssen: Research Funding. Maeda:Celgen: Research Funding; Takeda: Research Funding; Janssen: Research Funding. Mizuki:Celgen: Research Funding; Takeda: Research Funding; Janssen: Research Funding. Oritani:Celgen: Research Funding; Takeda: Research Funding; Janssen: Research Funding. Kanakura:Janssen: Research Funding; Takeda: Research Funding; Celgen: Research Funding.
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Fiala, Mark A., Tanya M. Wildes, Mark A. Schroeder, Armin Ghobadi, Keith E. Stockerl-Goldstein, and Ravi Vij. "The Characteristics, Treatment Patterns, and Outcomes of Older Adults with Multiple Myeloma." Blood 132, Supplement 1 (November 29, 2018): 4463. http://dx.doi.org/10.1182/blood-2018-99-118660.
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Abstract Background: Advances in the treatment for multiple myeloma (MM) have dramatically improved outcomes for younger patients. Older adults, particularly those 80 years of age or older at diagnosis, have seen more modest gains. MM incidence increases with age, and as more of the population is living later into life, the segment of the MM population over 80 will continue to grow. In this study, we sought to better understand the characteristics, treatment, and outcomes of older patients with MM. Methods: We identified all patients diagnosed with MM at age 80 or older in the Surveillance, Epidemiology, and End Results Program (SEER) database from 2007-2013 to determine incidence and outcomes. Subset analysis was then performed on patients included in the SEER-Medicare linked database who were enrolled in Medicare Parts A, B, and D to further explore patient characteristics and treatment patterns. Results: The incidence of MM increases over age, peaking after age 80. The annual incidence for those aged 65-69, 70-74, 75-79, 80-84 and 85+ was 24.4, 32.7, 39.5, 42.8 and 36.4 per 100,000, respectively. Based on 2010 US population estimates, approximately 4,500 new cases of MM were diagnosed annually 2007-2013 in patients age 80 or older. In that period, 8,093 cases, approximately 1,150 per year, were reported to SEER. The estimated median overall survival (OS) of these patients was 14 months (95% CI 13.2-14.8). The estimated relative 12 month survival was 58.9% (95% CI 57.4-60.4) compared to their peers without cancer. Of the 8,093 cases of MM reported to SEER during the study period, 2,385 were present in the SEER-Medicare linked dataset. Of these, 225 were identified as smoldering MM using a previously established algorithm (Fiala, et al, JCOCCI, 2018) and excluded leaving 2,160 for the analyses. The median age was 84 (range 80-100) and 55% were female. 81% were white, 13% black or African-American, and 6% another race. At disease presentation, 22% had claims indicating hypercalcemia, 61% renal failure or chronic kidney disease, 59% anemia, and 34% MM bone involvement. The estimated median OS was 13.4 months (95% CI 12.2-15.1). Only 52% of patients had claims indicating they received systemic MM treatment within 6 months post-diagnosis. Nearly all that did received novel agents; 38% received bortezomib-based treatment, 41% immunomodulatory drug (IMID)-based, and 14% both. The others received antineoplastic chemotherapies such as melphalan or cyclophosphamide. Interestingly, bortezomib utilization increased incrementally from 25% of patients treated in 2007 to 62% in 2013 while IMID utilization declined from 67% to 49%. The median OS of those receiving treatment was 21 months (95% CI 18.5-23.1) compared to 6.3 months (95% CI 5.3-7.3) for those who did not (p <0.0001). MM treatment was associated with a 26% decrease in hazard for death (aHR 0.74; 95% CI 0.67-0.82; p < 0.0001) independent of age, race, gender, poverty, comorbidities, and proxy measures of performance status. Outcomes improved for patients in more recent years; the hazard for death decreased by 3% (HR 0.97; 95% CI 0.94-0.99; p = 0.0096) each year 2007-2013. This can be attributed to increasing treatment rates. In 2007, only 41% of patients received treatment compared to 61% in 2013. After controlling for MM treatment, the year of diagnosis was no longer a significant predictor of survival. Conclusions: The outcomes of patients with MM over 80 years old are still relatively poor; nearly half of the patients do not receive systemic treatment and for those who do the median OS is just 21 months. The population over 80, when MM incidence peaks, is projected to triple over the next few decades. It is imperative that we improve our understanding of the needs of this vulnerable subgroup of patients of MM. Disclosures Schroeder: Amgen Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Vij:Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jansson: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.
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Wagner, Henri. "Willard Van Orman Quine. The Significance of the New Logic, traduit par W. Carnielli, F. Janssen-Lauret et W. Pickering (dir.) ; introduction par les éditeurs accompagnée d’un essai de F. Janssen-Lauret, Cambridge, Cambridge University Press, 2018, 168 pages." Philosophiques 47, no. 1 (2020): 239. http://dx.doi.org/10.7202/1070260ar.
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Roccati, G. Matteo. "La Fortune. Thèmes, représentations, discours, études rassemblées par Yasmina Foehr-Janssens et Emmanuelle Métry." Studi Francesi, no. 143 (XLVIII | II) (December 1, 2004): 329. http://dx.doi.org/10.4000/studifrancesi.38841.
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Croft, James, Andrew Hall, Amy L. Sherborne, Katrina Walker, Sidra Ellis, Kim Sharp, Amy Price, et al. "Prognostic Molecular Stratification in Relapsed/Refractory Multiple Myeloma - Results of the Pomalidomide Mukseven (NCT02406222) Biomarker Trial." Blood 134, Supplement_1 (November 13, 2019): 4327. http://dx.doi.org/10.1182/blood-2019-123640.
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Background Treatment of relapsed/refractory multiple myeloma (RRMM) remains challenging as durable remissions are achieved in patient sub-groups only. Identifying patients that are likely to benefit prior to or early after starting relapse treatments remains an unmet need. MUKseven is a trial specifically designed to investigate and validate biomarkers for treatment optimization in a 'real-world' RRMM population. Design In the randomized multi-center phase 2 MUKseven trial, RRMM patients (≥2 prior lines of therapy, exposed to proteasome inhibitor and lenalidomide) were randomized 1:1 to cyclophosphamide (500 mg po d1, 8, 15), pomalidomide (4 mg days 1-21) and dexamethasone (40 mg; if ≥75 years 20 mg; d1, 8, 15, 21) (CPomD) or PomD and treated until progression. All patients were asked to undergo bone marrow (BM) and peripheral blood (PB) bio-sampling at baseline, cycle 1 day 14 (C1D14, on-treatment) and relapse. For biomarker discovery and validation, IGH translocations were profiled by qRT-PCR, copy number aberrations by digital MLPA (probemix D006; MRC Holland), GEP by U133plus2.0 array (Affymetrix), PD protein markers by IHC and PB T-cell subsets by flow cytometry for all patients with sufficient material. Primary endpoint was PFS, secondary endpoints included response, OS, safety/toxicity and biomarker validation. Original planned sample size was 250 patients but due to a change in UK standard of care during recruitment with pomalidomide becoming available, a decision was made to stop recruitment early. Results In total, 102 RRMM patients were randomized 1:1 between March 2016 and February 2018. Trial entry criteria were designed to include a real-world RRMM population, permitting transfusions and growth factor support. Median age at randomization was 69 years (range 42-88), 28% of patients had received ≥5 prior lines of therapy (median: 3). Median follow-up for this analysis was 13.4 months (95% CI: 12.0-17.5). 16 patients remained on trial at time of analysis (median number of cycles: 19.5; range 8-28). More patients achieved ≥PR with CPomD compared to PomD: 70.6% (95% CI: 56.2-82.5%) vs. 47.1% (CI: 32.9-61.5%) (P=0.006). Median PFS was 6.9 months (CI: 5.7-10.4) for CPomD vs. 4.6 months (CI: 3.5-7.4) for PomD, which was not significantly different as per pre-defined criteria. Follow-up for OS is ongoing and will be presented at the conference. High-risk genetic aberrations were found at following frequencies: t(4;14): 6%, t(14;16)/t(14;20): 2%, gain(1q): 45%, del(17p): 13%. Non-high risk lesions were present as follows: t(11;14): 22%, hyperdiploidy: 44%. Complete information on all high-risk genetic markers was available for 71/102 patients, of whom 12.7% had double-hit high-risk (≥2 adverse lesions), 46.5% single-hit high-risk (1 adverse lesion) and 40.8% no risk markers, as per our recent meta-analysis in NDMM (Shah V, et al., Leukemia 2018). Median PFS was significantly shorter for double-hit: 3.4 months (CI: 1.0-4.9) vs. single-hit: 5.8 months (CI: 3.7-9.0) or no hit: 14.1 months (CI: 6.9-17.3) (P=0.005) (Figure 1A). GEP was available for 48 patients and the EMC92 high-risk signature, present in 19% of tumors, was associated with significantly shorter PFS: 3.4 months (CI: 2.0-5.7) vs. 7.4 (CI: 3.9-15.1) for EMC92 standard risk (P=0.037). Pharmacodynamic (PD) profiling of cereblon and CRL4CRBN ubiquitination targets (including Aiolos, ZFP91) in BM clots collected at baseline and C1D14 is currently ongoing. Preliminary results for the first 10 patients demonstrate differential change of nuclear Aiolos (Figure 1C), with a major decrease in Aiolos H-scores in 7/10 patients from baseline to C1D14 and reconstitution at relapse. T-cell PB sub-sets were profiled at baseline and C1D14 by flow cytometry. Specific sub-sets increased with therapy from baseline to C1D14, e.g. activated (HLA-DR+) CD4+ T-cells, as reported at last ASH. CD4+ T-cell % at baseline was associated with shorter PFS in these analyses in a multi-variable Cox regression model (P=0.005). PD and T-cell biomarker results will be updated and integrated with molecular tumor characteristics and outcome. Discussion Our results demonstrate that molecular markers validated for NDMM predict treatment outcomes in RRMM, opening the potential for stratified delivery of novel treatment approaches for patients with a particularly high unmet need. Additional immunologic and PD biomarkers are currently being explored. Disclosures Croft: Celgene: Other: Travel expenses. Hall:Celgene, Amgen, Janssen, Karyopharm: Other: Research funding to Institution. Walker:Janssen, Celgene: Other: Research funding to Institution. Pawlyn:Amgen, Janssen, Celgene, Takeda: Other: Travel expenses; Amgen, Celgene, Janssen, Oncopeptides: Honoraria; Amgen, Celgene, Takeda: Consultancy. Flanagan:Amgen, Celgene, Janssen, Karyopharm: Other: Research funding to Institution. Garg:Janssen, Takeda, Novartis: Other: Travel expenses; Novartis, Janssen: Research Funding; Janssen: Honoraria. Couto:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Wang:Celgene Corporation: Employment, Equity Ownership. Boyd:Novartis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Pierceall:Celgene: Employment. Thakurta:Celgene: Employment, Equity Ownership. Cook:Celgene, Janssen-Cilag, Takeda: Honoraria, Research Funding; Janssen, Takeda, Sanofi, Karyopharm, Celgene: Consultancy, Honoraria, Speakers Bureau; Amgen, Bristol-Myers Squib, GlycoMimetics, Seattle Genetics, Sanofi: Honoraria. Brown:Amgen, Celgene, Janssen, Karyopharm: Other: Research funding to Institution. Kaiser:Takeda, Janssen, Celgene, Amgen: Honoraria, Other: Travel Expenses; Celgene, Janssen: Research Funding; Abbvie, Celgene, Takeda, Janssen, Amgen, Abbvie, Karyopharm: Consultancy.
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Rawstron, Andy C., Walter Gregory, Ruth M. de Tute, Faith E. Davies, Susan E. Bell, Mark T. Drayson, Gordon Cook, et al. "Minimal Residual Disease (MRD) in Myeloma: Independent Outcome Prediction and Sequential Survival Benefits per Log Tumour Reduction." Blood 124, no. 21 (December 6, 2014): 3416. http://dx.doi.org/10.1182/blood.v124.21.3416.3416.
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Abstract Minimal residual disease (MRD), as assessed by flow cytometry is a powerful predictor of outcome in multiple myeloma (MM). We and others have previously demonstrated that such analyses are informative in patients treated with autologous stem cell transplant (ASCT) and non-transplant regimens. It predicts outcome in patients in conventional CR and is applicable to patients with standard and adverse risk cytogenetics. As a consequence MRD assessment is under consideration as a surrogate endpoint for clinical trials. This is urgently needed in MM as >5yrs follow-up is typically required to demonstrate survival differences in trials of upfront therapy. If surrogate end points are to be used in clinical trials it is essential that a reproducible effect is demonstrable using multivariate models. Previous studies have confirmed the effect of MRD on PFS but a consistent effect on OS has been not been definitively shown. This may in part be due to the availability of effective salvage therapy but it is also possible that the traditional threshold of 10-4 for analysis and the categorization of patients as MRD-postive or negative is suboptimal. Flow cytometry does provide a quantitative assessment of residual tumour over a large range and the degree of tumour depletion may be more informative than a positive-negative analysis. 397 patients from the MRC Myeloma IX trial were included in this analysis. Patients were randomly assigned to CTD (cyclophosphamide, thalidomide, and dexamethasone) or CVAD (cyclophosphamide, vincristine, doxorubicin, and dexamethasone) induction for 4-6 cycles followed by standard high-dose melphalan (HDM) ASCT. BM aspirates were obtained at day 100 for MRD analysis. 500,000 cells were evaluated with six-colour antibody combinations including CD138/CD38/CD45/CD19 with CD56/CD27 in all cases and CD81/CD117 in additional cases as required. PFS and OS data analysis was landmarked from the date of the MRD assesment. Of the 397 patients with MRD data available at day 100 after ASCT, 247/397 (62.2%) achieved <0.01% MRD. The level of residual disease varied across four logs in MRD-positive patients (0.01-<0.1% in 49/397, 0.1-<1% in 72/397, 1-<10% in 26/397 and ≥10% in 3/397). The PFS and OS for individuals with ≥1% residual disease was comparable to individuals with a PR/MR/SD confirming that MRD assessment is most relevant in CR. The level of MRD correlated with outcome. The median PFS for patients with ≥10% MRD at day 100 after ASCT was 0.8 years, with 1-<10% MRD was 1.7 years, with 0.1-<1% MRD was 1.9 years, with 0.01-<0.1% MRD was 2.7 years and for patients with <0.01% MRD was 3.1 years (P<0.001). The median OS for these groups was 1 yr, 4 yrs, 5.9 yrs, 6.8 yrs and for patients with <0.01% MRD not reached with >7.5 yrs median follow-up (P<0.001, see figure). A Cox proportional hazards model was used to further evaluate factors influencing outcome. B2M and MRD were log-transformed and along with age were considered as continuous variables. ISS, haemoglobin (<115g/l), platelets (<150x10^9/l) and cytogenetics were used as stratification factors. Cytogenetic groups were classified as unfavourable for patients with gain(1q), del(1p32), t(4;14), t(14;20), t(14;16), and del(17p), or favourable for hyperdiploidy, t(11;14) and t(6;14), or unknown/inevaluable. MRD assessment (χ2 11.8, P=0.0006) and cytogenetics (χ2 35.5, P=<0.0001) were the only factors that retained significance in this multivariate model. Conventional categorical response, ISS and B2M were not predictive of OS (p=0.99, 0.16 and 0.56 respectively). We would conclude that MRD quantitation is more informative than a positive or negative categorization with a 10-4 threshold and independently predicts outcome. In this analysis we were able to demonstrate an approximate 1 year survival benefit per log tumour depletion. A lower cutpoint for predicting improved outcome was not reached and more sensitive assays will likely improve outcome prediction further. This data strongly supports the role of MRD assessment as a surrogate endpoint in clinical trials. Figure 1 Figure 1. Disclosures Rawstron: Celgene: Consultancy; BD Biosciences: Consultancy, Intrasure Patents & Royalties. Gregory:Celgene: Consultancy. Davies:Celgene: Consultancy, Honoraria; Janssen-Cilag: Consultancy, Honoraria; Novartis: Consultancy. Cook:Celgene: Consultancy, Honoraria, Research Funding; Janssen-Cilag: Consultancy, Honoraria. Jackson:Celgene: Honoraria; Janssen-Cilag: Honoraria. Morgan:Celgene: Consultancy, Honoraria, Research Funding; Janssen-Cilag: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Novartis: Consultancy, Honoraria. Owen:Celgene: Consultancy, Honoraria, Research Funding.
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Ritchlin, C. T., P. Rahman, P. Helliwell, W. H. Boehncke, I. Mcinnes, A. B. Gottlieb, S. Kafka, et al. "AB0538 POOLED SAFETY RESULTS FROM TWO PHASE-3 TRIALS OF GUSELKUMAB IN PATIENTS WITH PSORIATIC ARTHRITIS THROUGH 1 YEAR." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 1300–1301. http://dx.doi.org/10.1136/annrheumdis-2021-eular.1334.
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Background:DISCOVER 1 & 2, two double-blind, phase-3, psoriatic arthritis (PsA) trials of guselkumab (GUS, an IL-23 inhibitor), demonstrated significant improvement with GUS vs placebo (PBO) in signs and symptoms of PsA, with good tolerability, at week (w) 24 during the PBO-controlled period.1,2 Beyond w24, all patients (pts) switched to GUS. Continued treatment maintained efficacy through w52.3,4Objectives:To describe pooled safety results from the DISCOVER 1 & 2 trials through 1-year of GUS treatment.Methods:Adults with active PsA (DISCOVER 1: ≥3 tender/swollen joints and C-Reactive protein [CRP] ≥0.3 mg/dL; DISCOVER 2: ≥5 tender/swollen joints and CRP ≥0.6 mg/dL) were randomized to subcutaneous GUS 100 mg at w0, w4, then every 8 w (q8w); GUS 100 mg q4w; or PBO. At w24, PBO pts switched to GUS 100 mg q4w. Pts were biologic naive except ~30% pts in DISCOVER 1. Safety was reported through w60 in DISCOVER 1 and through w52 in DISCOVER 2.Results:Baseline characteristics were similar between treatment groups in the pooled studies. Through w24 and 1 year, numbers of pts per 100 patient years with ≥1 event were similar among treatment groups for adverse events (AEs), serious AEs, infections, serious infections, and discontinuations due to AE (Table 1). At 1 year, there were no cases of active tuberculosis, opportunistic infections (including candida), or inflammatory bowel disease in GUS-treated pts; 2 deaths in PBO pts; and low incidences that were similar across treatment groups for malignancy, major adverse cardiac events, and injection-site reactions. Incidence of anti-GUS antibodies was 4.5%, and most were not neutralizing. Mild elevations in serum hepatic transaminases and decreases in neutrophil counts were consistent at 1 year with the results at w24 (Table 1).Conclusion:GUS regimens of q8w and q4w were well tolerated in PsA pts through 1 year of treatment in the phase-3 DISCOVER trials, consistent with the w24 results. No meaningful differences between incidences of AEs were reported in the q8w and q4w groups. The safety profile of GUS in PsA pts is generally comparable with the previously established safety profile of GUS.References:[1]Deodhar A et al. Lancet. 2020;395:1115[2]Mease P et al. Lancet. 2020;395:1126[3]Ritchlin C et al. EULAR 2020 # SAT0397[4]McInnes I et al. EULAR 2020 # SAT0402Table 1.Number of Patients with AEs per 100 PY and Incidence of AEs of InterestTime Period24 Weeks1 Year*Treatment GroupPBOGUS SC 100 mgPBO to GUS‡GUS SC 100 mgDosing ScheduleMatchingq8wq4wGUSCombined†q4wq8wq4wGUSCombined‡ N3723753737483523753731100Total PY Follow-Up173173172346204384385589Patients with AEs per 100 PY, n (95% CI)≥1 AE143 (123, 166)148 (127, 171)154 (132, 178)151 (136, 167)92 (77, 108)114 (100, 130)115 (101, 131)109 (100, 117)≥1 Serious AE7.1 (3.7, 12)4.1 (1.6, 8.4)4.7 (2.0, 9.3)4.4 (2.5, 7.3)7.0 (3.8, 11.8)4.8 (2.9, 7.6)4.0 (2.2, 6.6)4.9 (3.6, 6.6)≥1 Infection50 (39, 62)47 (37, 59)52 (42, 65)49 (42, 58)39 (31, 49)41 (34, 48)38 (31, 45)39 (35, 44)≥1 Serious Infection1.7 (0.4, 5.1)0.6 (0.0, 3.2)1.8 (0.4, 5.1)1.2 (0.3, 3.0)2.5 (0.8, 5.8)1.3 (0.4, 3.1)0.8 (0.2, 2.3)1.3 (0.7, 2.3)Discontinued due to AE4.1 (1.6, 8.4)2.9 (1.0, 6.8)4.7 (2.0, 9.3)3.8 (2.0, 6.5)3.5 (1.4, 7.1)2.1 (0.9, 4.1)2.6 (1.3, 4.8)2.6 (1.7, 3.8)AEs of Interest§, n (%)Death2 (0.5)0000000Malignancy1 (0.3)2 (0.5)02 (0.3)1 (0.3)2 (0.5)03 (0.3)Major Adverse Cardiac Events1 (0.3)01 (0.3)1 (0.1)001 (0.3)1 (0.1)Opportunistic Infections00000000Tuberculosis00000000Inflammatory Bowel Disease1 (0.3)0000000Injection-Site Reaction1 (0.3)5 (1.3)4 (1.1)9 (1.2)4 (1.1)6 (1.6)9 (2.4)19 (1.7)Anti-GUS Antibody+-6/373 (1.6)9/371 (2.4)15/744 (2.0)14/350 (4.0)18/373 (4.8)17/371 (4.6)49/1094 (4.5)*Through w60 for DISCOVER 1 and w52 for DISCOVER 2; †Combined GUS q8w and q4w; ‡For patients who switched from PBO to GUS, only data on and after first GUS administration were included in this group; §PBO N=370.AE, adverse event; CI, confidence interval; GUS, guselkumab; PBO, placebo; PY, patient year; q4w, every 4 weeks; q8w, every 8 weeks; SC, subcutaneous; w, weekDisclosure of Interests:Christopher T. Ritchlin Grant/research support from: Received grant/research support from UCB Pharma, AbbVie, Amgen, consultation fees from UCB Pharma, Amgen, AbbVie, Lilly, Pfizer, Novartis, Gilead, Janssen, Proton Rahman Speakers bureau: Received speakers fees from Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, Pfizer, Grant/research support from: Received grant/research support from Janssen and Novartis, consultation fees from Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, and Pfizer., Philip Helliwell Consultant of: Consultation fees paid to charity (AbbVie, Amgen, Pfizer, UCB) or himself (Celgene, Galapagos), Grant/research support from: Received grants/research support paid to charity (AbbVie, Janssen, Novartis), Wolf-Henning Boehncke Consultant of: Received consultation fees from Janssen, Grant/research support from: Received grant/research support from Janssen Research & Development, LLC, Iain McInnes Consultant of: Received consultation fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Gilead, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: Received grant/research support from Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, and UCB, Alice B Gottlieb Speakers bureau: Received speakers fees from Pfizer, AbbVie, BMS, Lilly, MSD, Novartis, Roche, Sanofi, Sandoz, Nordic, Celltrion and UCB, Consultant of: Received consultation fees from Pfizer, AbbVie, BMS, Lilly, MSD, Novartis, Roche, Sanofi, Sandoz, Nordic, Celltrion and UCB, Grant/research support from: Received grant/research support from Pfizer, AbbVie, BMS, Lilly, MSD, Novartis, Roche, Sanofi, Sandoz, Nordic, Celltrion and UCB, Shelly Kafka Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Alexa Kollmeier Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Elizabeth C Hsia Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Xie L Xu Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, May Shawi Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Shihong Sheng Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Prasheen Agarwal Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Bei Zhou Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Paraneedharan Ramachandran Shareholder of: Shareholder of Johnson & Johnson, Employee of: Employee of Janssen Research & Development, LLC, Philip J Mease Speakers bureau: Received speakers fees from Abbott, Amgen, Biogen Idec, BMS, Eli Lilly, Genentech, Janssen, Pfizer, UCB – speakers bureau, Consultant of: Received consultation fees from Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB, Grant/research support from: Received grant/research support from Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB.
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Puig, Noemi, Teresa Contreras, Bruno Paiva, María Teresa Cedena, José J. Pérez, Irene Aires, Cristina Agullo, et al. "Heavy and Light Chain Monitoring in High Risk Smoldering Multiple Myeloma Patients Included in the GEM-CESAR Trial: Comparison with Conventional and Minimal Residual Disease IMWG Response Assessment." Blood 134, Supplement_1 (November 13, 2019): 1852. http://dx.doi.org/10.1182/blood-2019-128655.
