Academic literature on the topic 'P 25.5 UL 2010 C399'

Abstract Abstract 1720 Background: The myelodysplastic syndromes are commonly divided into lower- and higher-risk subtypes depending on blast percentage and International Prognostic Scoring System (IPSS) score (0–1.0, low or Int-1, median overall survival (OS) 3.5–5.7 years). Because the IPSS is limited in its ability to identify poor prognosis lower-risk patients (pts), a prognostic scoring system specifically for lower-risk MDS pts (LR-PSS) was developed (Garcia-Manero Leukemia 2008) at MD Anderson (MDA), based on unfavorable (non-del(5q), non–diploid) cytogenetics, hemoglobin (hgb) <10g/dl, platelet count (plt) <50 k/uL or 50–200k/uL, bone marrow blast %≥4, and age ≥60 years. The IPSS-R (Greenberg Leuk Res 2011) improves upon the IPSS using novel cytogenetics classifications (Schanz EHA 2010) and a neutrophil cut-off of 800 k/uL. We validated the LR-PSS and the IPSS-R in a separate cohort of lower-risk MDS patients seen at Cleveland Clinic (CC) or at MDA not included in LR-PSS development. Methods: Of 1293 MDS patients identified at CC or MDA from 1991–2010, 664 had lower-risk disease and adequate data for analyses. OS was calculated from first date seen at either institution. The Kaplan–Meier method was used to estimate median OS. Univariable analyses were performed using the log-rank test; multivariable analyses used a Cox proportional hazards model stratified by treatment center. Harrell's c index and the Akaike information criteria (AIC) were used to assess the discriminatory power of the models and relative goodness of fit, respectively. Results: Comparing CC to MDA, baseline values were similar except median age: 70 vs. 67 years (p=.02); time since diagnosis: 2.7 vs. 1.1 months (p<.0001); hgb <10: 51% vs. 43% (p=.05); plt <50k/uL: 30 vs. 24% (p=.06); ANC <1.5 k/uL: 27% vs. 36% (p=.01); blasts <4%: 75% vs. 65% (p=.003); WHO classification RA/RARS/RCMD/CMML: 11/15/26/12% vs. 16/9/45/0% (p<.0001). Cytogenetics were diploid: 61% vs. 66%; del(5q): 9% vs. 2%; del(20q): 3% vs. 5%; -Y: 4% vs. 2%, respectively (p=.5). Median OS was 36.8 months (95% C.I. 33–45) and median follow-up of patients still alive was 13.9 months (range 0.01–155). LR-PSS and IPSS-R classifications for CC and MDA Pts and OS are in Table 1 and Figure 1. In univariable analyses, The IPSS, LR-PSS, and IPSS-R were all predictive of OS (p=.002, <.0001, and <.0001, respectively). Multivariable analyses confirmed the overall predictive abilities of the prognostic tools and of Hgb, plt, age, and IPSS/IPSS-R cytogenetics (all p≤.03). Compared to the IPSS-R, the LR-PSS had the higher (better) Harrell's c value (.64 vs.63) and lower (better) AIC (2518 vs. 2525). The LR-PSS upstaged 156 pts (25%) from IPSS low or Int-1 to LR-PSS Category 3, and downstaged 47 pts (12%) from Int-1 to Category 1. The IPSS-R upstaged 164 pts (27%) from IPSS low or Int-1 to IPSS-R Categories ≥Intermediate, and downstaged 5 pts (1%) from Int-1 to Very Good. Conclusions: The LR-PSS and IPSS-R are valid tools for distinguishing among pts previously thought to have lower-risk disease by the IPSS, and identifying those who have better and worse survival. This latter group of pts may benefit from earlier interventions with disease-modifying therapies, and should be considered in trials targeting higher-risk MDS pts. The LR-PSS appears to provide slightly better prognostic information. Disclosures: Sekeres: Celgene: Consultancy, Honoraria, Speakers Bureau. Maciejewski:Celgene: Membership on an entity's Board of Directors or advisory committees.

