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Journal articles on the topic 'Multiple Stratification'

Author: Grafiati

Published: 8 September 2023

Last updated: 31 July 2025

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1

JOURDAIN, BENJAMIN, BERNARD LAPEYRE, and PIERGIACOMO SABINO. "CONVENIENT MULTIPLE DIRECTIONS OF STRATIFICATION." International Journal of Theoretical and Applied Finance 14, no. 06 (2011): 867–97. http://dx.doi.org/10.1142/s0219024911006772.

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This paper investigates the use of multiple directions of stratification as a variance reduction technique for Monte Carlo simulations of path-dependent options driven by Gaussian vectors. The precision of the method depends on the choice of the directions of stratification and the allocation rule within each strata. Several choices have been proposed but, even if they provide variance reduction, their implementation is computationally intensive and not applicable to realistic payoffs, in particular not to Asian options with barrier. Moreover, all these previously published methods employ orth

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2

Ooi, Melissa Gaik-Ming, Sanjay de Mel, and Wee Joo Chng. "Risk Stratification in Multiple Myeloma." Current Hematologic Malignancy Reports 11, no. 2 (2016): 137–47. http://dx.doi.org/10.1007/s11899-016-0307-4.

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3

Skinner, C. J., D. J. Holmes, and D. Holt. "Multiple Frame Sampling for Multivariate Stratification." International Statistical Review / Revue Internationale de Statistique 62, no. 3 (1994): 333. http://dx.doi.org/10.2307/1403765.

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4

Chang, Kuang-Chao, Jeng-Fu Liu, and Chien-Pai Han. "Multiple inverse sampling in post-stratification." Journal of Statistical Planning and Inference 69, no. 2 (1998): 209–27. http://dx.doi.org/10.1016/s0378-3758(97)00157-2.

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5

Gharbi, Alya, Saloua Mrabet, Amina Nasri, et al. "Prognostic Factors Stratification in Multiple Sclerosis." Multiple Sclerosis and Related Disorders 37 (January 2020): 101534. http://dx.doi.org/10.1016/j.msard.2019.11.009.

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6

Ghaemsaidi, S. J., H. V. Dosser, L. Rainville, and T. Peacock. "The impact of multiple layering on internal wave transmission." Journal of Fluid Mechanics 789 (January 25, 2016): 617–29. http://dx.doi.org/10.1017/jfm.2015.682.

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Given the ubiquity of layering in environmental stratifications, an interesting example being double-diffusive staircase structures in the Arctic Ocean, we present the results of a joint theoretical and laboratory experimental study investigating the impact of multiple layering on internal wave propagation. We first present results for a simplified model that demonstrates the non-trivial impact of multiple layering. Thereafter, utilizing a weakly viscous linear model that can handle arbitrary vertical stratifications, we perform a comparison of theory with experiments. We conclude by applying

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7

Ortega-Legarreta, Asier, Sara Palomino-Echeverria, Estefania Huergo, et al. "ClustAll: An R package for patient stratification in complex diseases." PLOS Computational Biology 20, no. 12 (2024): e1012656. https://doi.org/10.1371/journal.pcbi.1012656.

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In the era of precision medicine, it is necessary to understand heterogeneity among patients with complex diseases to improve personalized prevention and management strategies. Here, we introduce ClustAll, a Bioconductor package designed for unsupervised patient stratification using clinical data. ClustAll is based on the previously validated methodology ClustAll, a clustering framework that effectively handles intricacies in clinical data, including mixed data types, missing values, and collinearity. Additionally, ClustAll stands out in its ability to identify multiple patient stratifications

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Chang, Kuang-Chao, Chien-Pai Han, and Doyle L. Hawkins. "Truncated multiple inverse sampling in post-stratification." Journal of Statistical Planning and Inference 76, no. 1-2 (1999): 215–34. http://dx.doi.org/10.1016/s0378-3758(98)00135-9.

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9

Ontaneda, Daniel, Samuel Cohn, and Robert J. Fox. "Risk stratification and mitigation in multiple sclerosis." Multiple Sclerosis and Related Disorders 3, no. 5 (2014): 639–49. http://dx.doi.org/10.1016/j.msard.2014.05.003.

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10

Hussain, Mohsin, Asad Mahmood, Rafia Mahmood, Hamid Iqbal, Ayesha Khurshid, and Nabeela Khan. "Multiple Myeloma-Clinicopathological Features and Risk Stratification." Pakistan Armed Forces Medical Journal 72, SUPPL-2 (2022): S95–98. http://dx.doi.org/10.51253/pafmj.v72isuppl-2.3100.