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Introduction: The GEM-CESAR trial is a potentially curative strategy for high-risk smoldering multiple myeloma (HRsMM) patients (pts) in which the primary endpoint is the achievement of bone marrow minimal residual disease (MRD) negativity. However, other methods of disease evaluation in serum such as heavy+light chain (HLC) assessment, with a potential complementary value to the IMWG response criteria, have also been tested. Aim: To evaluate the performance of HLC assay in HRsMM pts at diagnosis and after consolidation, comparing the results with standard serological methods and Next Generation Flow (NGF) for the assessment of bone marrow MRD. Patients and Methods: Ninety HRsMM pts included in the GEM-CESAR trial received six 4-weeks cycles of carfilzomib, lenalidomide and dexamethasone followed by high dose melphalan and 2 further cycles of consolidation with the same regimen. All pts received maintenance treatment with lenalidomide for up to 2 years. SPEP and IFE were performed using standard procedures. Serum IgGk, IgGl, IgAk and IgAl HLC concentrations were measured using Hevylite (The Binding Site Group Ltd, Birmingham, UK) on a SPA PLUS turbidimeter. HLC concentrations and ratios were considered abnormal if they were outside the 95% reference ranges provided by the manufacturer. MRD was analyzed by flow cytometry following EuroFlow recommendations (sensitivity, 2x10-6). Standard response assignment was carried out as per the IMWG guidelines. Hevylite responses were assigned and HLC-pair suppression was defined as in Michalet et al (Leukemia 2018). Results: Out of 90 HRsMM pts, 75 had monoclonal intact immunoglobulin and samples available at diagnosis (50 IgG and 25 IgA). HLC ratio was abnormal in 98% of IgG pts and in 100% of IgA pts. Response assessment by Hevylite and standard IMWG criteria were available in 62 pts post-consolidation (Table 1). A good agreement was found between the two methods (kappa quadratic weighting = 0,6327 (0,4016 - 0,8638)). Among 46 pts with assigned CR as per the IMWG response criteria, there were 3 and 8 pts in PR and VGPR according to the Hevylite method, respectively. In 62 cases, paired Hevylite and MRD assessment data were available. Concordant results were found in 72.5% of cases (45/62; HLC+/NGF+ in 15 and HLC-/NGF- in 30 cases) while in the remaining 27.4% of cases results were discordant (17/62; HLC-/NGF+ in 6 and HLC+/NGF- in 11 cases). Post-consolidation, 24, 25.8 and 42.3% of the 62 samples were positive by SPEP, NGF and Hevylite, respectively. HLC-pair suppression was identified in 13/62 pts; 10 had severe HLC-pair suppression at the end of consolidation. After a median follow-up of 32 months (8-128), 93% of pts remain alive and progression-free. Three patients that have already progressed had their responses assessed post-consolidation. The first pt was assigned VGPR by the standard IMWG criteria and PR by Hevylite and was MRD positive by NGF; the second pt was assigned CR by IMWG criteria and Hevylite but had severe HLC-pair immunosuppression and was MRD positive by NGF; the third pt was in CR by IMWG and HLC criteria and was MRD positive by MFC. Conclusions: Moderate agreement was found between response assessment by Hevylite and the standard IMWG methods as well as between Hevylite and MRD assessment by NGF. Most discordances were a result of Hevylite detecting disease in samples negative by the standard methods, but longer follow-up is needed to ascertain its clinical value. HLC assessment could have anticipated the progression noted in 2 (out of 3) patients. Disclosures Puig: Takeda, Amgen: Consultancy, Honoraria; The Binding Site: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Paiva:Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, Novartis, Roche and Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene, Janssen, Sanofi and Takeda: Consultancy. Rodriguez Otero:Kite Pharma: Consultancy; Celgene Corporation: Consultancy, Honoraria, Speakers Bureau; BMS: Honoraria; Janssen: Consultancy, Honoraria; Takeda: Consultancy. Oriol:Celgene, Amgen, Takeda, Jansse: Consultancy, Speakers Bureau. Rios:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Alegre:Celgene, Amgen, Janssen, Takeda: Membership on an entity's Board of Directors or advisory committees. de la Rubia:Amgen: Consultancy; Janssen: Consultancy; Celgene: Consultancy; Takeda: Consultancy; AbbVie: Consultancy. De Arriba:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Honoraria. Ocio:Celgene: Consultancy, Honoraria, Research Funding; Sanofi: Research Funding; BMS: Honoraria; Novartis: Consultancy, Honoraria; Array Pharmaceuticals: Research Funding; Pharmamar: Consultancy; Seattle Genetics: Consultancy; Mundipharma: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; AbbVie: Consultancy; Janssen: Consultancy, Honoraria. Bladé:Janssen, Celgene, Amgen, Takeda: Membership on an entity's Board of Directors or advisory committees; Irctures: Honoraria. Mateos:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmamar: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; EDO: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees.
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Jenner, Matthew, Amy L. Sherborne, Andrew Hall, Vallari Shah, Katrina Walker, Sidra Ellis, Kim Sharp, et al. "Molecular Treatment Stratification for Newly Diagnosed High-Risk Myeloma, Including Plasma Cell Leukemia - Feasibility Results of the Ukmra Optimum: MUK9 Trial (NCT03188172)." Blood 134, Supplement_1 (November 13, 2019): 3162. http://dx.doi.org/10.1182/blood-2019-123547.
Full textAbstract:
Background High-risk myeloma patients have unsatisfactory outcomes with current treatments and are in urgent need of improved diagnostic and therapeutic strategies. We have recently validated specific markers predicting high-risk disease in newly diagnosed MM (NDMM), in particular double-hit with presence of ≥2 consensus high-risk markers t(4;14), t(14;16), t(14;20), del(1p), gain(1q), del(17p) (Shah V, et al., Leukemia 2018) and diagnostic GEP SKY92 high risk signature (Sherborne A, et al., IMW 2017). Diagnostic tests for these markers were implemented in the UK multi-center OPTIMUM: MUK9 trial to prospectively stratify therapy for high-risk NDMM. Trial design OPTIMUM: MUK9 is a phase 2 trial for transplant eligible NDMM, consisting of two inter-related protocols: a molecular screening protocol (MUK9A) and an interventional trial (MUK9B) for high-risk MM identified in MUK9A. Patients with suspected or confirmed MM fit for intensive therapy enrolled in MUK9A have central molecular profiling at ICR, London, of CD138-selected BM MM cells for translocations, copy number aberrations (qRT-PCR; MLPA P425, MRC Holland) and SKY92 signature status (MMprofiler; SkylineDx). If clinically indicated SOC therapy (VTD, max. 2 cycles) can be given whilst central results are generated. Patients found to have high-risk MM by double-hit and/or SKY92 are offered enrolment into MUK9B. All other patients receive SOC (VTD, HD-MEL+ASCT) for which clinical data is collected. Patients diagnosed with plasma cell leukemia (PCL) can be enrolled directly in MUK9B. MUK9B treatment consists of quintuplet daratumumab, cyclophosphamide, bortezomib, lenalidomide, dexamethasone (Dara-CVRd) induction (up to 6 cycles), bortezomib-augmented single HD-MEL+ASCT, Dara-VRd consolidation 1 (6 cycles), Dara-VR consolidation 2 (12 cycles) and Dara-R maintenance (until PD). Dose adjustments are permitted in order to maximize tolerability of long-term therapy. Patient reported outcomes (PRO) are recorded at baseline and throughout treatment. Response and MRD are centrally assessed (Birmingham, Leeds). Primary endpoint for MUK9A is feasibility of central molecular testing within 56 days turnaround time, which we report on here. Primary endpoint of MUK9B is treatment efficacy, comparing MUK9B PFS to near-concurrent molecularly matched high-risk patient outcomes from UK NCRI Myeloma XI using a Bayesian design. Secondary endpoints include safety, PFS2, MRD and OS and study of molecular evolution in high-risk disease. Results The protocol recruited 29/Sep/17 - 31/Jul/19 at 39 UK sites, achieving the recruitment target of 105 high-risk patients treated on MUK9B ahead of projections. At the time of analysis (12/Jul/19), 430 patients with suspected or confirmed NDMM have been recruited to MUK9A across 39 UK NHS hospitals. Of these, 376 (87%) patients were confirmed to have symptomatic MM (60.9% male; median age 61y (range 29-79)) as per updated IMWG diagnostic criteria (2014), including 9 (2%) PCL patients, with the remainder diagnosed as SMM/MGUS (31; 7%) or other (14; 3%). For 371 of the 376 symptomatic MM patients BM was received by the central laboratory and was of sufficient quality for profiling in 331 (89%) patients. Repeat samples were requested for all others and a sufficient sample received for 20/45 (44%). Central results were successfully reported within the pre-specified 56 day interval for all patients (median 17 days; IQR 13-22). Of 346 patients with a reported result, 128 (37.0%) have high-risk MM, with molecular characteristics mirroring Myeloma XI patients (Figure 1). PCL patients show expected characteristics as listed in Table 1. Basic demographics were not different between high-risk vs. non-high-risk. 101 high-risk patients have or are planning to enter MUK9B, 10 pending decision; 17 high-risk patients did not enter MUK9B, the majority due to ineligibility. 92 patients have started Dara-CVRD therapy. There are currently no safety concerns, the majority of patients are completing induction successfully; 1 patient stopped induction therapy due to adverse events. Updated results will be presented. Discussion Our data demonstrate feasibility of multi-center molecular stratified trial delivery for high-risk NDMM patients. These early trial results strongly support accelerated trial strategies for MM patient groups with high unmet need and rational drug development specifically for high-risk MM. Disclosures Jenner: Abbvie, Amgen, Celgene, Novartis, Janssen, Sanofi Genzyme, Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Hall:Celgene, Amgen, Janssen, Karyopharm: Other: Research funding to Institution. Walker:Janssen, Celgene: Other: Research funding to Institution. Croft:Celgene: Other: Travel expenses. Jackson:Celgene, Amgen, Roche, Janssen, Sanofi: Honoraria. Flanagan:Amgen, Celgene, Janssen, Karyopharm: Other: Research funding to Institution. Drayson:Abingdon Health: Consultancy, Equity Ownership. Owen:Celgene, Janssen: Consultancy; Celgene: Research Funding; Janssen: Other: Travel expenses; Celgene, Janssen: Honoraria. Pratt:Binding Site, Amgen, Takeda, Janssen, Gilead: Consultancy, Honoraria, Other: Travel support. Cook:Celgene, Janssen-Cilag, Takeda: Honoraria, Research Funding; Janssen, Takeda, Sanofi, Karyopharm, Celgene: Consultancy, Honoraria, Speakers Bureau; Amgen, Bristol-Myers Squib, GlycoMimetics, Seattle Genetics, Sanofi: Honoraria. Brown:Amgen, Celgene, Janssen, Karyopharm: Other: Research funding to Institution. Kaiser:Celgene, Janssen: Research Funding; Abbvie, Celgene, Takeda, Janssen, Amgen, Abbvie, Karyopharm: Consultancy; Takeda, Janssen, Celgene, Amgen: Honoraria, Other: Travel Expenses.
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Mease, P. J., P. Foley, K. Reich, J. Bagel, M. Lebwohl, Y. W. Yang, M. Shawi, et al. "POS1031 LOW INCIDENCE OF GASTROINTESTINAL-RELATED AND OVERALL SERIOUS ADVERSE EVENTS AMONG GUSELKUMAB-TREATED PATIENTS: POOLED ANALYSES OF VOYAGE 1 & 2 AND DISCOVER 1 & 2 THROUGH 1-YEAR." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 787–88. http://dx.doi.org/10.1136/annrheumdis-2021-eular.558.
Full textAbstract:
Background:Guselkumab (GUS), a human monoclonal antibody that specifically binds to the p19-subunit of interleukin (IL)-23, demonstrated efficacy in the Phase 3 VOYAGE 1&2 trials of patients (pts) with moderate to severe plaque psoriasis (PsO)1,2 and in the DISCOVER 1&2 trials of pts with active psoriatic arthritis (PsA).3,4 IL-17 inhibitors used to treat PsO and PsA have been associated with exacerbation or new onset of inflammatory bowel disease (IBD) (e.g., Crohn’s disease or ulcerative colitis).5Objectives:Evaluate the incidence of gastrointestinal (GI)-related and overall serious adverse events (SAEs) from pooled safety data through 1-year of GUS 100 mg treatment from the VOYAGE 1&2 and DISCOVER 1&2 trials.Methods:Using pooled safety data from the VOYAGE 1&2 PsO trials and DISCOVER 1&2 PsA trials, SAEs related to GI disorders were identified using the Medical Dictionary for Regulatory Activities (MedDRA) system-organ class “GI disorders”. Pts with a previous history of IBD were not excluded in these trials; medical history of IBD was collected at baseline in DISCOVER 1&2. Rates of overall SAEs and GI-related SAEs were calculated as the number of SAEs per 100 pt-years (PY) of follow-up (95% confidence intervals). Data are presented for the placebo (PBO)-controlled period (Weeks 0-16 for VOYAGE 1&2; Weeks 0-24 for DISCOVER 1&2) and through 1-year (defined as through Week 48 for VOYAGE 1&2; through Week 60 for DISCOVER 1, and through Week 52 for DISCOVER 2). Events of uveitis and opportunistic infections were also analyzed.Results:Through the PBO-controlled period, the overall rates of GI-related SAEs per 100 PY for pooled VOYAGE 1&2 were: PBO 0.78 (0.02, 4.34), GUS q8w 0; and for pooled DISCOVER 1&2: PBO 0.58 (0.01, 3.23), GUS q8w 0.58 (0.01, 3.21), GUS q4w 0. The GI-related SAEs included: gastrointestinal hemorrhage (PBO; n=1) for pooled VOYAGE 1&2; and inflammatory bowel disease (PBO; n=1) and mechanical ileus (GUS q8w; n=1) for pooled DISCOVER 1&2. Through 1-year, the overall rates of GI-related SAEs for pooled VOYAGE 1&2 were: Combined GUS group (GUS q8w and PBO→GUS groups) 0.51 (0.17, 1.20); and for pooled DISCOVER 1&2: GUS q8w 0.52 (0.06, 1.88), GUS q4w 0, Combined GUS group (GUS q8w, GUS q4w, and PBO→GUS groups) 0.21 (0.02, 0.74). The GI-related SAEs in the Combined GUS group for pooled VOYAGE 1&2 included: gastritis, hemorrhoids, inguinal hernia, pancreatitis, and umbilical hernia (0.10/100PY [0.00, 0.57]; n=1 for each); and in the Combined GUS group for pooled DISCOVER 1&2: mechanical ileus and pancreatitis chronic (0.10/100PY [0.00, 0.57]; n=1 for each). Overall, no cases of exacerbation or new onset of IBD were reported in GUS-treated pts, including 2 pts with a prior history of IBD in DISCOVER 1&2 (total PY of follow-up for the Combined GUS groups in VOYAGE and DISCOVER were 974 and 973, respectively). Through the PBO-controlled period, rates of overall SAEs for GUS-treated pts were comparable to PBO-pts and SAE rates remained low through 1-year of follow-up in the VOYAGE 1&2 and DISCOVER 1&2 trials. There were no reported cases of uveitis, opportunistic infections, or tuberculosis in GUS-treated pts through 1-year.Conclusion:Through 1-year of follow-up with GUS treatment in pooled VOYAGE 1&2 and DISCOVER 1&2, GI-related SAE rates were low. There were no reported cases of uveitis, opportunistic infections, or new onset/exacerbation of IBD in GUS-treated pts. No new safety concerns were identified through 1-year.References:[1]Blauvelt A., et al. J Am Acad Dermatol. 2017;76:405-17.[2]Reich K., et al. J Am Acad Dermatol. 2017;76:418-31.[3]Deodhar A., et al. Lancet. 2020;395:1115-25.[4]Mease P.J., et al. Lancet. 2020; 395:1126-36.[5]Hohenberger M., et al. J Dermatolog Treat. 2018;29:13-8.Disclosure of Interests:Philip J Mease Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Novartis, Pfizer, SUN, and UCB, Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, SUN, and UCB, Peter Foley Speakers bureau: AbbVie, Celgene, Janssen, Lilly, Merck, Novartis, Pfizer, Valeant, Galderma, GSK, Leo Pharma, and Roche, Consultant of: Janssen, Lilly, Novartis, Pfizer, Galderma, AbbVie, Amgen, AstraZeneca, Arcutis, Aslan, Boehringer Ingelheim, Celgene, Hexima, Merck, Sun Pharma, UCB Pharma, Valeant, BMS, Celtaxsys, CSL, Cutanea, Dermira, Genentech, GSK, Leo Pharma, Regeneron Pharmaceuticals Inc, Reistone, Roche, and Sanofi, Grant/research support from: AbbVie, Amgen, Celgene, Janssen, Leo Pharma, Lilly, Merck, Novartis, Pfizer, Sanofi, and Sun Pharma; travel grants from AbbVie, Janssen, Lilly, Merck, Novartis, Pfizer, Galderma, Leo Pharma, Roche, Sun Pharma, and Sanofi, Kristian Reich Consultant of: AbbVie, Amgen, Gilead, Janssen, Lilly, Novartis, Pfizer, and UCB Pharma, Grant/research support from: AbbVie, Amgen, and UCB Pharma, Jerry Bagel Speakers bureau: AbbVie, Celgene Corporation, Eli Lilly, Janssen Biotech, and Novartis, Consultant of: AbbVie, Amgen, Celgene Corporation, Eli Lilly and Company, Janssen Biotech, Leo Pharma, Novartis, Sun Pharmaceutical Industries Ltd, and Valeant Pharmaceuticals, Grant/research support from: AbbVie, Amgen, Arcutis Biotherapeutics, Boehringer Ingelheim, Bristol Myers Squibb, Celgene Corporation, Corrona, LLC, Dermavant Sciences, LTD, Dermira/UCB, Eli Lilly and Company, Glenmark Pharmaceuticals Ltd, Janssen Biotech, Kadmon Corporation, Leo Pharma, Lycera Corp, Menlo Therapeutics, Novartis, Pfizer, Regeneron Pharmaceuticals, Sun Pharma, Taro Pharmaceutical Industries Ltd, and Valeant Pharmaceuticals, Mark Lebwohl Consultant of: Aditum Bio, Allergan, Almirall, Arcutis, Inc., Avotres Therapeutics, BirchBioMed Inc., BMD skincare, Boehringer-Ingelheim, Bristol-Myers Squibb, Cara Therapeutics, Castle Biosciences, Corrona, Dermavant Sciences, Evelo, Evommune, Facilitate International Dermatologic Education, Foundation for Research and Education in Dermatology, Inozyme Pharma, Kyowa Kirin, LEO Pharma, Meiji Seika Pharma, Menlo, Mitsubishi, Neuroderm, Pfizer, Promius/Dr. Reddy’s Laboratories, Serono, Theravance, and Verrica, Grant/research support from: Abbvie, Amgen, Arcutis, Boehringer Ingelheim, Dermavant, Eli Lilly, Evommune, Incyte, Janssen, Leo Pharmaceutucals, Ortho Dermatologics, Pfizer, and UCB, Ya-Wen Yang Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC, May Shawi Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC, Megan Miller Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Alexa Kollmeier Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Elizabeth C Hsia Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Xie L Xu Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Miwa Izutsu Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Paraneedharan Ramachandran Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Shihong Sheng Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Yin You Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development, LLC, Philip Helliwell Consultant of: Galapagos, Janssen, Novartis, Grant/research support from: Abbvie, Janssen, Pfizer, Wolf-Henning Boehncke Speakers bureau: AbbVie, Almirall, Celgene, Janssen, Leo, Lilly, Novartis, and UCB Pharma, Consultant of: AbbVie, Almirall, Celgene, Janssen, Leo, Lilly, Novartis, and UCB Pharma, Grant/research support from: Pfizer
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McBride, Ali, Karen MacDonald, and Ivo Abraham. "Conversion to Biosimilar Pegfilgrastim-Jmdb from Pegfilgrastim with on-Body Injector Device in Diffuse Large B-Cell Lymphoma: Simulation Modeling of Cost-Savings and Budget-Neutral Expanded Access to Prophylaxis and Anti-Neoplastic Therapy Considering Device Failure Rate." Blood 136, Supplement 1 (November 5, 2020): 22. http://dx.doi.org/10.1182/blood-2020-142749.
Full textAbstract:
Introduction: Approvals of biosimilar pegfilgrastim products in recent years have reduced the costs of single-dose prophylaxis of chemotherapy-induced (febrile) neutropenia (CIN/FN). While reference pegfilgrastim with on-body injector (PEG-OBI) offers convenience to patients over use of next day pre-filled syringe (PFS), PEG-OBI has a reported failure rate of 1.7-6.9% that predisposes patients to increased risk of CIN/FN episodes. Incremental FN-related hospitalizations (FN-HOSP) associated with PEG-OBI failure contribute to the cost differential between PEG-OBI and assured prophylaxis with biosimilar PEG-PFS. Cost savings generated from conversion to biosimilar PEG-jmdb create opportunities for providing expanded access on a budget-neutral basis to additional CIN/FN prophylaxis or anti-neoplastic treatment. Hence, in a panel of 15,000 patients with diffuse large B-cell lymphoma (DLBCL), we aimed to: 1) quantify the cost-savings from assured prophylaxis with biosimilar PEG-jmdb over PEG-OBI accounting for device failures, 2) simulate the additional CIN/FN prophylaxis that could be achieved from the cost-savings, and 3) model the expanded access to anti-neoplastic treatment with rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP) that could be provided on a budget-neutral basis through reallocation of cost-savings. Methods: Simulation analysis in a panel of 15,000 DLBCL patients at risk for CIN/FN from the US payer perspective utilized. Costs of medication were based on Q1 2020 average selling price (ASP) for PEG-OBI, PEG-jmdb, and R-CHOP drugs derived from CMS Q3 2020 reimbursement limits; cost of PEG-OBI and PEG-jmdb administration per CMS Outpatient Prospective Payment System; between one and six cycles of prophylaxis; conversion rates from PEG-OBI to biosimilar PEG-jmdb ranging from 10% to 100%; and PEG-OBI failure rates of 1% to 7%. Differential base rate of FN-HOSP in NHL (rate of FN-HOSP without colony-stimulating factor [CSF] minus rate with CSF) was 10.03% over a 6-cycle regimen with 56% occurring in cycle 1 (Chrischilles et al., Cancer Control 2002; 13.25% with CSF, 23.28% without). FN-HOSP costs in 2012 of $25,676 per episode for NHL patients (Tai, J Oncol Pract 2017) were adjusted per the Consumer Price Index for Medical Care to $31,914 for 2020. Results: Conversion from PEG-OBI to biosimilar PEG-jmdb in a panel of 15,000 DLBCL patients generated savings ranging from $379,230 (for one cycle of prophylaxis at 10% conversion) to $22,753,800 (6 cycles at 100%) considering the cost of medication plus administration. These cost-savings could provide access to between 110 (1 cycle at 10% conversion) and 6,623 (6 cycles at 100%) additional cycles of PEG-jmdb on a budget-neutral basis, or between 58 and 3,452 cycles of R-CHOP, respectively. Taking incremental FN-HOSP costs due to PEG-OBI failure into consideration, cost-savings in cycle one from conversion to PEG-jmdb, ranged from $406,118 (at 10% conversion and PEG-OBI failure of 1%) to $5,674,454 (at 100% conversion and 7% PEG-OBI failure). These savings translated into expanded access to between 118 additional cycles of PEG-jmdb or 62 cycles of R-CHOP (at 10% conversion and 1% PEG-OBI failure) and 1,652 cycles of PEG-jmdb or 861 cycles of R-CHOP (at 100% conversion and 7% PEG-OBI failure). Over a 6-cycle regimen, savings increase to $2,323,394 (at 10% conversion and 1% PEG-OBI failure) to $26,114,789 (at 100% conversion and 7% PEG-OBI failure). These additional savings increased expanded access to PEG-jmdb to between 676 additional cycles of PEG-jmdb or 353 cycles of R-CHOP (at 10% conversion and 1% PEG-OBI failure) and 7,601 cycles of PEG-jmdb or 3,962 cycles of R-CHOP (at 100% conversion and 7% PEG-OBI failure). Conclusions: CIN/FN prophylaxis with biosimilar PEG-jmdb generates substantial cost savings compared to PEG-OBI when considering drug and administration costs. Savings further increase when the costs of FN-HOSP related to PEG-OBI failure are taken into account. Reallocation of savings realized through conversion to biosimilar pegfilgrastim-jmdb provide expanded access to additional CIN/FN prophylaxis and anti-neoplastic treatment on a budget-neutral basis while reducing risk and associated hospitalization costs associated with inadequate prophylaxis due to device failure. Disclosures McBride: Coherus BioSciences: Consultancy, Speakers Bureau; Merck: Speakers Bureau; Pfizer: Consultancy; Sandoz: Consultancy; MorphoSys: Consultancy; Bristol-Myers Squibb: Consultancy. MacDonald:Sandoz: Consultancy; Coherus BioSciences: Research Funding; Mylan: Consultancy; Novartis: Consultancy; Janssen: Consultancy; Rockwell Medical: Consultancy; Terumo: Consultancy; Celgene: Consultancy; MorphoSys: Consultancy. Abraham:Sandoz: Consultancy; Mylan: Consultancy; Janssen: Consultancy; Rockwell Medical: Consultancy; Terumo: Consultancy; Celgene: Consultancy; Coherus BioSciences: Research Funding, Speakers Bureau; MorphoSys: Consultancy.
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Leleu, Xavier, Guillemette Fouquet, Lionel Karlin, Brigitte Kolb, Mourad Tiab, Carla Araujo, Nathalie Meuleman, et al. "IFM2012-03." Blood 128, no. 22 (December 2, 2016): 2128. http://dx.doi.org/10.1182/blood.v128.22.2128.2128.