Abstract INTRODUCTION: Autografting (auto-HSCT) is widely used for the treatment of hematological malignancies. Since 2010, Biosimilar Filgrastim (Nivestim™, Pfizer Inc.) (BioG-CSF) has been approved and introduced into clinical practice to mobilize hematopoietic stem cells (CD34+cells) and to reduce the duration of chemo-induced neutropenia. This single institution study was designed to evaluate its safety and efficacy in the setting of "real life" medical practice. METHODS: We designed a "mixed retrospetive-prospective study" to evaluate the impact of BioG-CSF on CD34+ cells collections and engraftment kinetics after autografting. Patients who received BioG-CSF were compared with a historical cohort treated with Originator G-CSF (Filgrastim or Lenograstim). Primary endopoints were CD34+ mobilizations and post auto-HSCT engraftment kinetics. Secondary objectives included transfusions requirements, duration of hospitalization and 1-year overall survival (OS). Leukapheresis (LA) was initiated when circulating CD34+ count was at least 20/uL. Day of neutrophil engraftment was defined as the first of 3 consecutive days of absolute neutrophil count (ANC) ≥ 500/ul whereas day of platelet engraftment was defined as the first of 7 consecutive days without transfusion support. RESULTS: Initially,187 patients (137/187 affected by multiple myeloma) have been enrolled in the cohort under evaluation for CD34+ mobilization kinetics. Overall, 138 and 49 patients received originator and BioG-CSF (5-10 ug/kg/day) to collect CD34+cells. All but two patients underwent chemotherapy for mobilization (high-dose cyclophosphamide in 157/187 patients). Less than 3% of patients were poor mobilizers in both cohorts. No differences between Originator and BioG-CSF cohort were observed in time from chemotherapy to first day of LA (median day 11 vs day 11 p=0.473), CD34+/ul (mean 157.3/ul vs 166.2/ul, p=0.59) and CD34+*10^6/kg recipient harvested on the first day of LA (mean 10.5*10^6/kg vs 11.1*10^6/kg, p=0.323). A higher count of white blood cells on the first day of LA was observed in patients treated with BioG-CSF (mean originator 18.6*10^9/L vs BioG-CSF 27.1*10^9/L, p=0.001). A further analysis was conducted on 175 patients (126/175 affected my multiple myeloma) for a total of 220 auto-HSCTs, evaluable for hematological recovery and clinical outcomes. Overall, 137 and 83 patients received Originator and BioG-CSF, respectively. All patients were hospitalized and prepared for the autograft with a high-dose conditioning (Melphalan 200mg/sqm in 171/220 auto-HSCTs). Infused CD34+ cells were 5*10^6/kg recipient (IQR 3.8-5.1) and 4.1*10^6/kg recipient (IQR 3.5-5.3) in the Originator and BioG-CSF cohorts. After the autograft, patients were prescribed 30-34 milliion units (MU) of Originator G-CSF and 30 MU dose of BioG-CSF starting on day +1/+3. Day +25 cumulative incidences of ANC and platelets recovery were 99.3% and 98.5% and 97.6% and 90.2% in the Originator and BioG-CSF groups, respectively (p=0.786, p=0.006). Of note, by Mann-Whitney test, no differences between cohorts were found in a)median duration of neutropenia (median 7 and 6 days, p=0.355), platelets (median 1 pool/patient in both, p=0.894) and red blood cells (median 0/patient in both, p=0.704) transfusion requirements, hospital stay (median 20 days and 21 days, p=0.33). Serial measurements of complete blood counts were performed from discharge to day +90 post auto-HSCT; no significant differences were found at any time point between the two groups. No severe adverse reactions attributable to G-CSFs were documented. Thrombocytopenia lasted longer for patients treated with BioG-CSF, however this finding did not translate into a higher transfusion requirement or bleeding episodes. Finally, 1-year OS was comparable between cohorts (p=0.699). CONCLUSIONS: In this sizable study, BioG-CSF was as effective as Originator G-CSF in mobilizing CD34+ cells as well as in treating post-transplant neutropenia in patients with hematological malignancies. Moreover, the extensive use of BioG-CSF led to a significant cost containment. Disclosures Massaia: Janssen: Other: advisory board; Gilead: Other: advisory board; Roche: Other: advisory board, research support. Cavallo:JANSSEN: Honoraria; CELGENE: Honoraria; ONYX: Honoraria. Palumbo:Janssen Cilag: Honoraria; Takeda: Employment, Honoraria. Boccadoro:Janssen: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Mundipharma: Research Funding; Abbivie: Honoraria; SANOFI: Honoraria, Research Funding; BMS: Honoraria, Research Funding; CELGENE: Honoraria, Research Funding.