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Objective: To evaluate the clinic pathological features and to risk stratify patients of multiple myeloma in our population. Study Design: Cross sectional study. Place and Duration of Study: Department of Hematology, Armed Forces Institute of Pathology (AFIP) Rawalpindi Pakistan, from Jan to Jun 2019. Methodology: Patients that were newly diagnosed multiple myeloma on the basis of International Myeloma Working Group (IMWG) 2014 criteria were included in the study. Blood counts, peripheral film examination, bone marrow aspirate and trephine were examined. Biochemical profile,

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11

van de Donk, Niels W. C. J., and Pieter Sonneveld. "Diagnosis and Risk Stratification in Multiple Myeloma." Hematology/Oncology Clinics of North America 28, no. 5 (2014): 791–813. http://dx.doi.org/10.1016/j.hoc.2014.06.007.

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12

Hansen, Rickard. "Smoke Stratification in a Mine Drift with Multiple Objects Downstream." Mining Revue 29, no. 1 (2023): 1–18. http://dx.doi.org/10.2478/minrv-2023-0001.

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Abstract The smoke behaviour and smoke stratification of a fire in a mine drift will be one of the decisive factors affecting the risk to mining personnel during a fire. This paper studies the smoke stratification in a mine drift with multiple objects downstream of the fire, at varying distances and number of objects. Data for the study was provided from earlier model-scale fire experiments and CFD modelling was performed for in-depth analysis of specific phenomena. It was found that at considerable downstream distances from the fire, the smoke stratification differences were significant, refl

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13

Cai, Runjia. "Dietary and Social Stratification: An Anthropological Perspective." COMPASS 4, no. 1 (2024): 56–65. http://dx.doi.org/10.29173/comp62.

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The number of articles dedicated to dietary and social stratification today is relatively small, and those that exist are often based on quantitative statistics rather than direct observations and narratives of people. This article aims to describe and analyze these phenomena, revealing the often invisible and nuanced social stratifications and definitions. This article uses phenomenological interpretation and analysis, providing an arrative overview of people’s choices and needs regarding their diets. Although diet continues to be influenced by social stratification, this influence is gradual

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14

Lussier, Tyler, Natalie Schoebe, and Sabine Mai. "Risk Stratification and Treatment in Smoldering Multiple Myeloma." Cells 11, no. 1 (2021): 130. http://dx.doi.org/10.3390/cells11010130.

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Smoldering multiple myeloma is a heterogeneous asymptomatic precursor to multiple myeloma. Since its identification in 1980, risk stratification models have been developed using two main stratification methods: clinical measurement-based and genetics-based. Clinical measurement models can be subdivided in three types: baseline measurements (performed at diagnosis), evolving measurements (performed over time during follow-up appointments), and imaging (for example, magnetic resonance imaging). Genetic approaches include gene expression profiling, DNA/RNA sequencing, and cytogenetics. It is impo

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15

De Queiroz Crusoe, Edvan, Alana Von Glasenapp, Glaciano Ribeiro, et al. "Smoldering Multiple Myeloma in Latin America- Risk Stratification." Blood 144, Supplement 1 (2024): 3774. https://doi.org/10.1182/blood-2024-209038.

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Introduction: Smoldering multiple myeloma (sMM) is a heterogeneous clinical entity that behaves as an indolent or aggressive plasma cell disease that can evolve to symptomatic MM. There is scarce data about sMM in Latin America (LA) and we aimed to characterize sMM in this region. Methods: The Brazilian and Latin America Myeloma Study Groups (GBRAM and GELAMM) established a consortium to conduct a retrospective cohort study of sMM cases diagnosed from 2015 to 2023. Demographics and diagnostic and prognostic tools data were collected. We also evaluated risk factors associated with the chance of

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16

Wong, A. B. D., and R. W. Griffiths. "Stratification and convection produced by multiple turbulent plumes." Dynamics of Atmospheres and Oceans 30, no. 2-4 (1999): 101–23. http://dx.doi.org/10.1016/s0377-0265(99)00022-6.

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17

Fernández-Paredes, Lidia, Armanda Casrouge, Jérémie Decalf, et al. "Multimarker risk stratification approach at multiple sclerosis onset." Clinical Immunology 181 (August 2017): 43–50. http://dx.doi.org/10.1016/j.clim.2017.05.019.

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18

Scott, James G. "Nonparametric Bayesian multiple testing for longitudinal performance stratification." Annals of Applied Statistics 3, no. 4 (2009): 1655–74. http://dx.doi.org/10.1214/09-aoas252.