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Abstract Background. Melphalan plus prednisone and bortezomib combination is the most frequent standard of care used upfront for newly diagnosed elderly myeloma (eNDMM). Despite significant improvements with bortezomib sub-cutaneous administration and weekly schedule, safety profile issues remain with MPV, that only can be resolved with lowering the doses, albeit of the potential loss of efficacy. Carfilzomib (K), a novel generation proteasome inhibitor, has different safety profile with absence of neuropathy. Carmysap, a phase I/II trial of twice weekly Carfilzomib plus MP in eNDMM, demonstrated carfilzomib MTD at 36mg/m2. The safety profile appeared otherwise good for this frail population. We hypothesized that Carfilzomib can be used on a weekly schedule allowing to increase the dose of Carfilzomib given its positive safety profile. Methods. IFM2012-03 (carmysap weekly) is a phase 1/2 multicenter symptomatic eNDMM (65 and older) study to determine MTD during the phase 1 part and VGPR+CR rate (IMWG criteria) during the phase 2 part of KMP (Carfilzomib Weekly Plus Melphalan and Prednisone) regimen. Inclusion criteria required absolute neutrophils ≥1G/L, untransfused platelet count ≥75G/L, hemoglobine ≥8.5g/dL and clairance creatinine ≥30ml/min. Induction comprised nine 5 weeks cycles. K is given 36, 45, 56 and 70 mg/m2 on days 1, 8, 15, 22 IV route in combination to oral Melphalan 0.25mg/kg/j and oral prednisone 60mg/m2, both on days 1 to 4. Maintenance. Carfilzomib. 36 mg/m2 weekly, every two weeks IV route for 1 year. Melphalan and Prednisone is not pursued at maintenance. Analysis is done on ITT. Recruitment was 6 patients per cohort, 3 DLTs defined MTD at the lower N-1 dose. We will report at ASH the results of the phase 1 and 2. Results. 32 NDMM recruited, 30 treated in the study, 6 per cohort at K 36 mg/m², 45, 56, and 70 twice per DSMB request. The median age was 76 with 2/3rd older than 75, sex ratio M/F 1.2, R-ISS 2 and 3 in 80%.There was one DLT at K 36 (grade 4 lymphopenia), one at 45 (lysis syndrome complicated with grade 4 renal insufficiency, two at 56 (cardiac insufficiency grade 3 and febrile neutropenia grade 3) and 2 at 70 (vomiting grade 3 and liver cholestase enzyme grade 3) across the 2 70 cohorts. As a whole for the study, the ORR is 87.5%, with 45.7% at least in CR. At data cut-off, with a median follow-up at 15 months, one patient had progressed and 2 had died of whom one of cardiac dysfunction considered K related at 56. The safery profile appeared well tolerated, however, 22 SAE were reported for a total of greater than 200 cycles administered of KMP. Of particular interest, 19 SAEs were reported across the K 56 and 70 cohorts, 6 of which were cardiovascular origin. Conclusion. IFM2012-03, KMP weekly, Carfilzomib plus Melphalan and Prednisone in elderly NDMM has reached RP2D at 70mg/m2 of K. The SAE signal at the highest dose of K 70 raise concerns on using K 70 in patients older than 75-80 years old, and the DSMB may recommend for these patients to limit the RP2D at 56mg/m2 of K. Updated data for phase 1 and 2 portions will be presented at ASH for the first time. Disclosures Leleu: TEVA: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; LeoPharma: Honoraria; Pierre Fabre: Honoraria; Amgen: Honoraria; Bristol-Myers Squibb: Honoraria; Takeda: Honoraria; Celgene: Honoraria; Janssen: Honoraria. Karlin:celgene: Consultancy, Honoraria; Bristol: Consultancy; takeda: Consultancy; janssen-cilag: Consultancy, Honoraria; amgen: Consultancy, Honoraria. Meuleman:Celgene: Consultancy; Bristol-Myers-Squibb: Consultancy; Takeda: Consultancy; Amgen: Consultancy. Roussel:AMGEN: Consultancy, Other: lecture fees, Research Funding; sanofi: Other: lecture fees; celgene: Consultancy, Other: lecture fees, Research Funding; janssen: Consultancy, Other: lecture fees; BMS: Other: lecture fees. Decaux:The Binding Site: Other: supply of free light chain assays , Research Funding; SIEMENS: Honoraria, Other: supply of free light chain assays , Research Funding. Hulin:celgene: Honoraria; Bristol: Honoraria; Janssen: Honoraria; Amgen: Honoraria; takeda: Honoraria. Attal:amgen: Consultancy, Research Funding; sanofi: Consultancy; celgene: Consultancy, Research Funding; janssen: Consultancy, Research Funding. Moreau:Celgene: Honoraria; Takeda: Honoraria; Janssen: Honoraria, Speakers Bureau; Amgen: Honoraria; Novartis: Honoraria; Bristol-Myers Squibb: Honoraria. Facon:Celgene: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Bristol: Consultancy; Janssen: Consultancy, Speakers Bureau; Karyopharm: Consultancy; Novartis: Consultancy; Millenium/Takeda: Consultancy.
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Martins Rodrigues, Fernanda, Qingsong Gao, Kuan-lin Huang, Adam David Scott, Steven M. Foltz, Justin King, Mark A. Fiala, et al. "Characterization of Germline Variants in Multiple Myeloma." Blood 132, Supplement 1 (November 29, 2018): 4499. http://dx.doi.org/10.1182/blood-2018-99-118673.
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Abstract Multiple myeloma (MM) is an incurable hematological malignancy characterized by the clonal proliferation of malignant plasma cells in the bone marrow. Like other cancers, MM is a genetically complex and heterogeneous disease. One of its distinctive characteristics is that it is preceded by a pre-malignant condition known as monoclonal gammopathy of undetermined significance (MGUS), which then progresses to asymptomatic (smoldering) multiple myeloma (SMM) and, ultimately, to late-stage MM. Its progression through these stages is determined by a sequence of genomic aberrations, starting with germline events that predispose to the disease, followed by early initiating events and the later acquisition of mutations that contribute to disease progression. Although considerable progress has been made in the past 6 years in cataloguing somatic events underlying MM development and progression, little is known about its genetic predisposition. Therefore, large-scale germline genomic variant studies are urgently needed. Recently, our group has published the largest-scale pan-cancer study of >10K adult and >1K pediatric cases that revealed new insights on germline predisposition variants across 33 cancer types (853 pathogenic or likely pathogenic variants) (Huang et al., 2018). Here, we aim to apply a similar strategy to MM cases. The CoMMpass study, promoted by MMRF (Multiple Myeloma Research Foundation) is a longitudinal, prospective observational study involving the collection and analysis of sequencing and clinical data from >1K MM patients at diagnosis and relapse. We performed germline variant calling on 808 normal samples from this dataset using GenomeVIP (https://github.com/ding-lab/GenomeVIP), which integrates multiple tools: VarScan2 and Genome Analysis ToolKit (GATK) for the identification of single nucleotide variants (SNVs) and indels; and Pindel for indel prediction. Variants were limited to coding regions of full length transcripts obtained from Ensembl release 70 plus the additional two base pairs flanking each exon that cover splice donor/acceptor sites. SNVs were based on the union of raw GATK and VarScan calls. Indels were required to be called by at least two out of the three callers (GATK, Pindel, VarScan). Variant calls from all tools were merged, filtered (allelic depth ≥ 5 for the alternative allele; rare variants with allele frequency ≤ 0.01 in 1000 Genomes and ExAC), and annotated using Variant Effect Predictor (VEP), resulting in an average of 1,653 variants per sample. Further, we applied CharGer (Characterization of Germline Variants, https://github.com/ding-lab/CharGer) to classify the identified germline variants as pathogenic, likely pathogenic, and prioritized variants of unknown significance (VUS). CharGer is an automatic variant classification pipeline developed by our group which adopts ACMG-AMP guidelines specifically for rare variants in cancer. Here, we were able to classify a total of 635 germline variants as pathogenic and 150 as likely pathogenic, affecting 90% of samples. Among pathogenic variants, 28 were found in known cancer predisposition genes including BRCA1 and BRCA2 - which have been previously associated with MM risk - BRIP1, CHEK2, TP53, TERT, and PMS2. Ongoing analyses include: functional characterization of these variants, identifying genes with enriched pathogenic or likely pathogenic variants in our dataset; investigation of LOH and two-hit (biallelic) events; gene and protein expression analyses in carriers of pathogenic germline variants of the respective gene; scanning for rare, germline copy number variations (CNVs); and identification of variants in post-translational modification sites that may affect protein signaling. Additionally, we are currently working on improving our CharGer tool by integrating new tumor associated data, such as DNA-Seq, RNA-Seq, Methyl-Seq and MS proteomics data, to improve variant classification. The preliminary results and analysis strategies described here will allow for efficient and cost-effective discovery of genetic changes relevant to MM etiology. Ultimately, we hope this work will impact our overall understanding of the genetics underlying MM predisposition, allowing for the development of better prevention and early detection strategies. Disclosures Vij: Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jansson: Honoraria, Membership on an entity's Board of Directors or advisory committees.
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Zabotti, A., A. Gabrielli, C. Selmi, R. D. Grembiale, R. Ramonda, L. Dagna, S. D’angelo, et al. "AB0680 BASELINE CHARACTERISTICS OF PATIENTS ENROLLED IN THE ONGOING SIRENA STUDY, A NATIONAL PROSPECTIVE OBSERVATIONAL REGISTRY IN SPONDYLOARTHRITIS SUBJECTS." Annals of the Rheumatic Diseases 79, Suppl 1 (June 2020): 1635–36. http://dx.doi.org/10.1136/annrheumdis-2020-eular.2876.
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Background:There is a paucity of epidemiological data in Early Arthritis. SIRENA is an Italian prospective observational study in SpA patients, naïve to conventional, targeted and biological DMARDs.Objectives:To present the baseline data, including demographic characteristics and patterns of clinical presentation, for the population enrolled between June 2017-February 2019.Methods:At the study entry, patients are diagnosed, newly or confirmed, according to ASAS criteria and classified in subjects with predominant axial (AX) or with mainly peripheral (PER) manifestations. Diagnostic delay, subtypes of SpA are evaluated as well as clinical features (i.e. presence of dactylitis, enthesitis, involvement of skin/nails/other organs).Results:In 23 italian sites, 282 patients were enrolled. Baseline data are shown in Table 1. 18% of the patients were obese (maximum BMI=39.7), 22% overweight. Diagnostic delay was registered for 58.1% patients with a mean delay of 57.1 months. Main reasons of the delay were incorrect referrals (44%) and previous misdiagnosis (27%). The most frequent type of SpA was psoriatic arthritis (54.3%), followed by ankylosing spondylitis (18.5%), undifferentiated SpA (11.5%), non-radiographic axial SpA (8.2%), and enteropathic SpA (7.5%). The majority of patients reported as first symptom peripheral arthritis and inflammatory back pain, followed by enthesitis. The most frequently reported comorbidities were psoriasis (50.4%) and cardiometabolic and gastrointestinal diseases (30.1% and 15.7%,respectively) - Table 2. To the 154 psoriatic arthritis (PsA) patients, CASPAR classification criteria were also applied, with a performance of 95% and a mean score of 3.64.Conclusion:SIRENA is the first Italian Disease Registry for SpA patients. The above results are in line with the few evidences found in literature (1), confirming the representativeness of our sample. In case of PsA, our results confirm that the accordance between ASAS and CASPAR criteria is very high.References:[1]Tayel et al. Rheumatol Int 2012; 32:2837-42.Table 1.Patient Characteristics (baseline)MeanN=282Age50.8 yearsSex (%)49 F/51 MWeight73.7 KgBMI25.3Smoking Status (never/ongoing/past - %)56.8/22/21.2Alcohol consumption (not/occasional/usual drinker - %)50.0/44.9/5.1SpA type (%)35.8 AX/64.2 PERDiagnostic Delay (yes - %)58.1Months of diagnostic delay (mean)57.1 monthsNewly diagnosis (%)68.4Table 2.A) First SymptomNumber of PatientsN=282, more than 1 symptom referredArthritis145Enthesitis70Dactylitis35Inflammatory Back Pain114Psoriasis skin67Psoriasis nails21Uveitis5IBD16B) ComorbiditiesPercentage of PatientsN=282, more than 1 comorbidity referredCardiometabolic30.1% - Hypertension27.0% - Dyslipidemia13.8% - Diabetes7.1% - MetS6.0% - CHD3.2%Psoriasis50.4%Gastrointestinal15.7% (5.3% Crohn’s disease)Endocrine9.6%Depression/Anxiety5.7%Osteoporosis4.6%Hepatic4.3% (2.5% NAFLD)Infections3.9%Malignancies2.8%Kidney1.8%Acknowledgments:This study was sponsored by Janssen Italy.We thank the Investigators and their staff at all of the study sites.Disclosure of Interests:Alen Zabotti Speakers bureau: Celgene, Novartis, Janssen, Armando Gabrielli Grant/research support from: Pfizer, Speakers bureau: Pfizer, Actelion, Carlo Selmi Grant/research support from: AbbVie, Janssen, MSD, Novartis, Pfizer, Celgene, and Leo Pharma, Consultant of: Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and Sanofi-Regeneron, Speakers bureau: AbbVie, Aesku, Alfa-Wassermann, Bristol-Myers Squibb, Biogen, Celgene, Eli-Lilly, Grifols, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi-Genzyme, UCB Pharma, Rosa Daniela Grembiale: None declared, Roberta Ramonda Speakers bureau: Novartis, Celgene, Janssen, Pfizer, Abbvie, Lilly, Lorenzo Dagna Grant/research support from: Abbvie, BMS, Celgene, Janssen, MSD, Mundipharma Pharmaceuticals, Novartis, Pfizer, Roche, SG, SOBI, Consultant of: Abbvie, Amgen, Biogen, BMS, Celltrion, Novartis, Pfizer, Roche, SG, and SOBI, Salvatore D’Angelo Speakers bureau: AbbVie, Biogen, BMS, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Sanofi, and UCB, Roberto Gerli: None declared, Salvatore De Vita Consultant of: Roche, Human Genome Science, Glaxo Smith Kline and Novartis, Silvia Marelli Employee of: Janssen, Daniela Frigerio Employee of: Janssen, Ennio Favalli Speakers bureau: BMS, Eli-Lilly, MSD, UCB, Pfizer, Sanofi-Genzyme, Novartis and Abbvie
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Alig, Stefan, Charles Macaulay, David M. Kurtz, Ulrich Dührsen, Andreas Hüttmann, Michael C. Jin, Brian Sworder, et al. "Short Diagnosis-to-Treatment Interval Is Associated with Higher Levels of Circulating Tumor DNA in Aggressive B-Cell Non-Hodgkin Lymphoma." Blood 134, Supplement_1 (November 13, 2019): 491. http://dx.doi.org/10.1182/blood-2019-129283.
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BACKGROUND Selection biases can impair the generalizability of clinical trials. Studies investigating aggressive diseases such as Diffuse Large B-cell Lymphoma (DLBCL) can be particularly affected by such biases since clinical urgency and need for therapy may not allow the requisite extensive screening and consent processes for trials. Diagnosis-to-Treatment Interval (DTI) has recently been proposed as a novel metric to capture this phenomenon (Maurer et al, JCO, 2018), and short DTI is associated with both adverse clinical factors and adverse clinical outcomes. Intriguingly, DTI was independent of clinical risk factors like the International Prognostic Index (IPI) suggesting that widely applied prognostic scores do not adequately reflect risk factors considered for clinical decision making. In this study, we aim to assess whether pretreatment levels of circulating tumor DNA (ctDNA) are associated with shorter DTI and may constitute an objective measure of clinical urgency. METHODS We quantified pretreatment ctDNA levels in plasma samples from 178 patients treated in 5 US and European centers for large cell lymphoma (DLBCL, Follicular lymphoma grade 3b, or High-grade-B-cell-lymphoma) using Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) as previously described (Kurtz, JCO 2018; Scherer, STM 2016). Pretreatment ctDNA levels were correlated with DTI, clinical factors and treatment outcome. RESULTS Pretreatment ctDNA was detectable in 175/178 cases. Median number of single nucleotide variants (SNV) detected per patient was 129 (range 0-628). Pretreatment ctDNA levels ranged from 0 - 1.4 x105 haploid genome equivalents per milliliter of plasma (hGE/ml, median 239). Median DTI was 19 days (range 0-141, Figure 1A) and was similar in distribution to 2 previously described cohorts from the US and Europe (Maurer et al, JCO 2018). Shorter DTI was associated with higher ctDNA levels (RS=-0.39, P= 1.4 x10-7, Figure 1B). Patients with longer DTI had improved Event-Free Survival (EFS, Hazard Ratio (HR) for DTI: 0.9/week, P= 0.03). However, this association was lost when adjusting for pretreatment ctDNA levels (HR for DTI: 0.95/week, P= 0.39; HR for log10(ctDNA): 1.7, P= 5.8 x10-5). In a multivariate analysis including DTI, ctDNA and IPI, only ctDNA levels were significantly associated with EFS (HR for log10(ctDNA): 1.6, P= 0.002, n=178, Figure 1C). Pretreatment ctDNA levels remained the only prognostic factor for EFS in a second multivariate analysis also considering pretreatment metabolic tumor volume (MTV, HR for log10(ctDNA): 1.8, P= 0.01, n=93, Figure 1D). DISCUSSION Shorter DTI is associated with higher pretreatment ctDNA levels in patients with aggressive B-cell lymphomas. When comparing to established factors (DTI, IPI, MTV), pretreatment ctDNA levels appear to best predict clinical outcomes. This suggests that quantification of ctDNA better reflects disease burden and treatment urgency than existing clinical biomarkers. Pretreatment ctDNA level may therefore be a valuable metric for disease aggressiveness of patients included in clinical trials, and may help identify studies suffering from selection bias. This may be particularly useful for noncontrolled Phase I/II single arm trials, but also for stratification in randomized trials. Disclosures Kurtz: Roche: Consultancy. Dührsen:Alexion: Honoraria; Novartis: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Janssen: Honoraria; Takeda: Consultancy, Honoraria; Celgene: Research Funding; CPT: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Teva: Honoraria; Roche: Honoraria, Research Funding. Hüttmann:Takeda: Honoraria; Gilead: Honoraria; University Hospital Essen: Employment. Westin:Juno: Other: Advisory Board; Novartis: Other: Advisory Board, Research Funding; Janssen: Other: Advisory Board, Research Funding; Kite: Other: Advisory Board, Research Funding; Curis: Other: Advisory Board, Research Funding; Celgene: Other: Advisory Board, Research Funding; 47 Inc: Research Funding; Unum: Research Funding; MorphoSys: Other: Advisory Board; Genentech: Other: Advisory Board, Research Funding. Gaidano:AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Astra-Zeneca: Consultancy, Honoraria; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sunesys: Consultancy, Honoraria. Rossi:Abbvie: Honoraria, Other: Scientific advisory board; Janseen: Honoraria, Other: Scientific advisory board; Roche: Honoraria, Other: Scientific advisory board; Astra Zeneca: Honoraria, Other: Scientific advisory board; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Diehn:Novartis: Consultancy; BioNTech: Consultancy; AstraZeneca: Consultancy; Quanticell: Consultancy; Roche: Consultancy. Alizadeh:Pfizer: Research Funding; Chugai: Consultancy; Celgene: Consultancy; Gilead: Consultancy; Pharmacyclics: Consultancy; Janssen: Consultancy; Genentech: Consultancy; Roche: Consultancy.
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Mamoto, K., T. Koike, Y. Yamada, T. Okano, Y. Sugioka, M. Tada, K. Inui, and H. Nakamura. "POS0466 RHEUMATOID ARTHRITIS PER SE IS NOT RISK FACTOR FOR CLINICAL FRACTURES: NINE-YEAR FINDINGS OF THE TOMORROW STUDY." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 465.1–465. http://dx.doi.org/10.1136/annrheumdis-2021-eular.2331.
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Background:Patients with rheumatoid arthritis (RA) who have sarcopenia and stiff or painful joints might be at increased risk of falls and fractures.Objectives:The present study aimed to prospectively identify the incidence of clinical fractures and associated risk factors in patients with RA in a cohort study named the TOMORROW (UMIN000003876) that started in 2010.Methods:We evaluated anthropometric parameters, bone mineral density (BMD), disease activity, RA medication at baseline and observed the incidence of clinical fractures during nine years in 202 patients with RA (mean age, 58.6 y; medication with biological agents, 54.9%) and 202 age- and sex-matched non-RA volunteers (mean age, 57.4 y). We compared the incidence of clinical fractures between patients with RA and controls for nine years, and analyzed the risk factors for fractures using Cox proportional hazard model.Results:The incidence of clinical fractures in RA patients was significantly higher compared to controls (27.5 vs 18.3%, p=0.04). However, Cox proportional hazard model, adjusted by age, sex, smoking and body mass index, revealed that low BMD at thoracic vertebrae (< 0.7 g/cm2) significantly associated to the incidence of clinical fractures (hazard ratio [HR], 1.86, p=0.02), but not RA morbidity (HR 1.47, p=0.10) (Table 1). Among patients with RA, low BMD at the thoracic vertebrae (< 0.7 g/cm2) was the most prominent risk factor for clinical fractures (HR, 2.66, p=0.02) (Table 1). Although the use of glucocorticoid (GC) at baseline (HR, 1.68, p=0.09) was not a significant risk factor for fractures, a mean GC dose (≥ 2 mg/day) at entry increased risk for clinical fractures in the patients (HR, 1.91, p=0.04) (Table 1).Conclusion:RA per se was not a risk factor for clinical fractures in this cohort. Low BMD at the thoracic vertebrae and the use of GC with even low dose at entry were apparently significant risk factors for the incidence of clinical fractures among patients with RA.Disclosure of Interests:Kenji Mamoto: None declared, Tatsuya Koike Grant/research support from: Takeda Pharmaceutical, Mitsubishi Tanabe Pharma Corporation,Chugai Pharmaceutical, Eisai, Abbott Japan, Teijin Pharma, Banyu Pharmaceutical and Ono Pharmaceutical, Yutaro Yamada: None declared, Tadashi Okano: None declared, Yuko Sugioka: None declared, Masahiro Tada: None declared, Kentaro Inui Speakers bureau: Daiichi Sankyo Co. Ltd., Mitsubishi Tanabe Pharma, Janssen Pharmaceutical K.K., Astellas Pharma Inc., Takeda Pharmaceutical Co. Ltd., Ono Pharmaceutical Co. Ltd., Abbvie GK, Pfizer Inc., Eisai Co.,Ltd., Chugai Pharmaceutical Co., Ltd., Grant/research support from: Janssen Pharmaceutical K.K., Astellas Pharma Inc., Sanofi K.K., Abbvie GK, Takeda Pharmaceutical Co. Ltd., QOL RD Co. Ltd., Mitsubishi Tanabe Pharma, Ono Pharmaceutical Co. Ltd., Eisai Co.,Ltd., Hiroaki Nakamura: None declared
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Martina, Piero Andrea. "“Fleur de clergie”. Mélanges en l’honneur de Jean-Yves Tilliette, édités par O. Collet, Y. Foehr-Janssens." Studi Francesi, no. 192 (LXIV | III) (December 1, 2020): 632–34. http://dx.doi.org/10.4000/studifrancesi.41908.
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Dimopoulos, Meletios A., Hang Quach, María-Victoria Mateos, Ola Landgren, Xavier Leleu, David S. Siegel, Katja Weisel, et al. "Carfilzomib, Dexamethasone, and Daratumumab Versus Carfilzomib and Dexamethasone in Relapsed or Refractory Multiple Myeloma: Updated Efficacy and Safety Results of the Phase 3 Candor Study." Blood 136, Supplement 1 (November 5, 2020): 26–27. http://dx.doi.org/10.1182/blood-2020-137602.