Abstract Abstract 3681 Background: Pediatric Immune Thrombocytopenia (ITP) has an incidence of 4–6/100,000 with 1/3 of cases becoming chronic. Treatment choice is arbitrary, because few studies are powered to identify predictors of therapy response. Increasingly, rituximab is becoming a treatment of choice in those refractory to other therapies (Neunert CE, et al. Pediatr Blood Cancer 2008; 51(4):513). Previous studies in ITP have not examined predictors of response to rituximab or whether response to prior treatments predicts response. Objective: To evaluate univariate and multivariable predictors of platelet count response to rituximab. Methods: After local IRB approval, 550 patients with chronic ITP enrolled in the longitudinal, North American Chronic ITP Registry (NACIR) between January 2004 and June 2010. Eligibility included: ages 6 months-18 years at ITP diagnosis, clinical diagnosis of ITP, and ITP duration >6 months. Primary ITP was defined as isolated thrombocytopenia without associated conditions. Secondary ITP included those patients with immune thrombocytopenia associated with other immune-mediated medical conditions, including Evans Syndrome. Treatment response was defined as a post-treatment platelet count ≥50,000/uL within 16 weeks of rituximab and within 14 days of steroids. Steroids were prescribed as 1–4 mg/kg prednisone or adult equivalent over 4–14 days with or without taper. The NACIR captured treatment responses both retrospectively prior to enrollment and then prospectively, and both periods were included in this analysis. The multivariable logistic regression modeling process utilized SAS 9.1 using binary variables which were either significant in the univariate analysis or clinically important. A backwards elimination procedure was used to select the final model. Results: Seventy-six (13.8%) patients were treated with rituximab. Demographics of the patients treated with rituximab include: 42% male; 81% Caucasian, 17% Black, and 2% Asian. The mean age at diagnosis of ITP was 8.4 ± SD 5.1 years. The median platelet count at diagnosis of acute ITP was 10,000/uL (IQR 5,000-20,000/uL). 19 (25%) patients had secondary ITP or Evans syndrome. Treatment with rituximab had an overall response rate of 63.2% (48/76). Univariate predictors of response to rituximab are shown in Table I. The strongest univariate predictor of response to rituximab was response to steroids. Gender, ethnicity, and race were not predictive of response to rituximab. Furthermore, other variables which did not predict rituximab response include: history of a bleeding score ≥3 (Buchanan and Adix, J Pediatr 2002; 141: 683), symptoms ≥1 month prior to ITP diagnosis, older age (age >5 years), platelets ≥20,000/uL at acute ITP diagnosis, and a positive ANA. In multivariable analysis, response to steroids remained a strong predictor of response to rituximab with an OR 6.2 (95% CI 1.8–21.3, p=0.004). Secondary ITP also remained a strong a predictor of a positive response to rituximab with an OR 5.9 (95% CI 1.2–33.3, p=0.03). Conclusion: In the NACIR, response to steroids and secondary ITP were strong predictors of response to rituximab, a finding not previously reported in children or adults. Although this finding requires further validation, this result may provide evidence that rituximab should be most considered in patients previously responsive to steroids. Disclosures: Off Label Use: Rituximab for chronic ITP. Lambert:Cangene: Membership on an entity's Board of Directors or advisory committees. Klaassen:Novartis: Research Funding; Cangene: Research Funding. Neufeld:Novartis, Inc: Research Funding.