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19

Chng, W. J., A. Dispenzieri, C.-S. Chim, et al. "IMWG consensus on risk stratification in multiple myeloma." Leukemia 28, no. 2 (2013): 269–77. http://dx.doi.org/10.1038/leu.2013.247.

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20

Kapoor, Rajan, Rajiv Kumar, and A. P. Dubey. "Risk Stratification in Multiple Myeloma in Indian Settings." Indian Journal of Hematology and Blood Transfusion 36, no. 3 (2019): 464–72. http://dx.doi.org/10.1007/s12288-019-01240-4.

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21

Ara Islam, Ismat, Mohsin Hasan Samarat, Nishat Mahzabin, et al. "Risk stratification of newly diagnosed multiple myeloma patients." International Journal of Research in Medical Sciences 12, no. 5 (2024): 1402–7. http://dx.doi.org/10.18203/2320-6012.ijrms20241219.

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Background: Multiple Myeloma is a neoplastic proliferation of plasma cells, associated with an M (monoclonal) protein in serum and/or urine and evidence of organ damage. Despite advances in treatment, the disease remains heterogeneous, necessitating a comprehensive understanding of its risk stratification. Risk-adapted initial therapy, maintenance therapy, refractory disease management and prognosis varies according to risk group. The aim of our study is to categorize the newly diagnosed MM patients according to their risk groups. Methods: This cross-sectional observational study was conducted

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22

Khadija, Jarnige, El yaacoubi Raounak, Tlamçani Imane, and Amrani Hassani Monçef. "Événements thromboemboliques au cours du myélome multiple : Stratification du risque et prophylaxie. Thromboembolic Events in Multiple Myeloma: Risk Stratification and Prophylaxis." Journal of Medical and Dental Science Research 11, no. 8 (2024): 94–106. http://dx.doi.org/10.35629/076x-110894106.

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La thromboembolie veineuse est une complication fréquente chez les patients atteints d'hémopathies malignes, due à la fois à la libération de facteurs procoagulants par les cellules tumorales et à des facteurs externes tels que les médicaments. Chez les patients atteints de myélome multiple, le risque est accru par l'utilisation d'immunomodulateurs, en particulier lorsqu'ils sont associés à une polychimiothérapie, pendant la phase d'induction. Prévention de la thromboembolie veineuse chez les patients atteints de myélome est fortement recommandée, mais il n'existe pas encore de directives spéc

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23

Segges, Priscilla, and Esteban Braggio. "Genetic Markers Used for Risk Stratification in Multiple Myeloma." Genetics Research International 2011 (September 13, 2011): 1–4. http://dx.doi.org/10.4061/2011/798089.

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While no specific genetic markers are required in the diagnosis of multiple myeloma (MM), multiple genetic abnormalities and gene signatures are used in disease prognostication and risk stratification. This is particularly important for the adequate identification of the high-risk MM group, which does not benefit from any of the current therapies, and novel approaches need to be proposed. Fluorescence in situ hybridization (FISH) has been employed for establishing risk-based stratification and still remains the most used genetic technique in the clinical routine. The incorporation of gene expr

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24

Koohestani, Kamran, Yury Stepanyants, and Mohammad Nabi Allahdadi. "Analysis of Internal Solitary Waves in the Gulf of Oman and Sources Responsible for Their Generation." Water 15, no. 4 (2023): 746. http://dx.doi.org/10.3390/w15040746.

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A combination of multiple data sources has been used to study the characteristics of internal solitary waves (ISWs) in the Gulf of Oman (GoO). Water column stratification in the Gulf has been examined using field observations and World Ocean Atlas 2018 datasets. The spatiotemporal distribution of ISWs has been obtained from satellite images obtained by means of Synthetic Aperture Radar (SAR) and optical sensors taken from 2018 to 2020. The mechanisms of ISW generation in the GoO have been studied using the data revealed from different available sources. The results show that there are annually

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25

O'Dowd, E., C. Bellinger, T. Dotson, et al. "P42.01 AI Assistance for Pulmonary Nodule Stratification: An Multiple-Reader Multiple-Case Study." Journal of Thoracic Oncology 16, no. 3 (2021): S477. http://dx.doi.org/10.1016/j.jtho.2021.01.825.

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26

Smilowitz, Nathaniel R., Vuthy Nguy, Yindalon Aphinyanaphongs, et al. "Multiple Biomarker Approach to Risk Stratification in COVID-19." Circulation 143, no. 13 (2021): 1338–40. http://dx.doi.org/10.1161/circulationaha.120.053311.