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Introduction: The randomized, open-label, multicenter, phase 3 CANDOR study compared carfilzomib, dexamethasone, and daratumumab (KdD) to carfilzomib and dexamethasone (Kd) in patients with multiple myeloma who have relapsed after 1-3 prior lines of therapy (ClinicalTrials.gov, NCT03158688). In the previously reported primary analysis (Dimopoulos et al, Lancet 2020), a significant progression-free survival (PFS) benefit was demonstrated in patients treated with KdD vs patients treated with Kd (hazard ratio [HR], 0.63 [95% CI, 0.46-0.85]; two-sided P=0.0027). However, after a median follow-up of 16.9 months, median PFS was not reached in the KdD arm. Here, we report updated efficacy and safety outcomes from the CANDOR study. Methods: Adult patients with relapsed or refractory multiple myeloma (RRMM) received 28-day cycles of KdD or Kd (randomized 2:1). In the primary analysis, PFS was the primary endpoint and overall survival (OS) a key secondary endpoint. In this prespecified interim OS analysis, statistical testing was based on the actual number of OS events observed by the data cutoff (approximately 36 months after enrollment of the first patient); PFS was summarized descriptively. Disease progression was determined locally by investigators in an unblinded manner and centrally by the sponsor using a validated computer algorithm (Onyx Response Computer Algorithm [ORCA]) in a blinded manner. PFS and OS were compared between the KdD and Kd arms using a stratified log-rank test, and HRs were estimated by a stratified Cox proportional-hazards model. Results: Patients were randomized to KdD (n = 312) and Kd (n = 154). Of all randomized patients, median age was approximately 64 years; 42% received previous lenalidomide, and 33% were lenalidomide refractory; 90% received previous bortezomib, and 29% were bortezomib refractory. At the data cutoff date of June 15, 2020, 199 (63.8%) patients in the KdD arm and 88 (57.1%) in the Kd arm remained on study. Among patients treated with KdD and Kd, 140 (44.9%) and 85 (55.2%) had PFS events, respectively; median follow-up was 27.8 months (KdD) and 27.0 months (Kd). Median PFS by ORCA was 28.6 months for the KdD arm versus 15.2 months for the Kd arm (HR, 0.59 [95% CI, 0.45-0.78]; Figure). OS data were not mature and will be updated at a future prespecified analysis. Median treatment duration was 79.3 weeks with KdD versus 40.3 weeks with Kd. Grade ≥3 adverse events (AEs) occurred in 87.0% and 75.8% of patients in the KdD and Kd arms, respectively, and fatal AEs occurred in 8.8% and 4.6%; one fatal AE in the KdD arm (due to arrhythmia) and one fatal AE in the Kd arm (due to COVID-19 pneumonia) had occurred since the primary analysis. Carfilzomib treatment discontinuation rates due to AEs were 26.0% with KdD and 22.2% with Kd. Exposure-adjusted AE rates per 100 patient years were: 171.2 and 151.9 for grade ≥3 AEs and 6.9 and 5.6 for fatal AEs in the KdD and Kd arms, respectively. Updated data by key subgroups will be presented. Conclusion: With approximately 11 months of additional follow-up, a 13.4-month improvement in median PFS was observed in patients treated with KdD (28.6 months) versus patients treated with Kd (15.2 months; HR, 0.59 [95% CI, 0.45-0.78]). Safety was consistent with previously reported results. KdD continues to show a favorable benefit-risk profile and represents an efficacious treatment option for patients with RRMM. Figure 1 Disclosures Dimopoulos: Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Research Funding, Speakers Bureau; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Speakers Bureau. Quach:GlaxoSmithKline, Karyopharm, Amgen, Celgene, Janssen Cilag: Consultancy; Amgen, Celgene, karyopharm, GSK, Janssen Cilag, Sanofi.: Membership on an entity's Board of Directors or advisory committees; Amgen, sanofi, celgene, Karyopharm, GSK: Research Funding; GlaxoSmithKline, Karyopharm, Amgen, Celgene, Janssen Cilag: Honoraria. Mateos:EDOMundipharma: Consultancy; Adaptive: Consultancy; Pharmamar: Consultancy; GlaxoSmithKline: Consultancy; AbbVie: Consultancy; Takeda: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Janssen: Consultancy. Landgren:Pfizer: Consultancy, Honoraria; Merck: Other; Cellectis: Consultancy, Honoraria; Juno: Consultancy, Honoraria; Glenmark: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria; Binding Site: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Karyopharma: Research Funding; Merck: Other; Janssen: Consultancy, Honoraria, Other: Independent Data Monitoring Committees for clinical trials, Research Funding; Takeda: Other: Independent Data Monitoring Committees for clinical trials, Research Funding; Glenmark: Consultancy, Honoraria, Research Funding; Juno: Consultancy, Honoraria; Seattle Genetics: Research Funding; Cellectis: Consultancy, Honoraria; Seattle Genetics: Research Funding; Takeda: Other: Independent Data Monitoring Committees for clinical trials, Research Funding; BMS: Consultancy, Honoraria; Adaptive: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Binding Site: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Other: Independent Data Monitoring Committees for clinical trials, Research Funding; Karyopharma: Research Funding. Leleu:Incyte: Honoraria; Merck: Honoraria; Novartis: Honoraria; Amgen: Honoraria; GSK: Honoraria; Sanofi: Honoraria; BMS-celgene: Honoraria; Janssen: Honoraria; Oncopeptide: Honoraria; AbbVie: Honoraria; Carsgen: Honoraria; Karyopharm: Honoraria. Siegel:Janssen: Consultancy, Honoraria, Speakers Bureau; Merck: Consultancy, Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria, Speakers Bureau; Celulatiry: Consultancy; Karyopharma: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau. Weisel:Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria; Adaptive: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; GlaxoSmithKline: Honoraria; Sanofi: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria; Roche: Consultancy, Honoraria. Gavriatopoulou:Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Genesis Pharma: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Oriol:Janssen: Consultancy; Celgene: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau. Rabin:Janssen, BMS/Celgene, Takeda, Karyopharm, Amgen: Consultancy; Janssen, BMS/Celgene, Takeda: Other: Travel; Jansse, BMS/Celgene, Takeda: Speakers Bureau. Nooka:GlaxoSmithKline: Consultancy, Honoraria, Other: Personal Fees: Travel/accomodations/expenses, Research Funding; Karyopharm Therapeutics, Adaptive technologies: Consultancy, Honoraria, Research Funding; Spectrum Pharmaceuticals: Consultancy; Celgene: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Oncopeptides: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria; Adaptive Technologies: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding. Ding:Amgen: Current Employment. Zahlten-Kumeli:Amgen: Current Employment, Current equity holder in publicly-traded company. Usmani:Celgene: Other; GSK: Consultancy, Research Funding; Pharmacyclics: Research Funding; Array Biopharma: Research Funding; Seattle Genetics: Consultancy, Research Funding; Merck: Consultancy, Research Funding; Incyte: Research Funding; SkylineDX: Consultancy, Research Funding; Takeda: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Sanofi: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy; BMS, Celgene: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Amgen: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Janssen: Consultancy, Honoraria, Other: Speaking Fees, Research Funding.
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Kaufman, Jonathan L., Jacob P. Laubach, Douglas Sborov, Brandi Reeves, Cesar Rodriguez, Ajai Chari, Rebecca W. Silbermann, et al. "Daratumumab (DARA) Plus Lenalidomide, Bortezomib, and Dexamethasone (RVd) in Patients with Transplant-Eligible Newly Diagnosed Multiple Myeloma (NDMM): Updated Analysis of Griffin after 12 Months of Maintenance Therapy." Blood 136, Supplement 1 (November 5, 2020): 45–46. http://dx.doi.org/10.1182/blood-2020-137109.
Full textAbstract:
Introduction: DARA, a human IgGκ monoclonal antibody targeting CD38, is approved as monotherapy and in combination with standard-of-care regimens for relapsed/refractory multiple myeloma and NDMM. In the primary analysis of the phase 2 GRIFFIN study (NCT02874742) in patients with transplant-eligible NDMM, DARA plus RVd (D-RVd) significantly improved rates of stringent complete response (sCR) by the end of post-transplant consolidation therapy versus RVd (Voorhees P, Blood 2020). Here, we present updated efficacy and safety results following 12 months of maintenance therapy with lenalidomide (R) or DARA plus R (D-R). Methods: Patients with NDMM eligible for high-dose therapy (HDT) and autologous stem cell transplant (ASCT) were randomized 1:1 to RVd ± DARA, stratified by ISS stage and creatinine clearance rate. Patients received 4 induction cycles, HDT, ASCT, 2 consolidation cycles, and maintenance with R ± DARA for 24 months. During induction and consolidation, patients received R 25 mg PO on Days 1-14; V 1.3 mg/m2 SC on Days 1, 4, 8, and 11; and d 40 mg QW every 21 days. DARA 16 mg/kg IV was given on Days 1, 8, and 15 of Cycles 1-4 and Day 1 of Cycles 5-6. During maintenance (Cycles 7-32), patients received R 10 mg (15 mg in Cycles 10+ if tolerated) on Days 1-21 every 28 days ± DARA 16 mg/kg IV Q8W (or Q4W per patient decision after Amendment 2). The primary endpoint was rate of sCR at the end of post-ASCT consolidation per IMWG criteria, evaluated by a validated computer algorithm. Key secondary endpoints included progression-free survival (PFS) and rate of minimal residual disease (MRD) negativity (10-5 threshold per IMWG criteria) assessed by next-generation sequencing (clonoSEQ; Adaptive Biotechnologies). The primary hypothesis was tested at a 1-sided alpha of 0.10. All secondary analyses were evaluated using a 2-sided P value (alpha 0.05) and were not adjusted for multiplicity. Results: In total, 207 patients were randomized (D-RVd, n=104; RVd, n=103). Baseline demographics and disease characteristics were well balanced between arms. At the end of post-transplant consolidation (median follow-up, 13.5 months) in the response-evaluable population, the sCR rate favored D-RVd versus RVd (42.4% [42/99] vs 32.0% [31/97]; 1-sided P=0.0680). With additional D-R or R maintenance therapy, responses continued to deepen and remained higher for the D-RVd group versus the RVd group. At the 12-months-of-maintenance therapy data cut (median follow-up, 26.7 months), the sCR rate still favored D-RVd versus RVd (63.6% [63/99] vs 47.4% [46/97], 2-sided P=0.0253; Figure). MRD-negativity (10‒5) rates in the ITT population favored D-RVd versus RVd (62.5% [65/104] vs 27.2% [28/103], P<0.0001; Figure), as well as among patients who achieved complete response (CR) or better at that time (76.5% [62/81] vs 42.4% [25/59], P<0.0001). Similarly, MRD-negativity (10‒6) rates favored D-RVd versus RVd in the ITT population (26.9% [28/104] vs 12.6% [13/103], P=0.0140; Figure), as well as among patients who achieved CR or better at that time (34.6% [28/81] vs 18.6% [11/59], P=0.0555). Estimated 24-month PFS rates were 94.5% and 90.8% for the D-RVd and RVd groups, respectively. In total, 14 deaths occurred (n=7 per group), and 9 were due to progressive disease (D-RVd, n=5; RVd, n=4). With longer follow-up, no new safety concerns were observed. 84.8% (84/99) of patients in the D-RVd group and 79.4% (81/102) in the RVd group had grade 3/4 treatment-emergent adverse events (TEAEs). One grade 5 TEAE occurred in the RVd group, which was unrelated to study therapy (unknown cause). Infusion-related reactions occurred in 43.4% (43/99) of patients, with the majority being grade 1 or 2 and occurring in the first cycle. Conclusions: After 26.7 months of median follow-up, the addition of DARA to RVd induction and consolidation, followed by D-R maintenance in patients with transplant-eligible NDMM continued to demonstrate deep and improved responses, including higher sCR and MRD negativity rates, compared with lenalidomide alone. Maintenance therapy increased sCR and MRD negativity rates, compared to post-consolidation rates. No new safety concerns were observed with longer follow-up. Support: Alliance Foundation Trials; https://acknowledgments.alliancefound.org; Janssen Oncology Disclosures Kaufman: Tecnopharma: Consultancy, Honoraria; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria; Sanofi/Genyzme: Consultancy, Honoraria; AbbVie: Consultancy; Amgen: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees. Sborov:University of Utah: Current Employment; Celgene, Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees. Reeves:Incyte: Honoraria; Takeda: Honoraria; Bristol Myers Squibb: Speakers Bureau. Rodriguez:BMS, Takeda, Amgen: Consultancy, Speakers Bureau. Chari:Janssen, Celgene, Novartis, Amgen, Bristol-Myers Squibb, Karyopharm, Sanofi, Genzyme, Seattle Genetics, Oncopeptides, Millennium/Takeda, Antengene, Glaxo Smith Kline, Secura Bio: Consultancy; Janssen, Celgene, Novartis, Amgen, Pharmacyclics, Seattle Genetics, Millennium/Takeda: Research Funding. Silbermann:Karyopharm: Consultancy; Janssen: Consultancy; Sanofi-Aventis: Consultancy, Research Funding. Costa:AbbVie: Consultancy; Sanofi: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Genentech: Consultancy; BMS: Consultancy, Honoraria. Anderson:Amgen: Consultancy, Honoraria, Research Funding; GSK: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding. Shah:GSK, Amgen, Indapta Therapeutics, Sanofi, BMS, CareDx, Kite, Karyopharm: Consultancy; BMS, Janssen, Bluebird Bio, Sutro Biopharma, Teneobio, Poseida, Nektar: Research Funding. Efebera:Pharmacyclics: Research Funding; Ohio State University: Current Employment; Celgene: Research Funding; Takeda: Honoraria, Speakers Bureau. Holstein:Sorrento: Consultancy; Adaptive Biotechnologies: Consultancy; Takeda: Consultancy; GSK: Consultancy; Celgene: Consultancy; Genentech: Consultancy; Sanofi: Consultancy; Oncopeptides: Consultancy, Research Funding. Costello:Takeda, Celgene: Consultancy, Honoraria. Jakubowiak:Adaptive, Juno: Consultancy, Honoraria; AbbVie, Amgen, BMS/Celgene, GSK, Janssen, Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Wildes:Seattle Genetics: Consultancy; Carevive Systems: Consultancy; Janssen: Research Funding. Orlowski:Founder of Asylia Therapeutics, Inc., with associated patents and an equity interest, though this technology does not bear on the current submission.: Current equity holder in private company, Patents & Royalties; STATinMED Research: Consultancy; Sanofi-Aventis, Servier, Takeda Pharmaceuticals North America, Inc.: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen, Inc., AstraZeneca, BMS, Celgene, EcoR1 Capital LLC, Forma Therapeutics, Genzyme, GSK Biologicals, Ionis Pharmaceuticals, Inc., Janssen Biotech, Juno Therapeutics, Kite Pharma, Legend Biotech USA, Molecular Partners, Regeneron Pharmaceuticals, Inc.,: Honoraria, Membership on an entity's Board of Directors or advisory committees; Laboratory research funding from BioTheryX, and clinical research funding from CARsgen Therapeutics, Celgene, Exelixis, Janssen Biotech, Sanofi-Aventis, Takeda Pharmaceuticals North America, Inc.: Research Funding. Shain:BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; AbbVie: Research Funding; GlaxoSmithKline: Speakers Bureau; Adaptive: Consultancy, Honoraria; Sanofi/Genzyme: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Honoraria, Speakers Bureau; Karyopharm: Research Funding, Speakers Bureau; Amgen: Speakers Bureau. Cowan:Nektar: Research Funding; Janssen: Consultancy, Research Funding; Abbvie: Research Funding; Bristol-Myer Squibb: Research Funding; Celgene: Consultancy, Research Funding; Cellectar: Consultancy; Sanofi-Aventis: Consultancy. Lutska:Janssen: Current Employment. Bobba:Janssen: Current Employment. Pei:Janssen: Current Employment, Current equity holder in publicly-traded company. Ukropec:Janssen: Current Employment, Current equity holder in publicly-traded company. Vermeulen:Janssen: Current Employment, Current equity holder in publicly-traded company. Lin:Janssen Scientific Affairs: Current Employment, Current equity holder in publicly-traded company. Richardson:Celgene/BMS, Oncopeptides, Takeda, Karyopharm: Research Funding. Voorhees:TeneoBio: Other: Advisory Board; Oncopeptides: Consultancy, Honoraria; Novartis: Consultancy; Janssen: Other: Advisory Board; GSK: Honoraria; BMS: Other: Advisory Board; Adaptive Biotechnologies: Other: Advisory Board. OffLabel Disclosure: The specific regimen combination is not yet approved, but individual components are.
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Deodhar, A., I. Mcinnes, X. Baraliakos, K. Reich, A. B. Gottlieb, M. Lebwohl, S. Schreiber, et al. "FRI0272 SECUKINUMAB DEMONSTRATES A CONSISTENT SAFETY PROFILE IN PATIENTS WITH PSORIASIS, PSORIATIC ARTHRITIS AND ANKYLOSING SPONDYLITIS OVER LONG TERM: UPDATED POOLED SAFETY ANALYSES." Annals of the Rheumatic Diseases 79, Suppl 1 (June 2020): 722.2–722. http://dx.doi.org/10.1136/annrheumdis-2020-eular.5118.
Full textAbstract:
Background:Pooled safety data has been reported with secukinumab (SEC) in patients (pts) with Psoriatic arthritis (PsA), Ankylosing Spondylitis (AS) and Psoriasis (PsO).1Objectives:To report longer-term safety data of SEC treatment in PsA, AS, PsO pts up to 5 years.Methods:The integrated clinical trial safety dataset included data pooled from 28 randomised controlled clinical trials of SEC 300 or 150 or 75 mg in PsO (11 Phase 3 and 8 Phase 4 trials), PsA (5 Phase 3 trials), and AS (4 Phase 3 trials), along with post-marketing safety surveillance data with a cut-off date of 25 December 2018. Adverse events (AEs) were reported as exposure-adjusted incident rates (EAIRs) per 100 pt-years. Analyses included all pts who received ≥1 dose of SEC.Results:A total of 12637 pts (8819, 2678 and 1140 pts with PsO, PsA and AS, with an exposure of 15063.1, 5984.6 and 3527.2 pt-years, respectively) were included. The most frequent AE was upper respiratory tract infection and EAIR per 100 pt-years for IBD, malignancies and MACE remained low. The EAIR per 100 pt-years for adverse events (AEs) of special interest are reported in Table 1. The cumulative post-marketing exposure to SEC was estimated to be ~285,811 pt-years across the approved indications. Safety data from post-marketing surveillance are reported in Table 2.Table 1.Selected AEs of interest with SEC across pooled clinical trialsVariablePsOPsAASSECN=8819SECN=2678SECN=1140Exposure (Days), Mean (SD)623.9 (567.7)816.2 (580.7)1130.1 (583.0)Death, n (%)15 (0.2)13 (0.5)10 (0.9)Selected AE’s of interest, EAIR (95% CI)Serious infections11.4 (1.2, 1.6)1.8 (1.5, 2.2)1.2 (0.9, 1.6)Candidainfections22.9 (2.7, 3.2)1.5 (1.2, 1.9)0.7 (0.5, 1.1)IBD3Crohn’s disease3Ulcerative colitis30.01 (0.0, 0.05)0.1 (0.05, 0.2)0.1 (0.08, 0.2)0.03 (0.0, 0.1)0.1 (0.04, 0.2)0.1 (0.04, 0.2)0.03 (0.0, 0.2)0.4 (0.24, 0.7)0.2 (0.1, 0.5)MACE40.4 (0.31, 0.5)0.4 (0.3, 0.6)0.7 (0.4, 1.0)Uveitis30.01 (0.0, 0.05)0.1 (0.04, 0.2)1.2 (0.9, 1.7)Malignancy50.9 (0.7, 1.0)1.0 (0.77, 1.3)0.5 (0.3, 0.8)1Rates for system organ class;2Rates for high level term;3Rates for preferred term (PT; IBD for unspecified IBD);4Rates for Novartis MedDRA Query term;5Rates for standardized MedDRA query term – ‘malignancies and unspecified tumour’; EAIR, exposure adjusted incidence rate per 100 pt-years; N, number of pts in the analysisTable 2.Summary of SEC post-marketing safetyExposure (PTY)PSUR126Dec14 -25Jun15PSUR226 Jun - 25Dec15PSUR326Dec15 -25Jun16PSUR426Jun -25Dec16PSUR526Dec16 -25Dec17PSUR626Dec17 -25Dec18Cumulative18387450168712854993744137325285811 n (Reporting rate PTY)Serious infections89 (4.8)149 (2.0)232 (1.4)475 (1.7)649 (0.7)1841 (1.3)3980 (1.4)Malignancy2 (0.1)15 (0.2)21 (0.1)50 (0.2)225 (0.2)422 (0.3)788 (0.3)Total IBD4 (0.2)12 (0.2)37(0.2)46 (0.2)185 (0.2)340 (0.3)693 (0.2)MACE6 (0.3)15 (0.2)16 (0.1)39 (0.1)151 (0.2)238 (0.2)504 (0.2)PSUR, periodic safety update report; PTY, pt-treatment yearsConclusion:In this long-term analysis across clinical trials and post-marketing surveillance, of pts with PsO, PsA and AS, SEC was well tolerated, with a safety profile consistent with previous reports.1Reference:[1]Deodhar et al. Arthritis Research & Therapy (2019) 21:111.Disclosure of Interests:Atul Deodhar Grant/research support from: AbbVie, Eli Lilly, GSK, Novartis, Pfizer, UCB, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myer Squibb (BMS), Eli Lilly, GSK, Janssen, Novartis, Pfizer, UCB, Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myer Squibb (BMS), Eli Lilly, GSK, Janssen, Novartis, Pfizer, UCB, Iain McInnes Grant/research support from: Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, and UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Gilead, Janssen, Novartis, Pfizer, and UCB, Xenofon Baraliakos Grant/research support from: Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Consultant of: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Kristian Reich Grant/research support from: Affibody; Almirall; Amgen; Biogen; Boehringer Ingelheim; Celgene; Centocor; Covagen; Eli Lilly; Forward Pharma; Fresenius Medical Care; GlaxoSmithKline; Janssen; Kyowa Kirin; LEO Pharma; Medac; Merck; Novartis; Miltenyi Biotec; Ocean Pharma; Pfizer; Regeneron; Samsung Bioepis; Sanofi Genzyme; Takeda; UCB; Valeant and Xenoport., Consultant of: Affibody; Almirall; Amgen; Biogen; Boehringer Ingelheim; Celgene; Centocor; Covagen; Eli Lilly; Forward Pharma; Fresenius Medical Care; GlaxoSmithKline; Janssen; Kyowa Kirin; LEO Pharma; Medac; Merck; Novartis; Miltenyi Biotec; Ocean Pharma; Pfizer; Regeneron; Samsung Bioepis; Sanofi Genzyme; Takeda; UCB; Valeant and Xenoport., Speakers bureau: Affibody; Almirall; Amgen; Biogen; Boehringer Ingelheim; Celgene; Centocor; Covagen; Eli Lilly; Forward Pharma; Fresenius Medical Care; GlaxoSmithKline; Janssen; Kyowa Kirin; LEO Pharma; Medac; Merck; Novartis; Miltenyi Biotec; Ocean Pharma; Pfizer; Regeneron; Samsung Bioepis; Sanofi Genzyme; Takeda; UCB; Valeant and Xenoport., Alice B Gottlieb Grant/research support from:: Research grants, consultation fees, or speaker honoraria for lectures from: Pfizer, AbbVie, BMS, Lilly, MSD, Novartis, Roche, Sanofi, Sandoz, Nordic, Celltrion and UCB., Consultant of:: Research grants, consultation fees, or speaker honoraria for lectures from: Pfizer, AbbVie, BMS, Lilly, MSD, Novartis, Roche, Sanofi, Sandoz, Nordic, Celltrion and UCB., Speakers bureau:: Research grants, consultation fees, or speaker honoraria for lectures from: Pfizer, AbbVie, BMS, Lilly, MSD, Novartis, Roche, Sanofi, Sandoz, Nordic, Celltrion and UCB., Mark Lebwohl Grant/research support from: AbbVie, Amgen, Arcutis, AstraZeneca, Boehringer Ingelheim, Celgene, Clinuvel, Eli Lilly, Incyte, Janssen Research & Development, LLC, Kadmon Corp., LLC, Leo Pharmaceutucals, Medimmune, Novartis, Ortho Dermatologics, Pfizer, Sciderm, UCB, Inc., and ViDac, Consultant of: Allergan, Almirall, Arcutis, Inc., Avotres Therapeutics, BirchBioMed Inc., Boehringer-Ingelheim, Bristol-Myers Squibb, Cara Therapeutics, Castle Biosciences, Corrona, Dermavant Sciences, Evelo, Foundation for Research and Education in Dermatology, Inozyme Pharma, LEO Pharma, Meiji Seika Pharma, Menlo, Mitsubishi, Neuroderm, Pfizer, Promius/Dr. Reddy’s Laboratories, Theravance, and Verrica, Stefan Schreiber Consultant of: AbbVie, Arena, BMS, Biogen, Celltrion, Celgene, IMAB, Gilead, MSD, Mylan, Pfizer, Fresenius, Janssen, Takeda, Theravance, provention Bio, Protagonist and Falk, Weibin Bao Shareholder of: Novartis, Employee of: Novartis, Kwaku Marfo Shareholder of: Novartis, Employee of: Novartis, Hanno Richards Shareholder of: Novartis, Employee of: Novartis, Luminita Pricop Shareholder of: Novartis, Employee of: Novartis, Abhijit Shete Shareholder of: Novartis, Employee of: Novartis, Jorge Safi Shareholder of: Novartis, Employee of: Novartis, Philip J Mease Grant/research support from: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB – grant/research support, Consultant of: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Eli Lilly, Novartis, Pfizer, Sun Pharmaceutical, UCB – consultant, Speakers bureau: Abbott, Amgen, Biogen Idec, BMS, Eli Lilly, Genentech, Janssen, Pfizer, UCB – speakers bureau
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Amundarain, Ane, Luis Vitores Valcárcel, Raquel Ordoñez, Leire Garate, Estíbaliz Miranda, Xabier Cendoya, Maria Jose Calasanz, et al. "Lncrnas As New Partners of Novel Chimeric Transcripts in Multiple Myeloma." Blood 134, Supplement_1 (November 13, 2019): 4356. http://dx.doi.org/10.1182/blood-2019-122568.