Abstract Introduction: Interleukin 2 receptor-α (CD25) expression on myeloid leukemic blasts may be a marker for chemotherapy-resistant leukemia stem cells (Saito et al., 2010) and has been associated with poor overall survival (OS) in AML patients (pts) <60 years treated with cytotoxic chemotherapy (Terwijn et al., 2009; Gonen et al., 2012; Cerny et al., 2013). The prognostic impact of CD25 expression in older pts remains unclear. We therefore retrospectively analyzed CD25 expression in baseline bone marrow (BM) of newly diagnosed AML pts >60 years enrolled in a Phase I clinical trial combining the CXCR4 antagonist, plerixafor and the DNA methyltransferase inhibitor, decitabine (Roboz et al., 2013). Methods: BM aspirates were available for 69 newly diagnosed older AML pts treated with 1-4 cycles of 5 days of plerixafor combined with 10 days of decitabine. Pts with favorable risk cytogenetic or mutational profiles were excluded from the clinical trial. Multi-parameter flow cytometry was used to evaluate the expression of CD25 in blast and progenitor (CD34+) populations. Cells were gated on CD45dim/SSClo characteristics. Pts were considered positive (CD25+) when greater than 10% of the gated population expressed CD25. Results: Of 69 pts, 58 were evaluable for survival and 57 for response; one pt died prior to scheduled response assessment. Of 58 pts evaluated at baseline (pre-treatment BM), 20 (34.5%) were CD25+ vs. 38 (65.5%) CD25-negative (CD25-). CD25+ pts had significantly inferior median OS (152 days vs. 419 days, p=0.003) and were at higher risk of dying within 1 year of diagnosis, relative risk (RR) 1.58 (95% 1.04-2.41). Similarly, pts surviving less than 1 year had significantly higher percentages of CD34+ cells expressing CD25 than those who lived greater than 1 year (7.82% vs. 4.77%, p=0.028). CD25+ pts were less likely to respond to therapy, RR 1.90 (95% CI 1.23-2.93) and, in turn, pts who were resistant to therapy had higher baseline CD25 expression level than those who responded (7.82% vs. 4.87%, p=0.033). Five CD25+ pts (25%) and 12 CD25- pts (32%) received an allogeneic transplant. Transplanted CD25+ pts had improved OS vs. CD25+ pts without transplant, (median OS not reached (NR) vs. 107 days), p=0.005. In contrast, there was no significant difference in survival between CD25- pts with and without allogeneic transplant, p=0.96. Also, there was no difference in median OS between CD25+ pts receiving transplant vs. CD25- pts (median OS NR vs. 419 days), p<0.40. There was no difference in survival between CD25+ pts with intermediate risk cytogenetics vs. CD25+ pts with unfavorable cytogenetics (OS 153 vs. 172, p=0.77). Lastly, CD25+ pts had significantly worse OS compared to CD25- pts with unfavorable cytogenetics, (median OS 152 vs. 333 days) respectively, p=0.05. Compared to CD25- pts, CD25+ pts were older (median age 74.5 vs. 71.5, p=0.096), more likely to be male (75% vs. 47.3%, p=0.055) and had higher baseline WBC (19x1000/uL vs. 5x1000/uL, p=0.089) and pretreatment lactate dehydrogenase (LDH) (median 365 vs. 271, p=0.04). Analysis of diagnosis BM blast percentage yielded no difference between CD25+ and CD25- pts (62% and 46%, p=0.44). Sixteen (80%) and 4 (20%) of CD25+ patients had intermediate and unfavorable cytogenetics vs. 21 (55%) and 17 (44%) CD25- pts respectively, p=0.09. No significant difference between groups was noted when evaluating the mutational status of TET2, TP53, RUNX1, DNMT3A, NPM1, or FLT3. Conclusions: Interleukin 2 Receptor-α expression on leukemic blasts is known to correlate with poor prognosis and OS in young pts with AML who have been treated with cytotoxic chemotherapy. We have demonstrated that >10% CD25 expression on CD34+ blasts is associated with poor OS and resistance to therapy in AML pts > 60years of age treated with the combination of plerixafor and decitabine. Pts with >10% CD25 expression on CD34+ cells were at increased risk of death within one year and increased risk of resistance to induction therapy. Thirty-four percent of the pts in this study were CD25+, consistent with previous reports (Terwijn et al., 2009). This study highlights the importance of CD25 expression on CD34+ leukemic cells in determining prognosis, OS, response to hypomethylating agent therapy and benefit of transplant in older pts with newly diagnosed AML. Further investigations into the aggressive nature of CD25+ AML, mechanisms of resistance and novel therapeutics are ongoing. Disclosures Roboz: Teva Oncology: Consultancy; Novartis: Consultancy; Sunesis: Consultancy; Astra Zeneca: Consultancy; Glaxo SmithKline: Consultancy; Celgene: Consultancy; Agios: Consultancy; Novartis: Consultancy; Astex: Consultancy. Ritchie:Celgene, Incyte: Speakers Bureau.