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27

Yoon, Sung-Soo. "Multiple myeloma in Korea: risk stratification and initial treatment." Blood Research 53, no. 3 (2018): 183. http://dx.doi.org/10.5045/br.2018.53.3.183.

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28

Jiang, Allan, Donna Reece, and Hong Chang. "Genomic stratification of multiple myeloma treated with novel agents." Leukemia & Lymphoma 53, no. 2 (2011): 202–7. http://dx.doi.org/10.3109/10428194.2011.608449.

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29

Shores, Kindal A., David Scott, and Myron F. Floyd. "Constraints to Outdoor Recreation: A Multiple Hierarchy Stratification Perspective." Leisure Sciences 29, no. 3 (2007): 227–46. http://dx.doi.org/10.1080/01490400701257948.

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30

Das, Nupur, and Ritu Gupta. "Risk stratification in multiple myeloma – A review and update." Annals of the National Academy of Medical Sciences (India) 60 (May 2, 2024): 120–30. http://dx.doi.org/10.25259/anams-2023-1-7-(820).

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Multiple myeloma (MM) is a hematological malignancy of plasma cell origin with a prevalence rate of 1% and 10% of all cancers and hematopoietic malignancies, respectively. Though the median survival time has improved dramatically in the patients diagnosed with MM with the administration of novel therapeutic agents, the disease, by and large, remains incurable with frequent progression and relapses. In the recent past, an increased understanding of MM pathogenesis has opened facets for improved diagnosis, prognosis, and response assessment in patients diagnosed with MM. This review focuses on t

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31

Lee, KangJae Jerry, and David Scott. "Participation in Wildlife Watching: A Multiple Hierarchy Stratification Perspective." Human Dimensions of Wildlife 16, no. 5 (2011): 330–44. http://dx.doi.org/10.1080/10871209.2011.597825.

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32

Bayes-Genis, Antoni, and Jordi Ordonez-Llanos. "Multiple biomarker strategies for risk stratification in heart failure." Clinica Chimica Acta 443 (March 2015): 120–25. http://dx.doi.org/10.1016/j.cca.2014.10.023.

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33

Tur, Carmen, and Xavier Montalban. "Natalizumab: Risk Stratification of Individual Patients with Multiple Sclerosis." CNS Drugs 28, no. 7 (2014): 641–48. http://dx.doi.org/10.1007/s40263-014-0168-0.

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34

Graf, Jonas, Verena I. Leussink, Thomas Dehmel, et al. "Infectious risk stratification in multiple sclerosis patients receiving immunotherapy." Annals of Clinical and Translational Neurology 4, no. 12 (2017): 909–14. http://dx.doi.org/10.1002/acn3.491.

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35

Li, Jiali, Xixi Xiang, Jun Rao, et al. "Copy Number Variants Identified By Shallow Whole-Genome Sequencing in Multiple Myeloma." Blood 144, Supplement 1 (2024): 6931. https://doi.org/10.1182/blood-2024-206990.

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Background: Multiple myeloma is a plasma cell neoplasm driven by primary and secondary chromosomal events. The detection of these copy number abnormalities (CNAs) are important, because they affect the prognosis, therapeutic response and disease survival. Methods: A total of 131 patients with newly diagnosed multiple myeloma were enrolled in this study to detect genome-wide CNAs by shallow whole-genome sequencing(sWGS). Risk stratification was performed following the Mayo Stratification of Myeloma and Risk-adapted Therapy (mSMART) criteria. Results: Compared with karyotyping and Fluorescence i

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36

Kurian, Allison W., Antonis C. Antoniou, and Susan M. Domchek. "Refining Breast Cancer Risk Stratification: Additional Genes, Additional Information." American Society of Clinical Oncology Educational Book, no. 36 (May 2016): 44–56. http://dx.doi.org/10.1200/edbk_158817.

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Recent advances in genomic technology have enabled far more rapid, less expensive sequencing of multiple genes than was possible only a few years ago. Advances in bioinformatics also facilitate the interpretation of large amounts of genomic data. New strategies for cancer genetic risk assessment include multiplex sequencing panels of 5 to more than 100 genes (in which rare mutations are often associated with at least two times the average risk of developing breast cancer) and panels of common single-nucleotide polymorphisms (SNPs), combinations of which are generally associated with more modes

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37

Ishino, Mitsunori, Yasuchika Takeishi, Takeshi Niizeki, et al. "Risk Stratification of Chronic Heart Failure Patients by Multiple Biomarkers." Circulation Journal 72, no. 11 (2008): 1800–1805. http://dx.doi.org/10.1253/circj.cj-08-0157.