Full textAbstract:
Deregulation of long non-coding RNAs (lncRNAs) is a common feature of cancer, including Multiple Myeloma (MM). In our previous studies, we detected 11,495 and 40,511 previously non-annotated lncRNAs during normal humoral immune response and MM patient samples, respectively. These results support an important role for the lncRNAs transcriptome in this hematological malignancy. lncRNAs are genes that differ from coding genes in that they do not give rise to a protein. Nevertheless, lncRNA could undergo the same genetic alterations as coding genes. In this study, we hypothesize that lncRNAs can be involved in the principal genetic alterations occurring in MM such as chromosomal translocations, affecting the Immunoglobulin loci (IG) and in the majority of which the fusion partner still remains unknown. In order to unveil the role of lncRNAs in fusion transcripts occurring in MM, we analyzed the strand specific RNA-seq (ssRNA-seq) data obtained from 35 samples from different subpopulations of B cells (Naïve, Centroblast, Centrocyte, Memory and Plasma cells (PCs)), purified PCs from 32 MM patients and 3 MM cell lines. Chimeric transcripts were detected with the STAR-Fusion software, identifying 1,347 novel fusion transcripts ranging from 1 to 142 chimeric transcripts per sample. Strikingly, healthy PC samples (from tonsils and bone marrow) yielded the highest number of fusion transcripts, while other B cell subpopulations showed overall low numbers and MM samples turned out highly variable. 96% of all fusion transcripts detected in healthy PCs occurred with IG genes and harbored few reads per transcript, suggesting that the hyperactive transcription of the IG loci in PCs may be the cause for their formation and are probably not involved in the pathogenesis of the disease. We also found that HLA fusion transcripts were abundant in Naïve B cells, disappearing progressively during the humoral immune response (Figure 1). Interestingly, fusion transcripts identified in different B cell subpopulations were not detected in MM samples. Next, we focus on myeloma samples and identified 362 chimeric transcripts (312 unique) expressed specifically in MM (ranging from 2 to 24 chimeric transcripts per sample), most of them (84%) identified for the first time. 69% of these transcripts partnered with the IG genes, while the other fusions involved two non-IG genes. Interestingly, as we hypothesized, 26,5% of the chimeric transcripts in MM occurred with lncRNA as a partner, increasing the relevance of lncRNAs in this disease. Furthermore, using the read distribution per chimeric transcript, we identified a prevalent reciprocal transcript or a prevalent transcript expressed with >1 FFPM in 47% of MM samples, suggesting that they could derived from underlying genomic rearrangements. Besides these prevalent transcripts, we observed that 40% of the non-IG fusion transcripts occurred between adjacent genes, defining novel MM-transcriptional read-throughs, possibly caused by the oncogenic stress suffered by MM cells. Some of these chimeric transcripts were validated in different cell lines of MM by conventional PCR and sequencing. In summary, our findings show that ssRNA-seq data is an adequate strategy for the detection of chimeric transcripts in MM, being able to detect highly expressed chimeric transcripts that probably were derived from an underlying genomic rearrangements and also new categories of chimeric transcripts. In addition, our study reveals a complex landscape of fusion transcripts in the MM, many of them including a lncRNA, which could be potential therapeutic targets for the development of new treatment strategies for MM. Disclosures Paiva: Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, Novartis, Roche, and Sanofi; unrestricted grants from Celgene, EngMab, Sanofi, and Takeda; and consultancy for Celgene, Janssen, and Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau. San-Miguel:Amgen, Bristol-Myers Squibb, Celgene, Janssen, MSD, Novartis, Roche, Sanofi, and Takeda: Consultancy, Honoraria.
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Puig, Noemi, Maria-Victoria Mateos, Teresa Contreras, Bruno Paiva, María Teresa Cedena, José J. Pérez, Irene Aires, et al. "Qip-Mass Spectrometry in High Risk Smoldering Multiple Myeloma Patients Included in the GEM-CESAR Trial: Comparison with Conventional and Minimal Residual Disease IMWG Response Assessment." Blood 134, Supplement_1 (November 13, 2019): 581. http://dx.doi.org/10.1182/blood-2019-127717.
Full textAbstract:
Introduction: The GEM-CESAR trial is a potentially curative strategy for high-risk smoldering multiple myeloma (HRsMM) patients in which the primary endpoint is the assessment of bone marrow minimal residual disease negativity by next generation flow (NGF). However, alternative methods of tumor burden evaluation in serum, like Quantitative Immunoprecipitation Mass Spectrometry (QIP-MS), a polyclonal antibody-based technology to identify intact immunoglobulins, have been also evaluated. Patients and Methods: Ninety HRsMM patients included in the GEM-CESAR trial received six 4-weeks cycles of carfilzomib, lenalidomide and dexamethasone followed by high dose melphalan and ASCT and 2 further cycles of consolidation with the same regimen. All patients received maintenance with lenalidomide up to 2 years. SPEP and IFE were performed using standard procedures and MRD was analyzed by flow cytometry following EuroFlow recommendations. QIP-MS assessment has been previously described (1) and allowed us the characterization of the isotype of each Ig trough immunoprecipitation with paramagnetic beads as well as the measurement of the molecular mass of each Ig for each specific patient, with enough precision and accuracy to establish clonality. Standard response assignment was carried out as per the IMWG guidelines. Results: First, we confirmed the higher sensitivity of QIP-MS to identify the presence of a serum M-spike as compared to conventional protein immunofixation electrophoresis methods. Amongst patients in CR, QIP-MS identified the M-spike in 18/30 (60%) post-induction, 18/47(38%) post-ASCT and 25/58(43%) post-consolidation. Interestingly, similar results were obtained with MRD-NGF post-induction [17/30(57%)] and post-ASCT [15/47(32%)] although the positive rate post-consolidation [15/58(26%)] was higher with QIP-MS. Then, we analyzed the overall concordance between the results obtained with QIP-MS and MRD-NGF at the three timepoints of disease evaluation, finding an overall concordance of 81% post-induction (n=76), 70% post-transplant (n=76) and 68% post-consolidation (n=77). Thus, when compared to the results of MRD-NGF, QIP-MS demonstrated sensitivities of 100%, 79% and 77% post-induction, post-ASCT and post-consolidation, and negative predictive values (NPV) of 100%, 79% and 82% at each respective time-point. (P < 0,0001; P = 0,0004; P = =,0012) Evaluation of discrepant cases showed 14 out of 22 MRD-NGF-negative patients post-induction for whom QIP-MS identified a M-spike; in some cases (i.e. IgG MM isotype) this may be related to a longer immunoglobulin half-life. There were no cases with detectable disease by NGF but QIP-MS negative. By contrast, post-ASCT, QIP-MS was negative in seven MRD-positive patients, two of whom became MRD-NGF-negative after consolidation; at last follow-up, none of them have progressed. On the other hand, sixteen patients with negative MRD-NGF after ASCT had a detectable M-spike by mass spectrometry. Of note, the M-spike became undetectable after consolidation in six out of these 16 patients. Post-consolidation, there were 7 patients in which MRD-NGF was positive but QIP-MS negative: MRD evaluation during maintenance is pending but none of them have so far progressed. By contrast, there were 18 patients with the M-spike detectable by QIP-MS but MRD-NGF negative: follow-up of these patients will address their outcome but, the only patient that has progressed so far had MRD-NGF negative post-induction, becoming positive post-transplant and consolidation, but the M-spike was detectable by QIP-MS throughout. Conclusions: M-spike monitoring by QIP-MS shows a moderate concordance with the MRD assessment by NGF in this group of HRsMM homogeneously treated. Longer follow-up will allow us to unravel the outcome of discordant cases and to define the specificity of QIP-MS and its complementary value to NGF. North S, Barnidge D, Brusseau S, Patel R, Haselton M, Du Chateau B, et al. QIP-MS: A specific, sensitive, accurate, and quantitative alternative to electrophoresis that can identify endogenous m-proteins and distinguish them from therapeutic monoclonal antibodies in patients being treated for multiple myeloma. Clinica Chimica Acta 2019;493:S433. Disclosures Puig: Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding; The Binding Site: Honoraria; Takeda, Amgen: Consultancy, Honoraria. Mateos:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria; GSK: Membership on an entity's Board of Directors or advisory committees; Pharmamar: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; EDO: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Paiva:Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, Novartis, Roche, and Sanofi; unrestricted grants from Celgene, EngMab, Sanofi, and Takeda; and consultancy for Celgene, Janssen, and Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau. Rodriguez Otero:Takeda: Consultancy; Kite Pharma: Consultancy; BMS: Honoraria; Celgene Corporation: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria. Oriol:Celgene, Amgen, Takeda, Jansse: Consultancy, Speakers Bureau. Rios:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Alegre:Celgene, Amgen, Janssen, Takeda: Membership on an entity's Board of Directors or advisory committees. de la Rubia:AbbVie: Consultancy; Janssen: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Takeda: Consultancy. De Arriba:Amgen: Consultancy, Honoraria; Takeda: Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Ocio:Mundipharma: Research Funding; Pharmamar: Consultancy; Amgen: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; AbbVie: Consultancy; Takeda: Consultancy, Honoraria; Array Pharmaceuticals: Research Funding; Sanofi: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy; Novartis: Consultancy, Honoraria; BMS: Honoraria. Bladé:Janssen, Celgene, Amgen, Takeda: Membership on an entity's Board of Directors or advisory committees; Irctures: Honoraria. Lahuerta:Takeda, Amgen, Celgene and Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees.
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Coates, L. C., L. Gossec, E. Theander, P. Bergmans, M. Neuhold, C. Karyekar, M. Shawi, W. Noel, G. Schett, and I. Mcinnes. "OP0230 EFFICACY AND SAFETY OF GUSELKUMAB IN PATIENTS WITH ACTIVE PSORIATIC ARTHRITIS WHO DEMONSTRATED INADEQUATE RESPONSE TO TUMOR NECROSIS FACTOR INHIBITION: WEEK 24 RESULTS OF A PHASE 3B, RANDOMIZED, CONTROLLED STUDY." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 140–41. http://dx.doi.org/10.1136/annrheumdis-2021-eular.42.
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Background:Guselkumab (GUS), a selective monoclonal antibody targeting the interleukin-23p19 subunit, has demonstrated efficacy in 2 pivotal Ph3 psoriatic arthritis (PsA) studies (DISCOVER-1,1 DISCOVER-22).Objectives:Evaluate GUS efficacy and safety in PsA patients (pts) with inadequate response (IR) to tumor-necrosis-factor inhibition (TNFi) through Week24 (W24) of the Ph3b COSMOS study.Methods:In this randomized, double-blind, placebo (PBO)-controlled trial, 285 pts with active PsA (≥3 swollen & ≥3 tender joints) who demonstrated lack of benefit or intolerance to 1-2 TNFi were randomized 2:1 to subcutaneous GUS 100mg (n=189) or PBO (n=96) at W0, W4, then every 8 weeks (Q8W) through W44 (with PBO crossover to GUS at W24). At W16, pts who met early escape (EE) criteria (<5% improvement in both tender & swollen joint counts) also could switch from PBO to GUS. The primary efficacy endpoint was ACR20 response at W24 among randomized, treated pts. Pts missing ACR20 data at W24 or who met treatment failure criteria (including meeting EE criteria at W16) were considered nonresponders (NRs). Subgroup analyses were performed to assess consistency of primary treatment effect based on demographics, disease characteristics, and medication use at baseline. Prespecified sensitivity analyses included ‘Per-Protocol’ (PP) (excluded pts with major protocol deviations) and ‘EE-Correction’ (included pts incorrectly routed to EE) analyses. Adverse events (AEs) were summarized by treatment received.Results:Baseline characteristics were similar across GUS and PBO pts, though a higher proportion of females and more severe joint symptoms were seen in the GUS group. At W24, 44.4% of GUS vs 19.8% of PBO pts achieved ACR20 (p<0.001) (Figure). GUS was superior to PBO for all major secondary endpoints. Efficacy was consistent across subgroups defined by baseline characteristics, including in pts who discontinued prior TNFi use due to inadequate efficacy (84% GUS vs 81% PBO) and safety (16% GUS vs 19% PBO) (Table). 20 pts (12 GUS, 8 PBO) were incorrectly routed to EE. Results of PP (48.8% vs 23.8%) and EE-correction (48.1% vs 19.8%) sensitivity analyses were consistent with the primary analysis (Figure). AEs were similar between GUS- and PBO-treated pts (Table).Table 1.Baseline characteristics of, and adverse events reported by, randomized and treated COSMOS ptsGUS 100 mg Q8W (N=189)PBO (N=96) Age, y4949 Sex, Female54%46% Duration of PsA, y8.38.7 Body mass index, kg/m22931a Swollen (0-66) / tender (0-68) joint count10 / 219 / 18 Pt pain / Pt global arthritis / Physician global disease, 0-10 cm VAS6.5 / 6.5 / 6.96.0 / 6.2 / 6.4 Health Assessment Questionnaire-Disability Index, 0-31.3b1.2 C-reactive protein, mg/dL1.2b1.2 Methotrexate use at baseline56%53% Psoriatic body surface area, %17.913.4 Number of prior TNFi: 1 / 288% / 12%89% / 11% Reason for prior TNFi discontinuation: Efficacy / Safety84% / 16%* 81% / 19%*Pts with ≥1 AE / SAE37% / 3%48% / 3%Pts with ≥1 infection / serious infection18% / 0%20% / 0%Pts with ≥1 AE leading to study agent discontinuation2%2%Pts with ≥1 malignancy0.4%0Pts with ≥1 injection-site reaction2%1%Data shown are mean or %. aN=95; bN=188. *Missing for 1 pt. SAE – serious adverse events; VAS – visual analog scaleConclusion:In this Ph3b, placebo-controlled study of PsA pts with IR to 1-2 TNFi, GUS 100 mg Q8W elicited a significantly higher ACR20 response rate vs. PBO at W24; results of prespecified sensitivity and subgroup analyses were consistent. GUS safety in TNF-IR PsA pts through W24 is consistent with the favorable GUS safety profile in psoriasis and biologic-naïve PsA pts.3References:[1]Deodhar A. Lancet 2018;391: 2213–24.[2]Mease PJ. Lancet 2020;395: 1126–36.[3]Guselkumab Prescribing Information. Janssen Biotech, Inc.Disclosure of Interests:Laura C Coates Consultant of: AbbVie, Amgen, Biogen, BMS, Boehringer Ingelehim, Celgene, Domain, Eli Lilly, Gilead, Janssen, Medac, Novartis, Pfizer and UCB, Grant/research support from: AbbVie, Amgen, Celgene, Eli Lilly, Gilead, Novartis, Pfizer, Laure Gossec Consultant of: AbbVie, Amgen, BMS, Biogen, Celgene, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, Samsung Bioepis, Sanofi-Aventis, UCB, Grant/research support from: Amgen, Eli Lilly, Galapagos, Janssen, Pfizer, Sandoz, Sanofi, Elke Theander Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Paul Bergmans Shareholder of: Johnson & Johnson, Employee of: Janssen, Marlies Neuhold Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Chetan Karyekar Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC, May Shawi Shareholder of: Johnson & Johnson, Employee of: Janssen Global Services, LLC, Wim Noel Shareholder of: Johnson & Johnson, Employee of: Janssen Scientific Affairs, LLC, Georg Schett: None declared, Iain McInnes Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, and UCB
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Deodhar, A., D. Van der Heijde, J. Sieper, F. Van den Bosch, W. P. Maksymowych, T. H. Kim, M. Kishimoto, et al. "OP0144 EFFICACY AND SAFETY OF UPADACITINIB IN PATIENTS WITH ACTIVE ANKYLOSING SPONDYLITIS: 1-YEAR RESULTS FROM A RANDOMIZED, DOUBLE-BLIND, PLACEBO-CONTROLLED STUDY WITH OPEN-LABEL EXTENSION." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 85–86. http://dx.doi.org/10.1136/annrheumdis-2021-eular.473.
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Background:Upadacitinib (UPA) was efficacious and well tolerated vs placebo (PBO) during the first 14 weeks (wks) of the phase 2/3 SELECT-AXIS 1 study in patients (pts) with active ankylosing spondylitis (AS) who had an inadequate response to NSAIDs.1Objectives:To report efficacy and safety of UPA through 1 year in the SELECT-AXIS 1 study.Methods:In SELECT-AXIS 1 (NCT03178487) pts were randomized 1:1 to UPA 15 mg once daily (QD) or PBO; at wk 14, pts continued in the 90-wk open-label extension and received UPA 15 mg QD; reported here are data up to wk 64. The study enrolled pts (≥18 y) with active AS (defined as BASDAI ≥4 and pt assessment of back pain ≥4 [numeric rating scale, 0–10] at screening and baseline [BL]) who had inadequate response to ≥2 NSAIDs or intolerance to or contraindication for NSAIDs and were biologic DMARD naive. Efficacy assessments included percentage of pts with Assessment of SpondyloArthritis international Society (ASAS) 20/40 response, ASAS partial remission, BASDAI50, AS Disease Activity Score (ASDAS) and change from BL in ASDAS and BASFI. Data are reported as observed and by using non-responder imputation (NRI). Treatment-emergent adverse events (TEAEs) were reported as events per 100 patient-years (PY) up to January 31, 2020.Results:Of 187 pts, 178 pts (each n=89 for UPA and PBO arms) completed wk 14 on study drug and entered the open-label extension; 160 pts completed wk 64. Efficacy was maintained or continued to improve throughout the study in the continuous UPA group: 85% (95% CI, 77%–93%) of pts achieved ASAS40 at wk 64 in the as-observed analysis and 72% (63%–81%) in the NRI analysis (Figure). Pts who switched from PBO to UPA at wk 14 showed similar speed of onset and magnitude of response vs pts initially randomized to UPA: 81% (95% CI, 72%–89%) in the as-observed analysis and 70% (61%–80%) in the NRI analysis achieved ASAS40 at wk 64 (Figure). Similar results were observed for other efficacy endpoints (Figure). Among all 182 pts receiving UPA, 618 AEs were reported. AEs leading to discontinuation and serious AEs were low (Table). No serious infections, active tuberculosis, venous thromboembolic events, gastrointestinal perforation, major adverse cardiovascular events, renal dysfunction, or deaths were reported.Table 1.TEAEs per 100 PYsEvents/(E/100 PY)UPA 15 mg QDN=182 (237.6 PY)Any AE618 (260.1)Serious AE14 (5.9)AE leading to discontinuation15 (6.3)Infections205 (86.3) Opportunistic infection*2 (0.8) Herpes zoster†5 (2.1)Creatine phosphokinase elevation‡28 (11.8)Hepatic disorder§24 (10.1)Neutropenia||7 (2.9)Anemia||3 (1.3)Lymphopenia||2 (0.8)Malignancy¶1 (0.4)Death0AE, adverse event; PY, patient-year; QD, once daily; TEAE, treatment-emergent AE; UPA, upadacitinib.*Two non-serious events of esophageal candidiasis in the same patient.†Five events in 4 patients; all non-serious and limited to 1 dermatome.‡All events were non-serious and none led to study drug discontinuation; majority were asymptomatic.§Majority based on asymptomatic alanine aminotransferase/aspartate aminotransferase elevations; all were non-serious and none led to study drug discontinuation.||All events were non-serious and none led to study drug discontinuation.¶Squamous cell carcinoma of tongue in 61-year-old male former smoker; no reasonable possibility to be study drug related per investigator.Conclusion:UPA 15 mg QD showed sustained and consistent efficacy over 1 year. Pts who switched from placebo to UPA at wk 14 showed a similar efficacy response compared with pts who received continuous UPA. No new safety findings were observed compared with safety data from the UPA clinical development program in other indications.2References:[1]van der Heijde D, et al. Lancet. 2019;394(10214):2108-2117.[2]Cohen, et al. Arthritis Rheumatol. 2019;71(suppl 10).Acknowledgements:AbbVie funded this study and participated in the study design, research, analysis, data collection, interpretation of data, reviewing, and approval of the publication. All authors had access to relevant data and participated in the drafting, review, and approval of this publication. No honoraria or payments were made for authorship. Medical writing support was provided by M Hovenden and J Matsuura of ICON plc (North Wales, PA) and was funded by AbbVie.Disclosure of Interests:Atul Deodhar Speakers bureau: Novartis, Pfizer, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, GlaxoSmithKline, Janssen, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer, UCB, Désirée van der Heijde Consultant of: AbbVie, BMS, Cyxone, Eisai, Galapagos, Gilead, GlaxoSmithKline, Lilly, Novartis, Pfizer, and UCB Pharma, Joachim Sieper Speakers bureau: AbbVie, Janssen, Lilly, Merck, and Novartis, Consultant of: AbbVie, Janssen, Lilly, Merck, and Novartis, Filip van den Bosch Speakers bureau: AbbVie, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, and UCB Pharma, Consultant of: AbbVie, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, and UCB Pharma, Walter P Maksymowych Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, UCB Pharma, Grant/research support from: AbbVie, Novartis and Pfizer, Tae-Hwan Kim Speakers bureau: AbbVie, Celltrion, Kirin, Lilly, and Novartis, Mitsumasa Kishimoto Consultant of: AbbVie, Amgen-Astellas BioPharma, Asahi-Kasei Pharma, Astellas, Ayumi Pharma, BMS, Chugai, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead, Janssen, Kyowa Kirin, Novartis, Pfizer, Tanabe-Mitsubishi, Teijin Pharma, and UCB Pharma, Andrew Ostor Consultant of: AbbVie, BMS, Roche, Janssen, Lilly, Novartis, Pfizer, UCB, Gilead, and Paradigm, Bernard Combe Speakers bureau: AbbVie, Lilly, Merck, Consultant of: AbbVie, Lilly, Gilead, Janssen, Novartis, Roche-Chugai, and Sanofi, Grant/research support from: AbbVie and Lilly, Yunxia Sui Shareholder of: AbbVie, Employee of: AbbVie, xin wang Shareholder of: AbbVie, Employee of: AbbVie, Alvina Chu Shareholder of: AbbVie, Employee of: AbbVie, In-Ho Song Shareholder of: AbbVie, Employee of: AbbVie
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Garrido-Cumbrera, M., E. Collantes-Estévez, V. Navarro-Compán, P. Zarco Montejo, C. Sastré, S. Sanz-Gómez, P. Plazuelo-Ramos, and J. Gratacos-Masmitja. "AB1160 A BENCHMARKING STUDY EVALUATING THE BURDEN OF AXIAL SPONDYLOARTHRITIS IN SPAIN COMPARED WITH THE REST OF EUROPEAN COUNTRIES. RESULTS OF THE SPANISH ATLAS AND EMAS STUDIES." Annals of the Rheumatic Diseases 79, Suppl 1 (June 2020): 1870.2–1871. http://dx.doi.org/10.1136/annrheumdis-2020-eular.5858.
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Background:Benchmarking studies in axial spondyloarthritis (axSpA) may provide evidence of disparities, making it necessary to improve the healthcare and management of these patients.Objectives:To evaluate differences between Spain and the rest of Europe (RoE) in relation to sociodemographic characteristics, life habits, and patient-reported outcomes (PROs) in axSpA patients.Methods:Data from 2,846 unselected patients from the European Map of Axial Spondyloarthritis (EMAS) were collected through an online survey, with a comparative analysis of 680 Spanish patients (2016) and 2,166 patients living in 12 other European countries (2017-2018). Socio-demographic characteristics, life habits, and PROs [BASDAI (0-10), spinal stiffness (3-12), and psychological distress (0-12, General Health Questionnaire GHQ-12)] were compared. The Χ2test was used for qualitative variables and the Mann-Whitney test applied for quantitative variables.Results:Data from 680 (23.9%) Spanish patients were compared to 2,166 (76.1%) patients from the RoE. Compared to Spain, the RoE patients reported a higher percentage of females (64.1% vs 52.5%; p<0.001), university studies (51.7% vs 36.9%; p<0.001) and higher income per family member (€1,173.5 vs €823.2; p<0.001). In Spain, the proportion of respondents who were members of patient associations was higher than in RoE (44.3% vs 37.2%; p<0.001) (Table 1). Also compared to RoE, Spanish patients showed a greater diagnostic delay (8.5±7.7 vs 7.2±8.6; p<0.001), HLA-B27 carriership (77.1% vs 70.1%; p=0.003), and disease activity (5.7±2.0 vs 5.4±2.0; p=0.024). Despite lower diagnosis of anxiety and depression rates, Spanish patients reported greater psychological distress (5.7±4.5 vs 4.8±4.0; p<0.001). However, RoE patients declared greater spinal stiffness compared to Spanish patients (7.8±2.4 vs 7.5±2.7; p=0.009) (Table 2).Table 1.Comparison of socio-demographic characteristics and lifestyle habits of axSpA patients in Spain and in RoESpain (n = 680)Mean ± SD; n (%)RoE (n = 2,166)Mean ± SD; n (%)p-valueAge (Years)45.7 ± 10.843.4 ± 12.6<0.001*Gender (Female)357 (52.5)1389 (64.1)<0.001*Educational level - No schooling9 (1.3)23 (1.1)<0.001* - Primary school119 (17.5)144 (6.6) - High school301 (44.3)880 (40.6) - University251 (36.9)1,119 (51.7)Monthly income (€) per household member823.2 ± 656.41,173.5 ± 928.8<0.001*Smoking - Non-smoker or socially417 (71.3)1,679 (77.5)<0.001* - Less than 10 cig/day24 (4.1)111 (5.1) - More than 10 cig/day144 (24.6)376 (17.4)Alcohol - Never or occasionally503 (86.0)1,723 (79.5)<0.001* - 1–2 times per week37 (6.3)292 (13.5) - More than 2 per week45 (7.7)151 (7.0)Member of a patient support group301 (44.3)806 (37.2)0.001*Table 2.Comparison of PROs of axSpA patients between Spain and RoESpain (n = 680)Mean ± SD; n (%)RoE (n = 2166)Mean ± SD; n (%)p valueDiagnostic delay, years8.5 ± 7.77.2 ± 8.6<0.001*HLA-B27 (positive)391 (77.1)892 (70.1)0.003*BASDAI (0–10)5.7 ± 2.05.4 ± 2.00.024*Spinal Stiffness (3–12)7.5 ± 2.77.8 ± 2.40.009*GHQ-12 (0–12)5.7 ± 4.54.8 ± 4.0<0.001*Anxiety135 (19.9)674 (33.1)<0.001*Depression100 (14.7)610 (30.0)<0.001*Conclusion:In this study, significant differences between Spanish and RoE patients were observed for the burden of the disease in patients with axSpA. Patients in Spain experience a greater diagnostic delay and greater psychological distress.Acknowledgments:Funded by Novartis Farmacéutica S.A.Disclosure of Interests:Marco Garrido-Cumbrera: None declared, Eduardo Collantes-Estévez Grant/research support from: ROCHE and Pfizer., Speakers bureau: ROCHE, Lilly, Bristol and Celgene., Victoria Navarro-Compán Consultant of: Abbvie, Lilly, Novartis, Pfizer, UCB, Speakers bureau: AbbVie, MSD, Lilly, Novartis, Pfizer, UCB, Pedro Zarco Montejo Grant/research support from: Pfizzer, MSD, ABBVIE, Janssen, Amgen, BMS, Novartis, Lilly, Speakers bureau: Pfizzer, MSD, ABBVIE, Janssen, Amgen, BMS, Novartis, Lilly, Carlos Sastré Employee of: YES; I´m Medical Advisor in Novartis Spain, Sergio Sanz-Gómez: None declared, Pedro Plazuelo-Ramos: None declared, Jordi Gratacos-Masmitja Grant/research support from: a grant from Pfizzer to study implementation of multidisciplinary units to manage PSA in SPAIN, Consultant of: Pfizzer, MSD, ABBVIE, Janssen, Amgen, BMS, Novartis, Lilly, Speakers bureau: Pfizzer, MSD, ABBVIE, Janssen, Amgen, BMS, Novartis, Lilly
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Gambella, Manuela, Paola Omedè, Stefania Oliva, Milena Gilestro, Vittorio Emanuele Muccio, Daniela Drandi, Simone Ferrero, et al. "In Multiple Myeloma, Minimal Residual Disease (MRD) Is an Early Predictor of Progression and Is Modulated By Maintenance Therapy with Lenalidomide." Blood 124, no. 21 (December 6, 2014): 3394. http://dx.doi.org/10.1182/blood.v124.21.3394.3394.