Abstract Abstract 2555 High hyperdiploidy is present in 30% of children with acute lymphocytic leukemia (ALL), and is associated with a favorable prognosis. We evaluated pts with newly diagnosed ALL treated on SWOG trials S9400 (1995–2000) and S0333 (2005–2010) to determine the prevalence and prognostic impact of hyperdiploidy in adults with ALL. Additionally, we examined the prognostic impact of hypodiploidy, a feature typically associated with a poor prognosis in children. Methods: One-hundred and eighty-five pts treated on S9400 and S0333 with successful cytogenetic (CG) analysis were included. The treatment regimens were: S9400 [Induction: Daunorubicin (D), vincristine (V), prednisone (P), PEG-asparaginase (PEG); Consolidation: Cytoxan (Cy), cytarabine (AraC), 6-mercaptopurine (6MP), intrathecal methotrexate (IT Mtx). Consolidation was followed by allogeneic stem cell transplant or maintenance chemotherapy] and S0333: Double Induction Chemotherapy [Induction 1: D, V, P, PEG; Induction 2: high dose AraC, mitoxantrone, decadron. Consolidation: Cy, AraC, 6MP, Mtx; consolidation was followed by maintenance therapy]. Karyotypes were centrally reviewed and clonal abnormalities described according to ISCN (2009). Hyperdiploidy was defined as: low hyperdiploidy [47–49 chromosomes (cs)], high hyperdiploidy (51–65 cs), near triploidy (66–79 cs), and near tetraploidy (84–100 cs). Hypodiploidy was defined as: near haploidy (25–29 cs), low hypodiploidy (31–39 cs), and high hypodiploidy (42–45 cs). When more than one cell line was present, ploidy was assigned by the most complex clonal karyotype. Hypodiploidy and hyperdiploidy were analyzed as prognostic factors for complete response (CR) rate and residual disease (RD) by logistic regression and chi-square tests; and for overall survival (OS) and relapse-free survival (RFS) by proportional hazards. Multivariable analyses were stratified by study and using the baseline variables: age, WBC, lineage, and CG risk. Results: The median age was 32 yrs (range 17–64), and median WBC at diagnosis 17.2 K/uL (range 0.6–396.6). CG risk was ascribed by (Pullarket V et al. Blood 2008; 111: 2563). Forty-five pts (24%) had normal CG, and 73 (39%) had poor risk CG. Fourteen pts (8%) had hypodiploidy (2: low hypodiploidy; 12: high hypodiploidy). Fifty-three pts (29%) had hyperdiploidy [40: low hyperdiploidy, 10: high hyperdiploidy (5%), 3: near tetraploidy or tetraploidy (2%)]. The CR rate for all pts was 72%; with a median RFS of 15 mos (95% CI: 12–29 mos) and median OS of 28 mos (95% CI: 21–36 mos). There was no significant association with ploidy status and age, WBC, or lineage. However, there was an increased prevalence of the t(9;22) in the high hypodiploidy group compared to the normal/pseudo diploidy group (p=0.049). Neither hypodiploidy nor hyperdiploidy were predictive of CR or RD; although pts with hypodiploidy had a higher rate of RD (p=0.062). The 2 pts with low hypodiploidy had very poor outcomes (1 had RD and died after 11 mos; the other relapsed after 3 mos from CR and died 4 mos after study registration). There were no statistically significant differences in OS, CR rate, or RFS between the ploidy groups even after adjusting for baseline characteristics in multivariate analysis. Surprisingly, when excluding pts with poor risk CG there was still a trend towards a worse RFS (29 vs. 32 months, p=0.20) and OS (40 vs. 68 mos, p=0.29) in pts with hyperdiploidy compared to normal/pseudodiploidy. In addition, the 3 pts in the high hyperdiploidy group without poor risk CG had poor OS (median 23 mos). Conclusions: The prevalence of high hyperdiploidy is much lower in adults with ALL, compared to children. The prevalence of hypodiploidy and near tetraploidy/tetraploidy is comparable to that seen in children with ALL. Hypodiploidy and high hyperdiploidy were not prognostic factors for outcome in this group of patients. Given the low prevalence of these abnormalities, it is possible that larger numbers of pts may be needed to detect such a difference. The poor outcomes of pts with low hypodiploidy are consistent with findings by Moorman et al. (Blood 2006; 109: 3189). However, in contrast to Moorman's results, there was no evidence of an association of hyperdiploidy with age/WBC, and there was a trend towards a worse prognosis in this subset of patients. This suggests that the biology and prognosis of high hyperdiploidy may be affected more by WBC and age in the adult population. Disclosures: No relevant conflicts of interest to declare.