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38

Sandoval-Sus, Jose, Claudia Sossa, Luis Antonio Salazar, et al. "Cytogenetic Risk Stratification in a Centre Colombian Multiple Myeloma Patients." Blood 144, Supplement 1 (2024): 6947. https://doi.org/10.1182/blood-2024-212370.

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Introduction: Multiple myeloma (MM) is a heterogeneous disease with patient outcomes influenced by guest factors, clinical presentation, and genetic abnormalities. This study aimed to classify MM patients into risk groups based on cytogenetic markers and assess their impact on survival. Methods: We conducted a prospective cross-sectional study involving 50 MM patients (aged &gt;18 years) treated at Clinica Foscal between October 1, 2021, and July 31, 2023. Patients with smoldering MM were excluded. Genetic studies (FISH, molecular studies, and karyotyping) were performed. Results: The coho

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39

Fox, R. J., and R. A. Rudick. "Risk stratification and patient counseling for natalizumab in multiple sclerosis." Neurology 78, no. 6 (2012): 436–37. http://dx.doi.org/10.1212/wnl.0b013e318245d2d0.

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40

Mellors, Patrick, Moritz Binder, Rhett P. Ketterling, et al. "Metaphase Cytogenetics for Risk Stratification in Newly Diagnosed Multiple Myeloma." Blood 134, Supplement_1 (2019): 4396. http://dx.doi.org/10.1182/blood-2019-122291.

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Introduction: Abnormal metaphase cytogenetics are associated with inferior survival in newly diagnosed multiple myeloma (MM). These abnormalities are only detected in one third of cases due to the low proliferative rate of plasma cells. It is unknown if metaphase cytogenetics improve risk stratification when using contemporary prognostic models such as the revised international staging system (R-ISS), which incorporates interphase fluorescence in situ hybridization (FISH). Aims: The aims of this study were to 1) characterize the association between abnormalities on metaphase cytogenetics and o

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41

Ariel, Barak, and Justice Tankebe. "Racial stratification and multiple outcomes in police stops and searches." Policing and Society 28, no. 5 (2016): 507–25. http://dx.doi.org/10.1080/10439463.2016.1184270.

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42

Chng, W. J., T.-H. Chung, S. Kumar, et al. "Gene signature combinations improve prognostic stratification of multiple myeloma patients." Leukemia 30, no. 5 (2015): 1071–78. http://dx.doi.org/10.1038/leu.2015.341.

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43

Maura, Francesco, Arjun Raj Rajanna, Andriy Derkach, et al. "Individualized Treatment-Adjusted Risk Stratification in Newly Diagnosed Multiple Myeloma." Blood 140, Supplement 1 (2022): 1561–63. http://dx.doi.org/10.1182/blood-2022-160215.

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44

Rajkumar, S. Vincent. "Multiple myeloma: 2013 update on diagnosis, risk-stratification, and management." American Journal of Hematology 88, no. 3 (2013): 225–35. http://dx.doi.org/10.1002/ajh.23390.

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Rajkumar, S. Vincent. "Multiple myeloma: 2014 Update on diagnosis, risk-stratification, and management." American Journal of Hematology 89, no. 10 (2014): 998–1009. http://dx.doi.org/10.1002/ajh.23810.

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46

Rajkumar, S. Vincent. "Multiple myeloma: 2016 update on diagnosis, risk-stratification, and management." American Journal of Hematology 91, no. 7 (2016): 719–34. http://dx.doi.org/10.1002/ajh.24402.

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Rajkumar, S. Vincent. "Multiple myeloma: 2018 update on diagnosis, risk-stratification, and management." American Journal of Hematology 93, no. 8 (2018): 1091–110. http://dx.doi.org/10.1002/ajh.25117.

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48

Rajkumar, S. Vincent. "Multiple myeloma: 2020 update on diagnosis, risk‐stratification and management." American Journal of Hematology 95, no. 5 (2020): 548–67. http://dx.doi.org/10.1002/ajh.25791.

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Rajkumar, S. Vincent. "Multiple myeloma: 2011 update on diagnosis, risk-stratification, and management." American Journal of Hematology 86, no. 1 (2010): 57–65. http://dx.doi.org/10.1002/ajh.21913.

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Rajkumar, S. Vincent. "Multiple myeloma: 2012 update on diagnosis, risk-stratification, and management." American Journal of Hematology 87, no. 1 (2011): 78–88. http://dx.doi.org/10.1002/ajh.22237.

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