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Abstract Background. Minimal residual disease (MRD) detection by multi-parameter flow cytometry (MFC) and real time quantitative PCR (RQ-PCR) is highly predictive of outcome in multiple myeloma (MM) patients (pts). Less is known on the ability of maintenance therapy to modulate MRD levels. The primary end-point of this study was to monitor MRD during maintenance therapy and to evaluate the impact on outcome. Patients and Methods. In the RV-MM-EMN-441 study (NCT01091831), after induction and consolidation pts received maintenance therapy with either Lenalidomide alone (R) or Lenalidomide-Dexamethasone (RD) until progression. Pts achieving at least very good partial response (VGPR) after induction/consolidation treatment were eligible for the MRD sub-study. MRD analysis was performed on bone marrow (BM) samples at diagnosis, after consolidation, after 3 and 6 courses of maintenance, and thereafter every 6 months until progression. MFC complete remission (CR) was defined by <1E-04 monoclonal plasmacells (PCs). Molecular-CR was defined by <1E-05 according to EuroMRD guidelines. MFC and molecular progression were defined by confirmed 25% increase of malignant plasma cells. Results. MRD sub-study included 50 pts with a median age of 57 years (range 40-65). After consolidation 34/50 (68%) pts achieved VGPR, 16/48 (32%) achieved CR according to IMWG criteria (Rajkumar et al. Blood 2011). After a median follow-up of 44 months, 22/50 (44%) progressed and 7/50 (14%) deaths were recorded, with a 4-year PFS of 49% and 4-year OS of 87%. In the MFC analysis 19/50 pts (38%) achieved MFC-CR after consolidation, while other additional 7/50 pts (14%) achieved MFC-CR during maintenance. Among pts who achieved MFC–CR (< 1E-04), 7/26 (27%) pts progressed after a median of 30 months; among those who did not reach MFC–CR, 15/24 (62%) pts progressed after a median of 26 months (p=0.009). In 18/19 pts MFC-progression anticipated clinical relapse of a median of 9 months. In 1/19 pts, clinical extra-medullary progression anticipated MFC-progression. A molecular marker was identified in 25/50 pts (50%); 4/25 pts (16%) achieved molecular-CR after consolidation, while other additional 3/25 pts (20%) achieved molecular-CR during maintenance. Among pts who achieved molecular–CR (<1E-05), 2/7 (28%) pts progressed after a median of 34 months; among those who did not reach molecular–CR, 11/18 (61%) pts progressed after a median of 30 months (p=0.15). In 12/13 pts molecular-progression anticipated clinical relapse of a median of 8 months. In 1/13 pts, clinical extra-medullary progression anticipated molecular-progression. Conclusions. Lower MRD values, both with MFC and RQ-PCR procedures, predict better outcome. 30% of patients achieved MFC-CR (7/26) or molecular-CR (3/7) during maintenance therapy suggesting that MRD levels can be modified by maintenance. MRD progression anticipates clinical relapse of approximately 8 months. Disclosures Off Label Use: lenalidomide used as off-label. Ferrero:MUNDIPHARMA: Honoraria. Gay:Sanofi: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Patriarca:Merck Sharp & Dohme: Honoraria; Janssen and Cilag: Honoraria; Celgene: Honoraria. Petrucci:CELGENE: Honoraria; JANSSEN-CILAG: Honoraria; SANOFI: Honoraria; BRISTOL MYERS SQUIBB: Honoraria. Caravita:Celgene: Honoraria. Di Raimondo:CELGENE: Honoraria; JANSSEN-CILAG: Honoraria. Musto:CELGENE: Honoraria; JANSSEN-CILAG: Honoraria. Boccadoro:Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees; Onyx: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen-Cilag: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees. Palumbo:Array BioPharma: Honoraria; Onyx Pharmaceuticals: Consultancy, Honoraria; Millennium Pharmaceuticals, Inc.: Consultancy, Honoraria; Janssen-Cilag: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Genmab A/S: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Sanofi: Honoraria.
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Hainfeld, James F., Frederic R. Fumya, and Richard D. Powell. "A new 1.4 nm gold-Fab probe." Proceedings, annual meeting, Electron Microscopy Society of America 49 (August 1991): 284–85. http://dx.doi.org/10.1017/s0424820100085721.
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A major advance in high resolution EM immunoprobes has recently been achieved: The smallest gold particles easily seen directly in the TEM have been coupled to Fab fragments thus making them the smallest gold-antibody probe commercially available.The gold particle, NanogoldTM, is 1.4 nm in diameter with a very controlled size range, ± 10% (Fig. 1). This is in sharp contrast to other small gold preparations, such as Auroprobe One (Janssen Life Sciences) which actually ranges from 1-3 nm.The Fab conjugate (Fig. 2) has close to one gold particle per Fab fragment. This again is different from other gold-IgG probes that have 0.2-10 gold particles per IgG. Another difference is that the Nanogold-Fab conjugates are separate molecules in solution rather than the often extensive aggregation of other colloidal gold-IgG preparations. The problems of ratio of gold particles to antibody and aggregation in conventional colloidal conjugates were shown to be controllable by careful trial and error testing.
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Foltz, Steven M., Qingsong Gao, Christopher J. Yoon, Amila Weerasinghe, Hua Sun, Lijun Yao, Mark A. Fiala, et al. "Comprehensive Multi-Omics Analysis of Gene Fusions in a Large Multiple Myeloma Cohort." Blood 132, Supplement 1 (November 29, 2018): 1898. http://dx.doi.org/10.1182/blood-2018-99-117245.
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Abstract Introduction: Gene fusions are the result of genomic rearrangements that create hybrid protein products or bring the regulatory elements of one gene into close proximity of another. Fusions often dysregulate gene function or expression through oncogene overexpression or tumor suppressor underexpression (Gao, Liang, Foltz, et al. Cell Rep 2018). Some fusions such as EML4--ALK in lung adenocarcinoma are known druggable targets. Fusion detection algorithms utilize discordantly mapped RNA-seq reads. Careful consideration of detection and filtering procedures is vital for large-scale fusion detection because current methods are prone to reporting false positives and show poor concordance. Multiple myeloma (MM) is a blood cancer in which rapidly expanding clones of plasma cells spread in the bone marrow. Translocations that juxtapose the highly-expressed IGH enhancer with potential oncogenes are associated with overexpression of partner genes, although they may not lead to a detectable gene fusion in RNA-seq data. Previous studies have explored the fusion landscape of multiple myeloma cohorts (Cleynen, et al. Nat Comm 2017; Nasser, et al. Blood 2017). In this study, we developed a novel gene fusion detection pipeline and post-processing strategy to analyze 742 patient samples at the primary time point and 64 samples at follow-up time points (806 total samples) from the Multiple Myeloma Research Foundation (MMRF) CoMMpass Study using RNA-seq, WGS, and clinical data. Methods and Results: We overlapped five fusion detection algorithms (EricScript, FusionCatcher, INTEGRATE, PRADA, and STAR-Fusion) to report fusion events. Our filtered call set consisted of 2,817 fusions with a median of 3 fusions per sample (mean 3.8), similar to glioblastoma, breast, ovarian, and prostate cancers in TCGA. Major recurrent fusions involving immunoglobulin genes included IGH--WHSC1 (88 primary samples), IGL--BMI1 (29), and the upstream neighbor of MYC, PVT1, paired with IGH (6), IGK (3), and IGL (11). For each event, we used WGS data when available to determine if there was genomic support of the gene fusion (based on discordant WGS reads, SV event detection, and MMRF CoMMpass Seq-FISH WGS results) (Miller, et al. Blood 2016). WGS validation rates varied by the level of RNA-seq evidence supporting each fusion, with an overall rate of 24.1%, which is comparable to previously observed pan-cancer validation rates using low-pass WGS. We calculated the association between fusion status and gene expression and identified genes such as BCL2L11, CCND1/2, LTBR, and TXNDC5 that showed significant overexpression (t-test). We explored the clinical connections of fusion events through survival analysis and clinical data correlations, and by mining potentially druggable targets from our Database of Evidence for Precision Oncology (dinglab.wustl.edu/depo) (Sun, Mashl, Sengupta, et al. Bioinformatics 2018). Major examples of upregulated fusion kinases that could potentially be targeted with off-label drug use include FGFR3 and NTRK1. We examined the evolution of fusion events over multiple time points. In one MMRF patient with a t(8;14) translocation joining the IGH locus and transcription factor MAFA, we observed IGH fusions with TOP1MT (neighbor of MAFA) at all four time points with corresponding high expression of TOP1MT and MAFA. Using non-MMRF single-cell RNA data from different patients, we were able to track cell-type composition over time as well as detect subpopulations of cells harboring fusions at different time points with potential treatment implications. Discussion: Gene fusions offer potential targets for alternative MM therapies. Careful implementation of gene fusion detection algorithms and post-processing are essential in large cohort studies to reduce false positives and enrich results for clinically relevant information. Clinical fusion detection from untargeted RNA-seq remains a challenge due to poor sensitivity, specificity, and usability. By combining MMRF CoMMpass data from multiple platforms, we have produced a comprehensive fusion profile of 742 MM patients. We have shown novel gene fusion associations with gene expression and clinical data, and we identified candidates for druggability studies. Disclosures Vij: Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jansson: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.
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Colombo Timelli, Maria. "«De vrai humain entendement». Hommage à Jacqueline Cerquiglini-Toulet, Textes rassemblés par Yasmina Foehr-Janssens et Jean-Yves Tilliette." Studi Francesi, no. 148 (XLX | I) (April 1, 2006): 138. http://dx.doi.org/10.4000/studifrancesi.30018.
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Álvarez-Reguera, C., R. Fernández-Ramón, J. J. Gaitán-Valdizán, J. L. Martín-Varillas, L. Sanchez-Bilbao, D. Martínez-López, I. González-Mazón, R. Demetrio-Pablo, M. Á. González-Gay, and R. Blanco. "POS0030 SARCOIDOSIS INCIDENCE IN A NORTHERN SPANISH HEALTH REGION." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 220. http://dx.doi.org/10.1136/annrheumdis-2021-eular.1870.
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Background:Sarcoidosis is a systemic and potentially severe disease (1). Its incidence varies widely worldwide.Objectives:The aim of this study was to estimate the sarcoidosis incidence in a Northern Spanish population-based cohort.Methods:All incident cases of sarcoidosis between January 1999 and December 2019 in a tertiary hospital were reviewed. Inclusion criteria were a) diagnosis of sarcoidosis according to ATS/ERS/WASOG (Eur Respir J. 1999; 14:735-7) and b) patients residing in our health region. Incidence between 1999 and 2019 was estimated by sex, age, and year of diagnosis.Results:From a total of 384 patients diagnosed with sarcoidosis, 234 (129 women/ 105 men) met the inclusion criteria and were finally included in the study. Mean age of the cohort at diagnosis was 48.43±14.83 years (46.95±14.50 in males; 49.63±15.04 in females, p=0.12). Annual incidence during 1999-2019 period was 3.56 per 100,000 population (3.32 per 100,000 in males and 3.72 per 100,000 in females). An upward trend in annual incidence over time was observed with rates ranging from 1.73 per 100,000 inhabitants in 1999 to 6.91 per 100,000 inhabitants in 2016 (Figure 1). Overall, sarcoidosis was predominantly diagnosed during middle adulthood. A bimodal distribution of age-specific incidence rates was observed in both sexes with two peaks in the age groups of 30-39 (4.98 per 100,000) and 60-69 years (5.12 per 100,000) in men, and in 40-49 (6.45 per 100,000) and 60-69 years (5.94 per 100,000) in women.Comparative studies with other regions are summarize in Table 1.Conclusion:A progressive increase in incident sarcoidosis is observed. The estimated incidence of sarcoidosis in this study (3.56 per 100,000) was like that of other Mediterranean countries (2). No gender predominance was observed. Demographics variations, changes in practice patters or diagnostic test improvements could explain the upward trend in sarcoidosis incidence detected in our study. Consistent with previous studies, male presented an incidence peak 10 years earlier than female (3-5).References:[1]Riancho-Zarrabeitia L, et al. Clin Exp Rheumatol 2014; 32(2): 275-84. PMID: 24321604[2]Brito-Zerón P, et al. Clin Exp Rheumatol. 2019;37(6):1052–64.[3]Arkema E V., et al. Eur Respir J. 2016;48(6):1690-9.[4]Yoon H, et al. Am J Respir Crit Care Med. 2018;197(MeetingAbstracts):1-8.[5]Ungprasert P, et. Mayo Clin Proc. 2016 Feb;91(2):183-8.Figure 1.Annual incidence of sarcoidosis in 1999-2019 (A)Table 1.Sarcoidosis incidence rates reported in the literature.Study, yearCountry, data sourceTime periodIncident casesIncidence per 100,000 persons-yearPietinalho, 1995Finland, hospital database19841,37811.4Pietinalho, 1995Japan, Hokkaido, hospital database19842881.0Yigla, 2002Israel, hospital database1980-19961200.8Byg, 2003Denmark, Danish National Patient Registry1980-19945,5367.2Gribbin, 2006UK, Health Improvement Network1990-20031,0195.0Gillman, 2007Australia, Victoria, hospital database1995-20051224.4-6.3Haraldsdottir, 2007Iceland, hospital database1981-20032353.8Musellin, 2009Turkey, healthcare providers2004-20062934.0Deubelbeiss, 2010Switzerland, Swiss Federal Office for Statistics2002-20052,9257.0Kowalska, 2014Poland, Katowice, National Health Fund2006-20101,2173.8-4.5Arkema, 2016Sweden, National Patient Register2003-201310,78710.4-14.8Baughman, 2016USA, Optum Health Care Database2010-201329,372African American: 17.8; Caucasian: 8.1; Hispanic: 4.3; Asian: 3.2Duchemann, 2017France, Seine-Saint-Denise County20123614.9Škopljanac, 2017Croatia, Split- Dalmatia County, hospital database1986-20153183.1-3.4Yoon, 2018Korea, National Health Insurance2007-20164,7910.85Fidler, 2019Canada, Ontario, health administrative data1996-201518,5506.8-7.9Fernandez, 2011Spain, Leon, hospital database2001-20081184.51Present study, 2020Spain, Santander, hospital database1999-20192343.56Disclosure of Interests:Carmen Álvarez-Reguera: None declared, Raúl Fernández-Ramón: None declared, Jorge Javier Gaitán-Valdizán: None declared, José Luis Martín-Varillas: None declared, Lara Sanchez-Bilbao: None declared, David Martínez-López: None declared, Iñigo González-Mazón: None declared, Rosalía Demetrio-Pablo: None declared, Miguel Á. González-Gay Speakers bureau: Abbvie, Pfizer, Roche, Sanofi and MSD., Grant/research support from: Abbvie, MSD, Jansen and Roche, Ricardo Blanco Speakers bureau: Abbvie, Pfizer, Roche, Bristol-Myers, Janssen, Lilly and MSD., Grant/research support from: Abbvie, MSD and Roche.
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Øvlisen, Andreas Kiesbye, Lasse H. Jakobsen, Kristian Hay Kragholm, Martin Hutchings, Henrik Frederiksen, Peter Kamper, Sandra Eloranta, et al. "Fertility Rates in Young Hodgkin Lymphoma Survivors: A Danish Nationwide Cohort Study of 769 Patients." Blood 134, Supplement_1 (November 13, 2019): 2841. http://dx.doi.org/10.1182/blood-2019-122642.
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Introduction: The vast majority of young adults with Hodgkin lymphoma (HL) are cured by contemporary first line treatments. Treatment-related long-term toxicities can have a negative impact on survivorship and the risk of infertility may be particularly pertinent to young HL survivors. This study aimed to investigate the fertility rate (rate of first child after index date) over time in patients with HL compared to the matched controls. Methods: All Danish patients with HL, including classical and lymphocyte predominant HL, diagnosed in the period 2000-2015 were identified in the Danish Lymphoma Registry. Patients aged 18-40 years at diagnosis with documented complete remission after first line therapy were included. Patient data were merged with the Danish Fertility Database and the Medical Register of Births and Deaths. For each HL patient, five random Danish citizens alive at the index date of the HL patient were matched on birth date, sex, and parenthood status (categorical; with children vs without children at the index date). Follow-up was measured from 9 months post diagnosis (index date) until the time of first child, relapse, death, or censoring, whichever came first. Patients with progression/relapse within the first 9 months after diagnosis were excluded. Cumulative incidences of first living child after the index date were computed for the entire cohort and stratified on sex using the Aalen-Johansen estimator with death or relapse before first child after index date as competing events. Cox regression was used to compare the rates of first child of HL patients and matched controls by clinical subgroups and estimated for males and females separately. Results: A total of 769 HL patients were included (male:female ratio 1.2, median age 30 years) and median follow-up was 9.9 years. The mean numbers of children per person at start of follow-up were similar in patients and matched controls (female HL patients 0.64 vs matched controls 0.63 children per individual; male HL patients 0.56 vs matched controls 0.54 children per individual). At the end of follow-up, average numbers of children were higher in male and female HL patients (female HL patients 1.22 children per individual; matched control 1.14 children per individual) and males (HL patients 1.00 children per individual; matched controls 0.92 children per individual). The cumulative incidence of first child after index date in female HL patients was lower during the first three years of follow-up compared to the matched controls. However, beyond three years of follow-up the cumulative incidences of first child after index date were similar (Figure 1A). Among male HL patients the cumulative incidence of first child after index date was higher than that of the matched controls throughout the entire follow-up (Figure 1B). Overall, fertility rates were higher in HL patients (males, 36.7 per 1,000 person years; females, 41.7 per 1,000 person years) as compared to the matched controls (males, 24.2 per 1,000 person years; females, 33.0 per 1,000 person years). The Cox regression showed that both male and female patients with HL had higher fertility rates as compared to matched controls (males, HR 1.5, p-value < 0.001; females, HR 1.2, p-value = 0.012; Table 1). This was also observed in specific clinical subgroups, i.e. ages 18-30 years, CCI 0, no children prior to diagnosis, and limited stage disease. Moreover, among patients receiving 6+ cycles of chemotherapy, fertility rates were not lower than expected (Table 1). Conclusion: The fertility rates for long-term HL survivors without progression/relapse were higher than in matched controls, in particular for male HL patients. Elevated fertility rates as compared to the matched controls were observed for lower age (<30 years), limited stage disease, and for patients without children at the time of diagnosis. No clinical subgroup did significantly decrease the fertility rates. Disclosures Hutchings: Genmab: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Research Funding; Novartis: Research Funding. Frederiksen:Abbvie: Research Funding; Alexion: Research Funding; Gilead: Research Funding; Novartis: Research Funding; Janssen: Research Funding. Eloranta:Karolinska Institutet: Other: coordinator for a public-private real world evidence; Janssen Pharmaceuticals.: Other: project coordinator for a public-private real world evidence. Glimelius:Janssen Pharmaceuticals: Honoraria. Ekstroem Smedby:Janssen Cilag: Honoraria, Other: Grant funding, Research Funding; Celgene: Honoraria, Other: Grant funding, Research Funding; Takeda: Honoraria, Other: Grant funding, Research Funding. El-Galaly:Roche: Employment, Other: Travel support; Takeda: Other: Travel support.
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Tedeschi, Alessandra, Anna Maria Frustaci, Francesca Romana Mauro, Annalisa Chiarenza, Marta Coscia, Stefania Ciolli, Gianluigi Reda, et al. "Do Age, Fitness and Concomitant Medications Influence Management and Outcomes of CLL Patients Treated with Ibrutinib?" Blood 136, Supplement 1 (November 5, 2020): 54–55. http://dx.doi.org/10.1182/blood-2020-137024.
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Background Chronic lymphocytic leukemia (CLL) is a disease of the elderly. Advancing age is associated with greater vulnerability, increasing treatment side effects and reduced survival with chemoimmunotherapy (CIT). Comorbidities burden, Charlson Comorbidity Index (CCI) and Cumulative Illness Rating Scale (CIRS) scores emerged as reliable tools in trials with patients (pts) receiving CIT. Ibrutinib changed CLL treatment paradigm. Nevertheless, adverse events leading to dose reductions and discontinuations are frequent in everyday practice. Finally, it is still unclear whether age, ECOG and comorbidities retain a predictive value with ibrutinib and if number and types of concomitant medications may interfere with treatment outcome. Methods This multicenter retrospective analysis evaluated 712 pts in 15 Italian centers treated with ibrutinib from March 2014 to May 2020. We analyzed the impact of age (<65y, vs ≥ 65y) , CIRS (≤6 vs >6), major CIRS comorbidity (at least one organ with a CIRS score ≥3, CIRS3+), ECOG (0-1 vs >1) and CCI (<2 vs ≥2) in definitive treatment discontinuation due to toxicity (tox-DTD); permanent dose reduction (PDR); EFS (definitive treatment discontinuation for any reason, progression, death); PFS and OS. Medical conditions that were deemed to be CLL complications and CLL diagnosis, were not included in CIRS calculation. Survival functions for the time-to-event variables were estimated by Kaplan-Meier method and related strata compared using the log-rank test. Multivariate analyses were also performed using the Cox regression. Results Table 1 shows pts characteristics. Median follow-up was 26.6 months (range 3 - 75.8); median months on ibrutinib, 21.2 (range 3 - 75.4). Overall, 440 (61.8%) pts are continuing treatment. A total of 272 pts (38.2%) permanently discontinued ibrutinib: 128 (18%) due to toxicity; 132 (18.5%) due to progressive disease/Richter Transformation; 13 (1.8%) for other reasons. Of 712 pts, 325 (45.6%) discontinued treatment for ≥7 days with a median of 15 days/pts interruption. At least one dose reduction occurred in 219 pts (30.8%) and in 123 (17.3%) ibrutinib was permanently administered at a lower dosage. Toxicity was the main reason for PDR (175 pts). Concomitant medications were recorded in 624 (87.6%) pts, 374 of whom took ≥4 drugs in addition to ibrutinib. In 75 cases ibrutinib was concomitant with CYP3A4 inhibitors/inducers. At univariate analysis age ≥ 65y, CIRS>6, CIRS3+, ECOG >1 and CCI ≥2, showed to be significant for tox-DTD. All parameters except age ≥ 65y had an impact on PDR. ECOG >1 was the only parameter affecting PFS, EFS and OS (p<.0001), while CIRS>6 negatively influenced PFS and EFS but not OS. In pts stratification according to age, only in the elderly CIRS >6 was significant for tox-DTD (p 0.009), PDR (p<.0001), PFS (p 0.022) and EFS (p .0002). CIRS3+ instead, was associated to tox-DTD and PDR both in the younger (p .0002 and p .0182, respectively) and older population (p .0128 and p 0.011, respectively). While CIRS3+ did not influence outcome in the younger, it determined a shorter EFS in the elderly. At the Cox regression analysis, ECOG >1 and CIRS>6 were the only fitness-related parameters affecting both PFS and EFS; the influence of ECOG was significant for tox-DTD and OS also (Table 2). CCI ≥2 had an impact on PDR only. Baseline neutropenia also influenced pts tox-DTD and all survival outcomes. Treatment with CYP3A4 inhibitors/inducers was independently associated with higher PDR. Pts outcome in terms of EFS, PFS and OS was also significantly dependent on number of previous lines of treatment (0 vs 1-2 vs ≥3) and presence of del17p/TP53 mutation (not shown in table 2). Ibrutinib PDR did not affect PFS and OS, while OS was significantly reduced in pts definitively discontinuing treatment due to toxicity (p <.0001). Conclusions To our knowledge this is the largest series analyzing the role of age, comorbidities and concomitant medications in pts treated with ibrutinib. In univariate analysis the incidence of tox-DTD and PDR was significantly higher in pts with CIRS3+ and in elderly pts with CIRS>6. ECOG>1 significantly affected pts outcome. Furthermore, CIRS>6 was associated with shorter EFS and PFS in elderly. In the Cox regression hazards model ECOG and CIRS>6 were the only fitness-related factors influencing outcome. Baseline neutropenia also emerged as a parameter significantly affecting both treatment management and survival outcomes. Disclosures Tedeschi: Abbvie: Honoraria, Speakers Bureau; Acerta: Honoraria, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Beigene: Honoraria, Speakers Bureau; Sunesis: Honoraria, Speakers Bureau. Coscia:Karyopharm Therapeutics: Research Funding; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; Shire: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Ciolli:Abbvie: Research Funding; Janssen: Honoraria. Reda:Abbvie: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees. Laurenti:Janssen: Honoraria; Gilead: Honoraria; AbbVie: Honoraria; Roche: Honoraria. Varettoni:Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel/accommodations/expenses; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Other: Travel/accommodations/expenses. Murru:Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Sportoletti:AbbVie: Honoraria; Janssen: Honoraria. Vitale:Janssen: Honoraria. Di Raimondo:Takeda: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Amgen, Takeda, Novartis: Honoraria; GILEAD, Incyte: Research Funding. Montillo:F. Hoffmann-La Roche: Honoraria, Research Funding; AbbVie: Honoraria, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Astra Zeneca: Honoraria; Gilead: Honoraria, Speakers Bureau; Verastem: Honoraria.
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Mease, P. J., A. Deodhar, P. Rahman, H. Marzo-Ortega, V. Strand, T. Hunter, D. Adams, et al. "FRI0286 IXEKIZUMAB TREATMENT IMPROVES FATIGUE, SPINAL PAIN, STIFFNESS, AND SLEEP IN PATIENTS WITH NON-RADIOGRAPHIC AXIAL SPONDYLOARTHRITIS." Annals of the Rheumatic Diseases 79, Suppl 1 (June 2020): 731–32. http://dx.doi.org/10.1136/annrheumdis-2020-eular.1969.
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Background:Common symptoms of axial spondyloarthritis (axSpA) include fatigue, spinal pain, stiffness, and sleep problems, which can impair health-related quality of life. Ixekizumab (IXE) treatment shows efficacy in active non-radiographic axSpA (nr-axSpA).1Objectives:To assess fatigue, spinal pain, stiffness, and sleep with IXE treatment versus (vs) placebo (PBO) in patients (pts) with active nr-axSpA up to 16 and 52 weeks (wks).Methods:In COAST-X, pts with active nr-axSpA were randomized to 52 wks of double-blind IXE 80 mg once every 4 wks (Q4W) or 2 wks (Q2W), or PBO. Data were collected from baseline to Wk 52.Results:At Wk 16, IXE Q4W significantly improved fatigue, spinal pain, and stiffness, and IXE Q2W improved spinal pain, spinal pain at night, and stiffness vs PBO (Table). At Wk 52, IXE Q4W significantly improved stiffness, and IXE Q2W improved spinal pain, spinal pain at night, and stiffness vs PBO. Numeric improvements in sleep were not significant vs PBO. Wk 1, and up to Wk 16, IXE Q4W and Q2W significantly reduced spinal pain and stiffness vs PBO; stiffness was significantly reduced vs PBO up to Wk 52 (Figure).Least squares mean (standard error) change from BL-ITT population (mixed-effect model of repeated measures)MeasureTimepointPBO N=105IXE Q4W N=96IXE Q2W N=102Spinal painaWk 16-1.45 (0.244)-2.35 (0.248)*-2.59 (0.244)†Wk 52-2.29 (0.350)-2.92 (0.305)-3.32 (0.304)*Spinal pain at nightaWk 16-1.71 (0.262)-2.43 (0.267)-2.79 (0.263)*Wk 52-2.25 (0.358)-3.04 (0.312)-3.58 (0.311)*BASDAI-stiffnessb,cWk 16-1.44 (0.242)-2.44 (0.246)*-2.89 (0.242)†Wk 52-1.94 (0.332)-3.15 (0.290)*-3.48 (0.289)†Fatigue severity NRSdWk 16-1.4 (0.24)-2.1 (0.24)*-1.9 (0.24)Wk 52-2.1 (0.38)-2.6 (0.32)-2.7 (0.32)Sleep disturbanceeWk 16-2.3 (0.45)-2.0 (0.45)-2.5 (0.45)Wk 52-2.9 (0.63)-3.6 (0.52)-3.6 (0.53)Pt Global Assessment of Disease ActivityfWk 16-1.30 (0.246)-2.32 (0.251)*-2.64 (0.247)†Wk 52-1.81 (0.378)-2.77 (0.320)-3.30 (0.321)**P<.05 vs PBO;†P≤.001 vs PBO. ITT population: all randomized pts. Pts needing rescue treatment after Wk 16 per investigator could switch to open-label IXE Q2W; observations at visits thereafter not included in analyses. BL values similar across treatments. Numerical improvements in BASDAI-fatigue not significant vs PBO.aScored 0 (no pain) to 10 (most severe pain) on NRSbMean score BASDAI questions 5 (intensity) and 6 (duration)cScored 1–10 on NRSdScored 0 (no fatigue) to 10 (as bad as you can imagine)eJenkins Sleep Evaluation Questionnaire scored 0 to 20: each of 4 items scored 0 (0 days) to 5 (22–30 days)fScored 0 (not active) to 10 (very active) on NRSBASDAI=Bath Ankylosing Spondylitis Disease Activity IndexBL=baselineITT=intent-to-treatIXE=ixekizumabN=number of pts in ITT populationNRS= numeric rating scalePBO=placebopt=patientQ2W=every 2 wksQ4W=every 4 wksvs=versuswk=weekConclusion:IXE Q4W and/or Q2W significantly improved spinal pain, spinal pain at night, and stiffness vs PBO at 16 and 52 wks in pts with nr-axSpA. IXE Q4W also improved fatigue at 16 wks in these pts. Numerical improvements in sleep were not significant vs PBO.References:[1]Deodhar A, et al. Lancet. 2019Disclosure of Interests:Philip J Mease Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Janssen, Eli Lilly, Novartis, Pfizer, Sun Pharma, UCB Pharma, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Janssen, Eli Lilly, Galapagos, Gilead, Novartis, Pfizer, Sun Pharma, UCB Pharma, Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Genentech, Janssen, Novartis, Pfizer, UCB Pharma, Atul Deodhar Grant/research support from: AbbVie, Eli Lilly, GSK, Novartis, Pfizer, UCB, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myer Squibb (BMS), Eli Lilly, GSK, Janssen, Novartis, Pfizer, UCB, Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myer Squibb (BMS), Eli Lilly, GSK, Janssen, Novartis, Pfizer, UCB, Proton Rahman Grant/research support from: Janssen and Novartis, Consultant of: Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, and Pfizer., Speakers bureau: Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, Pfizer, Helena Marzo-Ortega Grant/research support from: Janssen, Novartis, Consultant of: Abbvie, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, UCB, Speakers bureau: Abbvie, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Takeda, UCB, Vibeke Strand Consultant of: AbbVie, Amgen, Biogen, Celltrion, Consortium of Rheumatology Researchers of North America, Crescendo Bioscience, Eli Lilly, Genentech/Roche, GlaxoSmithKline, Hospira, Janssen, Merck, Novartis, Pfizer, Regeneron Pharmaceuticals, Inc., Sanofi, UCB, Theresa Hunter Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, David Adams Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, David Sandoval Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Andris Kronbergs Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Baojin Zhu Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Ann Leung: None declared, Soyi Liu Leage Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Victoria Navarro-Compán Consultant of: Abbvie, Lilly, Novartis, Pfizer, UCB, Speakers bureau: AbbVie, MSD, Lilly, Novartis, Pfizer, UCB
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Mohty, Mohamad, Evangelos Terpos, Maria-Victoria Mateos, Antonio Palumbo, Sandra Lejniece, Meral Beksac, Mohamed Amine Bekadja, et al. "Analysis of Final Data from the Multinational, Non-Interventional, Observational Emmos Study (NCT01241396) in Patients (Pts) with Multiple Myeloma (MM) in Real-World Clinical Practice." Blood 126, no. 23 (December 3, 2015): 3034. http://dx.doi.org/10.1182/blood.v126.23.3034.3034.
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Abstract Background A lack of objective data exists on differences in treatment practices and outcomes for MM between countries. The EMMOS study aimed to document and describe current treatment regimens and disease progression patterns of MM pts at different stages of the disease in real-world medical practice. Methods Adult pts initiating any new MM therapy, irrespective of treatment line at study entry or therapy type received, were eligible for inclusion in the EMMOS registry. A multi-staged pt/site recruitment model was applied to minimize selection bias; enrollment was stratified by country, region, and practice type. Pts' medical/disease features, treatment history, and remission status were recorded at baseline. Prospective data on treatment, efficacy, and safety were collected electronically every 3 mos until 2 yrs after the last pt enrolled. Responses were investigator-assessed (no predefined criteria). Here we report data from the final analysis of EMMOS. Pts were grouped according to receipt of high-dose chemotherapy/stem cell transplantation in any treatment line (SCT pts, non-SCT pts). Within a given line, pts may have received induction, SCT, consolidation, and/or maintenance therapy; if multiple drug combinations were used within a line, the line grouping was based on the combination received in cycle 1. Results 2358 pts were enrolled between Oct 2010-Oct 2012 in 22 countries in Europe and Africa; the last pt completed follow-up in Oct 2014. Of these, 775 pts had undergone SCT in any treatment line. Baseline characteristics in the prospective phase by starting line are shown in the Table. As expected, there was a higher proportion of younger pts (≤65 yrs) in the SCT vs non-SCT group across all treatment lines, and in both groups a higher proportion of pts in 4th + vs earlier lines with ISS stage III disease. While cytogenetics were evaluated in a small number of pts overall (670/2358 [28%]), these assessments were performed significantly more frequently in SCT vs non-SCT pts (p<0.0001). In 380 prospective 1st line (L1) SCT pts, 299 (79%) underwent SCT-based treatment in L1; induction was with a bortezomib (btz)-based combination in 83% (47% btz without immunomodulatory drug [IMiD]; 36% btz + IMiD), IMiD in 11%, and other (ie. no btz/IMiD) in 6%. In 81 SCT pts who received non-SCT-based treatment in L1 (21%), 36% received btz without IMiD, 40% other, and 17% IMiD-based combinations. In 345 pts receiving L2, most frequent therapies were btz without IMiD (45% of pts), IMiD without btz (30%), other (13%), and btz + IMiD (12%); non-btz/IMiD combinations were increasingly prevalent in pts receiving L3 or L4 (24% and 40%, respectively). In the non-SCT population, 58% of pts received a btz-based combination in L1, most frequently btz without IMiDs (54%). In pts receiving L2, btz or IMID were equally represented (39%); in L3, non-SCT pts were most likely to receive other therapies (39%) versus 27% btz without IMiD and 32% IMiD without btz. Based on preliminary data, mean EQ5D score at baseline was 0.316 (range -0.594, 0.731) in the overall pt population, which increased slightly to 0.410 (-0.429, 0.731) at 12 mos and was largely comparable between countries. Resource utilization (hospitalization, ICU, ER visit, outpatient visit, full-time care) appeared highest in Germany (67.6 records per pt) and lowest in Croatia (7.5 per pt), with those in Germany spending a mean of 12.1 days in hospital per stay. Efficacy/safety data will be presented at the meeting. Conclusion This large, real-world, observational study provides for the first time a comprehensive picture of the baseline characteristics and therapy of MM pts treated in Europe, the Middle-East, and Africa. These data provide a framework towards the design of future protocols aiming to improve outcomes in MM. Table. Baseline characteristics by starting line Non-SCT pts SCT pts L1 (n=897) L2 (n=319) L3 (n=184) L4+ (n=166) Total* (N=1566) L1 (n=378) L2 (n=161) L3 (n=107) L4+ (n=120) Total* (N=775) Age ≤65 yrs, % 36 34 35 39 36 87 76 72 71 80 ISS Stage II/III, % 36/44 34/47 43/38 22/52 35/44 33/35 44/27 34/26 23/48 34/34 Salmon-Durie Stage 2/3, % 28/64 25/66 24/71 29/62 27/65 22/68 25/67 20/65 11/81 20/69 Bone lesion history, % 64 72 75 70 68 66 74 77 80 71 Cytogenetics assessed, % 24 19 19 14 21 51 35 43 33 44 Del 17p 8 8 9 13 8 10 7 4 13 9 t(4,14) 6 7 9 4 6 7 14 13 8 9 ISS, International staging system; L, line *17 non-SCT and 9 SCT pts were enrolled but did not receive a line of therapy within 75 days of baseline Disclosures Mohty: Celgene: Honoraria; Janssen: Honoraria. Terpos:Amgen: Honoraria, Research Funding; Janssen: Honoraria; Celgene: Honoraria; Novartis: Honoraria. Mateos:Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees. Palumbo:Array BioPharma: Consultancy; Onyx Pharmaceuticals: Consultancy; Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Consultancy, Honoraria; Janssen-Cilag: Consultancy, Honoraria; Genmab A/S: Consultancy; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy; Sanofi Aventis: Consultancy. Lejniece:Amgen: Honoraria; Sandoz: Honoraria. Beksac:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen-Cilag: Speakers Bureau; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Speakers Bureau; Amgen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Dimopoulos:Novartis: Honoraria; Janssen: Honoraria; Amgen: Honoraria; Onyx: Honoraria; Celgene: Honoraria; Genesis Pharma: Research Funding. De Stefano:Shire: Speakers Bureau; Roche: Research Funding; Bruno Farmaceutici: Research Funding; Janssen Cilag: Research Funding; Amgen: Speakers Bureau; GlaxoSmithKline: Speakers Bureau; Novartis: Research Funding, Speakers Bureau; Celgene: Speakers Bureau. Salwender:Celgene: Honoraria; Janssen Cilag: Honoraria; Bristol Meyer Sqibb: Honoraria; Amgen: Honoraria; Novartis: Honoraria. Pečeliūnas:Johnson & Johnson: Honoraria, Research Funding. Willenbacher:CTI: Consultancy, Other: Travel, Accommodations, Expenses; Gilead: Consultancy, Other: Travel, Accommodations, Expenses, Speakers Bureau; Amgen: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding; Janssen: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding; Roche: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding; Celgene: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses, Research Funding; Novartis: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses, Research Funding. Da Silva:Janssen Pharmaceuticals: Research Funding. Louw:Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Nemet:Sanofi: Honoraria; Pliva: Honoraria; Pfizer: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Celgene: Honoraria. Potamianou:Janssen: Employment. Couturier:Janssen-Cilag: Employment. Olie:Johnson & Johnson: Equity Ownership; Janssen-Cilag: Employment. Feys:Janssen Pharmaceutica N.V.: Employment, Equity Ownership. Thoret-Bauchet:Janssen-Cilag: Employment.
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McBride, Ali, Karen MacDonald, and Ivo Abraham. "Simulation Modeling of Cost-Savings from Conversion to Biosimilar Pegfilgrastim-Cbqv for the Prophylaxis of Chemotherapy-Induced Neutropenia, and Budget-Neutral Expanded Access to Prophylaxis and Anti-Neoplastic Therapy from Derived Cost-Savings in Non-Hodgkin Lymphoma." Blood 136, Supplement 1 (November 5, 2020): 24–25. http://dx.doi.org/10.1182/blood-2020-136810.
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Introduction: Costs of prophylaxis of chemotherapy-induced (febrile) neutropenia (CIN/FN) have been reduced in recent years by the approval of several biosimilar filgrastim and pegfilgrastim agents. The savings from conversion to biosimilars can be reallocated to provide expanded access to CIN/FN prophylaxis or anti-neoplastic treatment. To illustrate this, we simulated in a panel of 20,000 non-Hodgkin lymphoma (NHL) patients: 1) the savings that could be realized from CIN/FN prophylaxis with biosimilar pegfilgrastim-cbqv over reference pegfilgrastim with or without on-body injector (PEG/PEG-OBI), 2) a model of expanded access to CIN/FN prophylaxis with biosimilar pegfilgrastim-cbqv from cost-savings achieved from conversion from PEG/PEG-OBI, and 3) a model of expanded access to chemotherapy with cyclophosphamide, doxorubicin, vincristine, and prednisone plus rituximab (R-CHOP) for NHL from cost-savings achieved from conversion from PEG/PEG-OBI. Methods: Simulation modeling for a panel of 20,000 NHL patients was conducted from the US payer perspective. Medication costs for PEG/PEG-OBI, pegfilgrastim-cbqv, and R-CHOP drugs were calculated in three ways 1) Q1 2020 average selling price (ASP) derived from CMS Q3 2020 reimbursement limits, 2) Wholesale Acquisition Cost (WAC) from Redbook, and 3) a blended ASP/WAC rate proportionate to the NHL age distribution per Surveillance, Epidemiology, and End Results Program data. These three cost estimate bases were applied to one through six cycles of prophylaxis with conversion rates from PEG/PEG-OBI to biosimilar pegfilgrastim-cbqv ranging from 10% to 100%. The number-needed-to-convert (NNC) to biosimilar pegfilgrastim-cbqv from PEG/PEG-OBI to purchase one additional treatment of pegfilgrastim-cbqv or one additional cycle of R-CHOP chemotherapy was also estimated. Results: Using ASP, cost-savings of biosimilar pegfilgrastim-cbqv over PEG/PEG-OBI in a panel of 20,000 NHL patients ranged from $371,444 (for 1 cycle of prophylaxis at 10% conversion) to $22,286,640 (6 cycles at 100% conversion). The corresponding savings ranged from $4,112,120 to $246,727,200 when using WAC; and from $1,976,194 to $118,571,640 when using the age-proportionate blended ASP/WAC rate. Focusing on the blended ASP/WAC rate, the savings in a single cycle of chemotherapy translated into expanded access to biosimilar pegfilgrastim-cbqv ranging from 524 cycles at 10% conversion from PEG/PEG-OBI to 5,243 cycles at 100% conversion. The savings over six cycles of biosimilar prophylaxis could provide between 3,146 (at 10% conversion) and 31,457 (at 100% conversion) additional cycles of biosimilar pegfilgrastim-cbqv. The NNC from one cycle of PEG/PEG-OBI to biosimilar pegfilgrastim-cbqv to purchase one additional cycle of biosimilar pegfilgrastim-cbqv is 4. In a single cycle of chemotherapy, savings using the blended ASP/WAC rate translated into expanded access to R-CHOP ranging from 282 cycles at 10% to 2,817 cycles at 100% conversion. The savings over six cycles of biosimilar prophylaxis could provide between 1,690 (at 10% conversion) and 16,900 cycles (at 100% conversion) additional cycles of R-CHOP. The NNC from one cycle of PEG/PEG-OBI to biosimilar pegfilgrastim-cbqv to purchase one additional cycle of R-CHOP is 8. Conclusions: These simulation models demonstrate that significant cost savings for supportive cancer care can be generated through conversion to biosimilar pegfilgrastim-cbqv for CIN/FN prophylaxis. The savings generated from conversion from PEG/PEG-OBI can be reallocated on a budget-neural basis to provide expanded access to additional patients/cycles of CIN/FN prophylaxis with biosimilar pegfilgrastim-cbqv or to curative anti-neoplastic treatment. Such efficiency and expanded access enhance the value of cancer care to payers and patients. Disclosures McBride: MorphoSys: Consultancy; Sandoz: Consultancy; Pfizer: Consultancy; Merck: Speakers Bureau; Coherus BioSciences: Consultancy, Speakers Bureau; Bristol-Myers Squibb: Consultancy. MacDonald:Sandoz: Consultancy; MorphoSys: Consultancy; Celgene: Consultancy; Terumo: Consultancy; Rockwell Medical: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Mylan: Consultancy; Coherus BioSciences: Research Funding. Abraham:MorphoSys: Consultancy; Sandoz: Consultancy; Mylan: Consultancy; Janssen: Consultancy; Rockwell Medical: Consultancy; Terumo: Consultancy; Celgene: Consultancy; Coherus BioSciences: Research Funding, Speakers Bureau.
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Boyle, Eileen M., Faith E. Davies, Shayu Deshpande, Ruslana G. Tytarenko, Cody Ashby, Yan Wang, Christopher P. Wardell, et al. "Analysis of the Sub-Clonal Structure of Smoldering Myeloma over Time Provides a New Means of Disease Monitoring and Highlights Evolutionary Trajectories Leading to Myeloma." Blood 134, Supplement_1 (November 13, 2019): 4333. http://dx.doi.org/10.1182/blood-2019-126679.
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Background: Smoldering myeloma (SMM) is an asymptomatic plasma cell disorder, distinguished from monoclonal gammopathy of undetermined significance (MGUS) by a higher risk of progression to symptomatic multiple myeloma (MM). Studying the genetic makeup and sub-clonal architecture of bone marrow samples taken from the same case sequentially over time is an innovative strategy to define the evolutionary trajectory underlying myeloma initiation and progression through SMM to MM and may provide new strategies to identify progression and to intervene therapeutically before end organ damage develops. Methods: Sequential samples from 9 SMM patients (53 samples) with a median follow-up of 7 years (range: 3.5 to 12.8 years) were analyzed. DNA was obtained from CD138+ cells from the bone marrow of SMM patients. 100 ng of DNA was fragmented, end-repaired, and adapters ligated, before hybridization using MedExomePlus (Nimblegen) with an additional capture for the IGH, IGK, IGL, and MYC loci. After PCR amplification hybridized libraries were sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads. The median coverage was 93x (IQR 86-105) and 100x (IQR 95-103) for tumors and controls, respectively. Variant, translocations, and copynumber changes were called using Variant Effect Predictor (v.85), Manta (v0.29.6), and Sequenza respectively. Sub clonal architecture was determined using the Pyclone package and nNMF performed using the NMF package in R. Results: The median number of mutations per sample was 79 (range: 34-236) and increased with time from diagnosis with a trend suggesting that the mutation rate of progressors (n=6) was higher than of the non-progressors (F=3.9, p=0.052). Samples with hyperdiploidy had a higher mutational rate than other subgroups (F=9, p=0.009) in relation to higher DNA contents. We previously defined a set of 63 genes that drive myeloma; 7/9 patients had a mutation in one of these genes, independently from progression status. Four patients had more than one driver mutation, which were in different clones in two patients and in the same clone in two patients. The acquisition of bi-allelic inactivation of myeloma drivers immediately before progression was seen in genes such as DIS3 and TRAF3 indicating a role in progression to an active disease state. Translocations were detected in six patients from the initial time point. In one case, a t(8;14) was detected during follow-up, 5.9 years from diagnosis. Quantification of the rearranged MYC allele compared to the IGH rearranged locus was performed by ddPCR. This t(8;14) was not present at diagnosis, appeared in a small fraction (1%) 4.1 years after diagnosis and steadily increased over time reaching 45% in the last sample, 8.9 years from the initial diagnosis indicating growing dominance of a potentially progressive clone. It was possible to reconstruct the sub-clonal structure and how it varied overtime for eight patients. This analysis identified a median number of seven sub-clones per patient, most of them related via branching evolutionary patterns (7/8). In one case a linear pattern was identified. Ninety-five percent of the tumor contents was occupied by five clones in 6/8 cases, and six in 2/8 cases. The median number of minor clone (<10% of tumor content) at diagnosis was estimated to be 3 (range: 1-5). In 7/8 patients a minor clone increased to more than at least 15% of tumor content and in 5/8 patients at least 20%. All patients that had more than 2 minor clones that increased to more than 15% progressed or had progressed (4/8). The only patient that progressed and did not display these clonal changes progressed within 4 months from the initial SMM sample, suggesting the clonal sweep had already occurred. Significant changes in sub-clonal structures were also seen in all samples at least one year prior to progression. Conclusion: A comprehensive analysis of multiple SMM samples over time offers new insight into the mechanisms of progression of SMM to MM including the role of events we have identified previously associated with relapse e.g. MYC translocations, clonal sweeps, and biallelic deletions and changes in the clonal architecture. Changes in sub-clonal structure occurred before progression providing a new tool to monitor SMM. Disclosures Boyle: Amgen, Abbvie, Janssen, Takeda, Celgene Corporation: Honoraria; Amgen, Janssen, Takeda, Celgene Corporation: Other: Travel expenses. Davies:Janssen, Celgene: Other: Research Grant, Research Funding; Amgen, Celgene, Janssen, Oncopeptides, Roche, Takeda: Membership on an entity's Board of Directors or advisory committees, Other: Consultant/Advisor. van Rhee:Takeda: Consultancy; Sanofi Genzyme: Consultancy; Castleman Disease Collaborative Network: Consultancy; EUSA: Consultancy; Adicet Bio: Consultancy; Kite Pharma: Consultancy; Karyopharm Therapeutics: Consultancy. Facon:Sanofi: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Membership on an entity's Board of Directors or advisory committees. Morgan:Amgen, Janssen, Takeda, Celgene Corporation: Other: Travel expenses; Bristol-Myers Squibb, Celgene Corporation, Takeda: Consultancy, Honoraria; Celgene Corporation, Janssen: Research Funding. Walker:Celgene: Research Funding.
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Khorana, Alok A., Frank Peacock, Sally G. Tamayo, Zhong Yuan, Nicholas Sicignano, Kathleen Hopf, and Manesh Patel. "Major Bleeding Events Among Cancer and Non-Cancer Patients Taking Rivaroxaban for Venous Thromboembolism Treatment in a Department of Defense Health System Cohort." Blood 128, no. 22 (December 2, 2016): 1447. http://dx.doi.org/10.1182/blood.v128.22.1447.1447.
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Abstract Background: Cancer patients are at increased risk of both venous thromboembolism (VTE) and bleeding, but real world bleeding rates with contemporary anticoagulants are not known. Purpose: To describe the incidence of major bleeding (MB) in VTE patients treated with rivaroxaban, and to compare differences in MB incidence and characteristics among patients with active cancer, history of cancer, and no current or past cancer. Methods: We queried over 10 million electronic medical records (EMRs) from the United States Department of Defense healthcare system from November 2, 2012 to September 30, 2015 to identify MB events in VTE patients treated with rivaroxaban. The Cunningham algorithm was used for identifying MB, and VTE was determined by diagnosis codes. Presence of cancer was assessed from 5 years prior to index rivaroxaban exposure through end of study, and categorized by active cancer, history of cancer, and no cancer. Active cancer was defined by one of the following: 1) a metastatic diagnosis code within 6 months prior to or overlapping with rivaroxaban exposure, 2) chemotherapy and/or radiation codes within 6 months prior to rivaroxaban exposure, 3) cancer-related surgery overlapping with rivaroxaban exposure, or 4) leukemia and/or indolent lymphoma codes at any point within the entire assessment window. History of cancer was defined as the presence of any cancer diagnosis within the 5-year baseline period not meeting the definition of active cancer. Patients with active cancer or history of cancer were further categorized by cancer site/type. Incidence, outcomes, demographics, and bleeding risk scores were evaluated by cancer status. A Cox proportional hazard model was used to assess the association between cancer status and rate of MB adjusting for baseline characteristics. Results: The study population comprised 9,638 VTE patients on rivaroxaban, including 1,728 (17.9%) with active cancer, 1,548 (16.1%) with history of cancer and 6,362 (66.0%) with no cancer. Of these, 130 (1.3%) experienced MB. After stratifying by cancer status, MB occurred at a rate of 2.61 (95% CI 1.80-3.78) per 100 person-years in those with active cancer, 3.18 (95% CI 2.17-4.67) per 100 person-years in those with history of cancer, and 2.25 (95% CI 1.80-2.81) per 100 person-years in those with no cancer. No significant difference in the incidence of MB was found between those with cancer (active or history) and those without cancer (HR 1.01; 95% CI 0.70-1.47, p-value 0.94) after adjusting for age, sex, and baseline comorbidities. Neither history of cancer nor active cancer when independently compared to no cancer was significantly associated with MB after multivariate adjustment. MB rates varied notably by cancer site. Additional key findings are presented in Table 1. Conclusion: In this large United States Department of Defense cohort study of rivaroxaban users treated for VTE, incidence of MB is relatively low and not significantly different between cancer and non-cancer patients. Fatal outcomes associated with bleeding hospitalization were also uncommon across all the cancer groups. These data should provide assurance to oncology providers regarding the safety of rivaroxaban use in the real-world setting. Disclosures Khorana: Pfizer: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Leo: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria; Bayer: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Halozyme: Consultancy, Honoraria; Janssen Scientific Affairs, LLC: Consultancy, Honoraria, Research Funding. Peacock:Phillips: Consultancy; Comprehensive Research Associates LLC: Equity Ownership; Pfizer: Research Funding; Banyan: Research Funding; Cardiorentis: Consultancy, Research Funding; Portola: Consultancy, Research Funding; Abbott: Research Funding; Emergencies in Medicine LLC: Equity Ownership; Ischemia Care: Consultancy; Janssen: Consultancy, Research Funding; Alere: Consultancy, Research Funding; Roche: Research Funding; The Medicine's Company: Consultancy, Research Funding; ZS Pharma: Consultancy, Research Funding; Prevencio: Consultancy. Yuan:Janssen Research and Development: Employment; Johnson & Johnson: Other: Mr. Yuan owns stocks in Johnson & Johnson.. Sicignano:Janssen Research and Development: Other: NMS is an employee of Health ResearchTx LLC, which has a business relationship with Janssen.. Hopf:Janssen Research and Development: Other: KPH is an independent contractor for Health ResearchTx LLC, which has a business relationship with Janssen . Patel:National Heart Lung and Blood Institute: Research Funding; Janssen: Consultancy; Bayer: Consultancy; Otsuka: Consultancy; Johnson & Johnson: Consultancy; AstraZeneca: Consultancy, Research Funding; Heart Flow Technologies: Research Funding; Agency for Healthcare Research and Quality: Research Funding.
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Weits, G., L. Kosse, H. Vonkeman, P. Spuls, B. Van den Bemt, S. Tas, F. Hoentjen, et al. "OP0268-HPR RHEUMATIC DISEASE PATIENTS’ PREFERENCES IN ADVERSE DRUG REACTION INFORMATION REGARDING BIOLOGICS." Annals of the Rheumatic Diseases 79, Suppl 1 (June 2020): 167.2–168. http://dx.doi.org/10.1136/annrheumdis-2020-eular.1841.
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Background:Patient-reported outcomes (PROs) are increasingly used in studies and medical practice to obtain information on patients’ perspectives towards their treatment or disease. However, study outcomes are primarily directed at and shared with healthcare professionals, even though the results may also be relevant for patients.Objectives:The objective of this study was to obtain insight in which results patients with immune-mediated inflammatory diseases (IMIDs), including inflammatory rheumatic disease patients, prefer to receive after participating in the Dutch Biologic Monitor.Methods:The Dutch Biologic Monitor is a PRO-based prospective cohort event monitoring study focused on adverse drug reactions (ADRs) [1]. A survey was conducted among the participants of the Dutch Biologic Monitor who wanted to be informed about the results. Patients’ preferences were identified using twelve statements and rated with five-point Likert-type scales. Averages described the preference per statement. Preference for the results per IMID or altogether was assessed using Mann-Whitney U Test.Results:Respondents (N=591, response rate 67.6%) preferred results per IMID over aggregated results (p=<0.001). Information on whether patients with the same IMID experience ADRs (average 4.5), which biologics are most likely to cause ADRs (4.4) and whether the ADRs subside or disappear (4.4) were regarded as most interesting. Outcomes of patients with other IMIDs (3.5), patient characteristics (3.7) and injection site reactions (3.8) were least interesting.Table 1.Respondent characteristics.CharacteristicsAllInflammatory rheumatic disease patients(n=591)(%)(n=453)(%)Female gender,n(%)353(59.7)286(63.1)Age, median (IQR), years59.0(51.0-67.0)60.0(51.0-67.5)BiologicsAdalimumab220(37.2)164(36.2)Etanercept196(33.2)189(41.7)Infliximab43(7.3)8(1.8)Tocilizumab21(3.6)17(3.8)Ustekinumab21(3.6)7(1.5)Other90(15.2)68(15.0)Combination therapyMethotrexate195(33.0)183(40.4)Corticosteroids65(11.0)51(11.3)Thiopurines41(6.9)10(2.2)No combination therapy231(39.1)157(34.7)Other123(20.8)106(23.4)Indications for biologic therapyRheumatoid arthritis277(46.9)277(61.1)Psoriatic arthritis111(18.8)111(24.5)Ankylosing spondylitis/axSpA83(14.0)83(18.3)Other159(26.9)17(3.8)IQR: interquartile range; axSpA: axial spondyloarthritis.Figure 1.The preferences of patients on the communication of the reported adverse drug reaction information resulting from the Dutch Biologic Monitor.Conclusion:Participants of the Dutch Biologic Monitor that use a biologic for their IMID prefer to receive ADR information tailored to their own biologic and IMID. Furthermore, they want to obtain insight in the course of ADRs. Therefore, we advocate to generate disease-specific information on ADRs for IMID patients.References:[1]Kosse LJ, Jessurun NT, Hebing RCF, Huiskes VJB, Spijkers KM, van den Bemt BJF, et al. Patients with inflammatory rheumatic diseases: quality of self-reported medical information in a prospective cohort event monitoring system.Rheumatol.published on 30 Sept 2019. doi: 10.1093/rheumatology/kez412.Disclosure of Interests:Gerda Weits: None declared, Leanne Kosse: None declared, Harald Vonkeman: None declared, Phyllis Spuls Grant/research support from: Departmental independent research grant for TREAT NL registry LeoPharma December 2019; Contract support: I am involved in performing clinical trials with many pharmaceutical industries that manufacture drugs used for the treatment of e.g. psoriasis and atopic dermatitis for which we get financial compensation paid to the department/hospital, Consultant of: Consultancies in the past for Sanofi 111017 and AbbVie 041217 (unpaid), Bart van den Bemt Grant/research support from: UCB, Pfizer and Abbvie, Consultant of: Delivered consultancy work for UCB, Novartis and Pfizer, Speakers bureau: Pfizer, AbbVie, UCB, Biogen and Sandoz., Sander Tas: None declared, Frank Hoentjen Grant/research support from: Received grants from Dr Falk, Janssen-Cilag, and AbbVie., Consultant of: Served on advisory boards, or as speaker or consultant for AbbVie, Celgene, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz, and Dr Falk, Speakers bureau: Served on advisory boards, or as speaker or consultant for AbbVie, Celgene, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz, and Dr Falk, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research, Martijn van Doorn Grant/research support from: Unrestricted grants, advisory board, speaker fees and/or other (investigator) from Novartis, Abbvie, Janssen Cilag, Leopharma and Pfizer, Speakers bureau: Unrestricted grants, advisory board, speaker fees and/or other (investigator) from Novartis, Abbvie, Janssen Cilag, Leopharma and Pfizer, Eugène van Puijenbroek: None declared, Naomi Jessurun: None declared
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Rahman, P., Q. Li, D. Codner, D. O’Rielly, A. Dohey, K. Jenkins, D. D. Gladman, V. Chandran, and I. Jurisica. "POS0406 miRNAs DEREGULATED IN RESPONSE TO IL17A INHIBITORS IN PSORIATIC ARTHRITIS REGULATE GENE PRODUCTS IN Rho-GTPase PATHWAYS." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 432–33. http://dx.doi.org/10.1136/annrheumdis-2021-eular.1434.
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Background:Using transcriptomic data at initiation of therapy, we recently identified differentially expressed genes (DEGs) that separated IL-17Ai response from non-response1. Integration of cell-type-specific DEGs with protein-protein interactions (PPIs) and further comprehensive pathway enrichment analysis revealed Rho GTPase signaling pathway exhibited a strong signal specific to IL-17Ai response and particularly the genes, RAC1 and ROCKs.Objectives:To characterize microRNA (miR) profiles among IL-17Ai responders and non-responders, as it relates to RHO GTPase pathway.Methods:We interrogated 20 psoriatic arthritis (PsA) patients initiating IL-17Ai. Patients achieving at least low disease activity according to the Disease Activity Index for PsA (DAPSA) at three months were classified as responders. There were seven responders (35%) and thirteen non-responders (65%) in the IL-17Ai group, with biologic treatment naïve (bio-naïve) and previously-exposed (bio-exposed) patients exhibiting a 50% (4/8) and a 25% (3/12) response rate, respectively. For the miR analysis, CD4 positive T cells were isolated from peripheral blood mononuclear cells using DynabeadsTM CD4 beads (ThermoFisher). Total RNA was extracted from the CD4+ T cells using Lexogen’s Split RNA Extraction Kit (D-Mark Biosciences). Libraries were prepared from 200ng total RNA with the NEXTFLEX Small RNA-Seq Kit v3 with UDIs (Bioo Scientific) and sequenced on the Illumina NovaSeq 6000. Raw sequencing fastq data assessed the quality using FastQC. The miRDeep2 was used to trim the adapter, align and quantify human mature miRs from miRbase (Release 22). The abundance of miRs was converted to read counts per million, normalized and limma R package was used to identify pre- and post-differentially expressed miRs.Results:We obtained 2,889 miRs. After removing miRs with low reads in >90% of samples, 1902 high quality miRs remained for further analysis. Using mirDIP v4.1 we identified gene targets for differential miRs, and focused on recently identified DEGs related to RHO GTPase pathway. The miRs on the left of the figure 1 are those deregulated in pre-treatment, and the miRs on the right of the figure 1 show the post-treatment deregulated miRs. hsa-miR-3691-5p and hsa-miR-3161 represent the miRs that were deregulated in both conditions. The red highlighted nodes represent the most connected miRs and genes; thus, representing miRs that are the most RHO-pathway centric regulators (hsa-miR-495-3p, 16-5p, 129-5p, 520h, 520g-3p), and genes representing the most strongly regulated RHO-pathway gene products (ROCK1, RHOQ, PFN2, TAOK1, DYNC1L12, MAPRE1, PAFAH1B1, ARHGAP5, MAPK1, CALM1, DIAPH2, PKN2, ITSN1).Conclusion:Pre- and post-treatment differential miRs related to IL-17Ai response regulate multiple genes from RHO GTPase pathway.References:[1]Rahmati S, O’Rielly DD, Li Q, Codner D, Dohey A, Jenkins K, Jurisica I, Gladman DD, Chandran V, Rahman P. Rho-GTPase pathways may differentiate treatment response to TNF-alpha and IL-17A inhibitors in psoriatic arthritis. Sci Rep. 2020 Dec 10;10(1):21703.Figure 1.Disclosure of Interests:Proton Rahman Speakers bureau: AbbVie, Amgen, BMS, Celgene, Eli Lily, Janssen, Merck, Novartis, Pfizer, UCB, Consultant of: AbbVie, Amgen, BMS, Celgene, Eli Lily, Janssen, Merck, Novartis, Pfizer, UCB, Grant/research support from: Janssen, Novartis, Quan Li: None declared, Dianne Codner: None declared, Darren O’Rielly: None declared, Amanda Dohey: None declared, Kari Jenkins: None declared, Dafna D Gladman Speakers bureau: AbbVie, Amgen, BMS, Eli Lily, Galapagos, Gilead, Janssen, Novartis, Pfizer, UCB, Consultant of: AbbVie, Amgen, BMS, Eli Lily, Galapagos, Gilead, Janssen, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Eli Lily, Janssen, Novartis, Pfizer, UCB, Vinod Chandran Speakers bureau: AbbVie, Amgen, BMS, Eli Lily, Janssen, Novartis, Pfizer, UCB, Paid instructor for: AbbVie, Amgen, BMS, Eli Lily, Janssen, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Eli Lily, Employee of: Spousal Employment Eli Lilly, Igor Jurisica: None declared
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Raje, Noopur S., David S. Siegel, Sundar Jagannath, Sagar Lonial, Nikhil C. Munshi, Philippe Moreau, Hartmut Goldschmidt, et al. "Idecabtagene Vicleucel (ide-cel, bb2121) in Relapsed and Refractory Multiple Myeloma: Analyses of High-Risk Subgroups in the KarMMa Study." Blood 136, Supplement 1 (November 5, 2020): 37–38. http://dx.doi.org/10.1182/blood-2020-134319.
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Background: Outcomes remain poor in patients with high-risk relapsed and refractory multiple myeloma (RRMM) receiving conventional treatments, including immunomodulatory drugs (IMiD agents), proteasome inhibitors (PIs), and anti-CD38 antibodies. The pivotal phase 2 KarMMa study (NCT03361748) demonstrated deep and durable responses with idecabtagene vicleucel (ide-cel, bb2121), a BCMA-directed CAR T cell therapy, in triple-class exposed patients with RRMM. The overall response rate (ORR), complete response (CR) rate, median duration of response (DOR), and median progression-free survival (PFS) were 73%, 33%, 10.7 months, and 8.8 months, respectively, across the target dose levels of 150−450 × 106 CAR+ T cells, and 82%, 39%, 11.3 months, and 12.1 months at the highest target dose of 450 × 106 CAR+ T cells (Munshi et al. J Clin Oncol. 2020;38[suppl, abstr]:8503). The most frequent all-grade adverse events were cytopenias (97%) and cytokine release syndrome (84%). Here we report safety and efficacy from the KarMMa study in patient subgroups that are historically difficult to treat. Methods: Patients in KarMMa had received ≥3 prior regimens, including an IMiD agent, a PI, and an anti-CD38 antibody, and were refractory to their last regimen per International Myeloma Working Group (IMWG) criteria. After lymphodepletion with cyclophosphamide (300 mg/m2/day) and fludarabine (30 mg/m2/day) for 3 days followed by 2 days of rest, patients received target doses of 150, 300, or 450 × 106 CAR+ T cells. We performed subgroup analyses in patients stratified by high-risk characteristics, including those with extramedullary disease, high-risk cytogenetics [del(17p), t(4;14), and t(14;16)], high tumor burden (defined as ≥50% bone marrow plasma cells), receipt of bridging therapy, disease stage III at baseline (per the revised International Staging System [R-ISS]), and >1 prior regimen per year. The primary endpoint was ORR. Additional endpoints included CR rate (key secondary), DOR, PFS, and safety. ORR and CR were assessed per IMWG criteria; DOR and PFS were analyzed via Kaplan-Meier methods. Results: Among all 128 ide-cel treated patients, 39% had extramedullary disease, 35% had high-risk cytogenetics, 51% had high tumor burden, 88% received bridging therapy, 16% had R-ISS disease stage III, and 47% had received >1 prior antimyeloma regimen per year. The ORR and CR rate were ≥65% and ≥20%, respectively, across all high-risk subgroups examined except patients with R-ISS disease stage III (Table). Notably, the presence of extramedullary disease and baseline tumor burden did not substantially affect ORR (70% with and 76% without extramedullary disease; 71% with and 77% without high tumor burden). CR rates were 24% in patients with and 39% in patients without extramedullary disease, and 29% in patients with and 37% in patients without high tumor burden. The median DOR was ≥9.1 months and the median PFS was ≥7.5 months in all subgroups examined except in patients with R-ISS stage III (Table). In the subgroups (baseline tumor burden and bridging therapy) analyzed for safety, no new safety signals were identified. Conclusions: These results demonstrate the benefit of ide-cel in historically difficult-to-treat patient subsets. Deep and durable responses were observed in most subgroups, even in those with the highest risk, including patients with more aggressive disease features (extramedullary disease, high-risk cytogenetics, and high tumor burden), and those who received bridging therapy or multiple prior regiments per year. These results further support the favorable benefit-risk profile of ide-cel and suggest that ide-cel represents a promising treatment option for patients with RRMM, including those with high-risk disease. Table Disclosures Raje: Bluebird, Bio: Consultancy, Research Funding; Astrazeneca: Consultancy; Takeda: Consultancy; Caribou: Membership on an entity's Board of Directors or advisory committees; Immuneel: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy; Celgene: Consultancy; Janssen: Consultancy; BMS: Consultancy; Amgen: Consultancy. Siegel:Amgen: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria, Speakers Bureau; Karyopharma: Consultancy, Honoraria; Celulatiry: Consultancy; Merck: Consultancy, Honoraria, Speakers Bureau. Jagannath:Legend Biotech: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria. Lonial:BMS: Consultancy, Honoraria, Other: Personal fees, Research Funding; Merck: Consultancy, Honoraria, Other: Personal fees; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; JUNO Therapeutics: Consultancy; Genentech: Consultancy; Karyopharm: Consultancy; Sanofi: Consultancy; Janssen: Consultancy, Honoraria, Other: Personal fees, Research Funding; Millennium: Consultancy, Honoraria; Onyx: Honoraria; Novartis: Consultancy, Honoraria, Other: Personal fees; GSK: Consultancy, Honoraria, Other: Personal fees; Amgen: Consultancy, Honoraria, Other: Personal fees; Takeda: Consultancy, Other: Personal fees, Research Funding; Abbvie: Consultancy. Munshi:Amgen: Consultancy; Karyopharm: Consultancy; AbbVie: Consultancy; C4: Current equity holder in private company; Adaptive: Consultancy; Legend: Consultancy; BMS: Consultancy; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; Janssen: Consultancy; Takeda: Consultancy. Moreau:Janssen: Consultancy, Honoraria; Takeda: Consultancy; Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Sanofi: Honoraria. Goldschmidt:Incyte: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product:, Research Funding; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product:, Research Funding; Chugai: Honoraria, Other: Grants and/or provision of Investigational Medicinal Product:, Research Funding; Dietmar-Hopp-Foundation: Other: Grants and/or provision of Investigational Medicinal Product:; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product:, Research Funding; University Hospital Heidelberg, Internal Medicine V and National Center for Tumor Diseases (NCT), Heidelberg, Germany: Current Employment; GlaxoSmithKline (GSK): Honoraria; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product, Research Funding; Merck Sharp and Dohme (MSD): Research Funding; Molecular Partners: Research Funding; Novartis: Honoraria, Research Funding; Johns Hopkins University: Other: Grants and/or provision of Investigational Medicinal Product; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Mundipharma GmbH: Research Funding. Cavo:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel accomodations, Speakers Bureau; GlaxoSmithKline: Honoraria, Speakers Bureau; Karyopharm: Honoraria; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel accomodations, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Truppel-Hartmann:bluebird bio, Inc: Current Employment, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); F. Hoffmann La Roche: Current equity holder in publicly-traded company, Ended employment in the past 24 months. Rowe:Bristol-Myers Squibb: Current Employment. Huang:BMS: Current Employment, Current equity holder in publicly-traded company. Agarwal:Bristol-Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Wang:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Campbell:BMS: Current Employment, Current equity holder in publicly-traded company. San-Miguel:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; MSD: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees. Reece:Karyopharm: Consultancy; Amgen: Consultancy, Honoraria; Millenium: Research Funding; BMS: Research Funding; Merck: Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Otsuka: Research Funding.
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Siebert, S., K. Sweet, C. T. Ritchlin, E. C. Hsia, A. Kollmeier, X. L. Xu, Q. Song, and M. Miron. "POS0195 GUSELKUMAB TREATMENT MODULATES CORE PSORIATIC ARTHRITIS GENE EXPRESSION IN TWO PHASE 3 CLINICAL TRIALS (DISCOVER-1 AND -2)." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 312.2–312. http://dx.doi.org/10.1136/annrheumdis-2021-eular.479.
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Background:Guselkumab (GUS), an interleukin-23 p19-subunit monoclonal antibody, demonstrated efficacy compared with placebo (PBO) in reducing signs and symptoms of psoriatic arthritis (PsA) in the phase 3 DISCOVER-1 & 2 studies.1,2Objectives:To evaluate gene expression in the blood of PsA patients (pts) in the DISCOVER-1 & -2 studies and the impact of GUS on the expression of these genes.Methods:Pts were treated with GUS 100 mg every 4 weeks (Q4W); GUS 100 mg at W0, W4, then Q8W; or matching PBO. Whole transcriptome profiling by RNA-sequencing was performed using the Novaseq platform on blood samples obtained from a subset of 673 pts with PsA at baseline across the 2 DISCOVER studies, as well as from 21 demographically (age, sex, and ethnicity) matched healthy controls procured independently of the clinical program. A subgroup (N=227) also had serial blood samples (W0/W4/W24) evaluated; the subgroup pts were selected based on having baseline characteristics (demographics, disease activity, medication use) representative of the overall cross-study PsA population. Significance of differentially expressed genes (DEGs) between PsA and healthy controls was defined by a false discovery rate (FDR) <0.05 based on a log-linear model using edgeR. Top genes were defined by significance and |logFC| >1. For cell type analysis, genes that changed with GUS treatment were tested for enrichment using Cibersort. Gene enrichment scores were calculated using Gene Set Variation Analysis (GSVA).Results:To define disease genes, we compared genes at baseline in pts with active PsA vs. healthy control whole blood transcriptomes and detected 355 upregulated and 314 downregulated (top genes shown in Table 1), defined here as core disease genes. Upregulated genes were largely related to neutrophils, monocytes, macrophages, and extracellular matrix, whereas downregulated genes were related to T cells. The upregulated disease genes were significantly decreased and the downregulated disease genes were significantly increased by GUS treatment vs. PBO at W4 and W24 (Fig 1). Upon stratification by Psoriasis Area and Severity Index 75% response and American College of Rheumatology 20% response, changes in core disease gene expression from W0 were statistically significant among responders, but not in non-responders, at W4 and W24 (data not shown). We then performed the second differential expression analysis comparing baseline to W4 and W24 for both PBO and GUS treatment arms to define genes that change with treatment arm over time. At W4 and W24 we found many DEGs from baseline with GUS treatment and none with PBO. These included genes related to B-, T-, NK-, and plasma cells (increased by GUS) and neutrophils, monocytes, eosinophils, and macrophages (decreased by GUS), suggestive of a partial normalization of immune cell composition in whole blood.Conclusion:Using whole transcriptome profiling, we detected DEGs in blood samples obtained from PsA pts vs. healthy controls, suggesting a dysregulation of immune cell profiles in PsA. The majority of these disease-associated genes were modulated by GUS, with directionality toward a normalization of whole blood transcriptomic signatures.References:[1]Deodhar A et al. Lancet. 2020;395:1115.[2]Mease P et al. Lancet. 2020;395:1126.Table 1.Top DEGs derived from PsA vs. healthy whole blood transcriptomes.Upregulated in PsADownregulated in PsAGenelogFClogCPMFDRGenelogFClogCPMFDRADGRG75.92-0.900.02101AK8-1.36-1.061.61E-07ADAMTS24.060.820.006466FTCD-1.48-1.741.67E-05PGF3.21-0.680.006466GPR15-1.541.811.67E-05PCSK93.21-2.960.023872CHRM3-1.54-2.629.6E-08OLAH2.760.750.004539RFPL4AL1-1.69-3.340.009738MAOA2.55-0.260.005463SPACA3-1.85-3.230.000216SLC2A142.300.590.022594VANGL2-1.95-1.799.6E-08MMP12.25-1.160.004745RFPL4A-2.04-1.280.004539DAAM22.124.310.024628GLYATL2-2.77-2.781.93E-15BCAR1-3.13-2.586.24E-26Bold indicates positive change. CPM = counts per million.Disclosure of Interests:Stefan Siebert Consultant of: AbbVie, Janssen, Novartis, UCB, Grant/research support from: AbbVie, Amgen (previously Celgene), Bristol Myers Squibb, Boehringer Ingelheim, GSK, Janssen, Novartis, UCB, Kristen Sweet Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development LLC, Christopher T. Ritchlin Consultant of: AbbVie, Amgen, Gilead, Janssen, Eli Lilly, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Amgen, and UCB, Elizabeth C Hsia Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development LLC, Alexa Kollmeier Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development LLC, Xie L Xu Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development LLC, Qingxuan Song Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development LLC, Michelle Miron Shareholder of: Johnson & Johnson, Employee of: Janssen Research & Development LLC