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POS1050 INCIDENCE RATES OF INTERSTITIAL LUNG DISEASE AMONG PATIENTS WITH RHEUMATOID ARTHRITIS TREATED WITH ABATACEPT: A POST HOC POOLED ANALYSIS FROM A COMPENDIUM OF CLINICAL TRIALS

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Annals of the Rheumatic Diseases 2023年 82卷 843-843页

作者： P. Dieudé J. Sparks A. Fischer L. Chen K. Lozenski S. Dahan M. Chaballa W. Little Paris Cité University Bichat Hospital APHP Department of Rheumatology Paris France Brigham and Women's Hospital Harvard Medical School Division of Rheumatology Inflammation and Immunity Boston United States of America Bristol Myers Squibb Lung Fibrosis Lawrenceville United States of America Syneos Health Biostatistics and Statistical Programming Richmond Canada Bristol Myers Squibb Rheumatology Pipeline and Early Assets Lawrenceville United States of America Bristol Myers Squibb Worldwide Medical Lawrenceville United States of America Bristol Myers Squibb US Medical Immunology and Fibrosis Lawrenceville United States of America Bristol Myers Squibb Worldwide Rheumatology Lawrenceville United States of America

Background Interstitial lung disease (ILD) is a recognized complication of RA. Prior studies have suggested stabilization or improvement of ILD in patients with RA (RA-ILD) treated with abatacept. [1,2] Few studies have evaluated the background incidence rate of RA-ILD. Objectives To determine the incidence rate of clinically significant ILD in a cohort of patients with RA receiving abatacept + MTX versus placebo + MTX from multiple clinical trials. Methods This retrospective analysis examined pooled safety data from ten phase 3 clinical trials of patients with RA treated with background MTX in combination with abatacept or placebo. The term ‘interstitial lung’ was used to identify incidences of ILD reported as AEs in the safety data. The exposure period for each patient was censored at first incidence of clinically significant ILD, 56 days after last study drug administration, or 1 day prior to commencement of another study drug, whichever occurred first. Poisson regression models were used to estimate crude incidence rates per 100 person-years for baseline risk factors within treatment groups, and to estimate incidence rate ratios for the placebo + MTX versus abatacept + MTX treatment groups. Disease activity parameters, DAS28 (CRP) and HAQ-DI, were estimated from baseline to the time of ILD diagnosis (as reported by AEs). Results In total, 3,708 patients (10,521 person-years) treated with abatacept + MTX and 999 patients (938 person-years) treated with placebo + MTX were included. Patients treated with placebo + MTX had a higher incidence rate of ILD per 100 person-years (95% CI) versus those treated with abatacept + MTX (0.43 [0.16–1.14] vs 0.10 [0.05–0.18], respectively; Figure 1). The incidence rate ratio of placebo + MTX versus abatacept + MTX treatment groups for the total population was 4.49 (95% CI, 1.23–13.42). For all subpopulations stratified by baseline risk factors (where ≥ 1 patient in each treatment group had an ILD event), incidence rate ratios wer

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9O Phase I/II, open-label, first-in-human study of the anti-GPC3 T cell engager SAR444200 in patients with advanced solid tumors: Updated safety and pharmacokinetic analysis

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ESMO Open 2025年 10卷 104165-104165页

作者： Almhanna, K. Hong, J.Y. Chenard-Poirier, M. Ryoo, B-Y. Lim, D.W-T. El-Khoueiry, A.B. Goh, B-C. Samol, J. Kefsi, A. Perez, R. Meng, R. Masciari, S. Abbadessa, G. Guillemin-Paveau, H. Lepine, L. Zhang, Y. Dumbrava, E.E. Medical Oncology Warren Alpert Medical School of Brown University Providence United States of America Hematology-Oncology Samsung Medical Center (SMC) Seoul Republic of Korea Gastrointestinal Cancer Unit Centre Intégré de Cancérologie - Chu de Québec Québec Canada Department of Oncology Asan Medical Center - University of Ulsan Seoul Republic of Korea Medical Oncology Department NCCS - National Cancer Centre Singapore Medical Oncology Division USC - Kenneth J. Norris Jr. Comprehensive Cancer Center Los Angeles United States of America Hematology-Oncology NCIS - National University Cancer Institute Singapore Singapore Medical Oncology Department National Healthcare Group - Tan Tock Seng Hospital Singapore Oncology Early Development Sanofi Vitry-sur-Seine France Immuno Modulatory Agents-Early Development Sanofi Bridgewater United States of America Research and Development Department Sanofi Cambridge United States of America Early Development in Oncology Sanofi Cambridge United States of America Oncology Early Development Sanofi Cambridge United States of America Pharmacokinetics/Pharmacodynamics VA Sanofi Vitry-sur-Seine France Pharmacokinetics Dynamics and Metabolism Sanofi Vitry-sur-Seine France Department of Biostatistics and Programming Sanofi Cambridge United States of America Investigational Cancer Therapeutics Department The University of Texas MD Anderson Cancer Center - Main Building Houston United States of America

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Imbalanced randomization in clinical trials

arXiv

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arXiv 2018年

作者： Chandereng, Thevaa Wei, Xiaodan Chappell, Rick Department of Statistics University of Wisconsin-Madison WI United States Department of Biostatistics & Medical Informatics University of Wisconsin-Madison WI United States Morgridge Institute of Research WI United States Biostatistics and Programming Sanofi BridgewaterNJ United States

Randomization is a common technique used in clinical trials to eliminate potential bias and confounders in a patient population. Equal allocation to treatment groups is the standard due to its optimal efficiency in many cases. However, in certain scenarios, unequal allocation can improve efficiency. In superiority trials with more than two groups, the optimal randomization is not always a balanced randomization. In non-inferiority trials, additive margin with equal variance is the only instance with balanced randomization. Optimal randomization for non-inferiority trials can be far from 1:1 and can greatly improve efficiency, a fact which is commonly overlooked. A tool for sample size calculation for non-inferiority trials with additive or multiplicative margin with normal, binomial or Poisson distribution is available at http://***/shiny/SSNI/. Copyright © 2018, The Authors. All rights reserved.

关键词： Efficiency

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A Family-based graphical approach for testing hierarchically ordered families of hypotheses

arXiv

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arXiv 2018年

作者： Qiu, Zhiying Yu, Li Guo, Wenge Biostatistics and Programming Sanofi BridgewaterNJ08807 United States Department of Mathematical Sciences New Jersey Institute of Technology NewarkNJ07102 United States

In applications of clinical trials, tested hypotheses are often grouped as multiple hierarchically ordered families. To test such structured hypotheses, various gatekeeping strategies have been developed in the literature, such as series gatekeeping, parallel gatekeeping, tree-structured gatekeeping strategies, etc. However, these gatekeeping strategies are often either non-intuitive or less flexible when addressing increasingly complex logical relationships among families of hypotheses. In order to overcome the issue, in this paper, we develop a new family-based graphical approach, which can easily derive and visualize different gatekeeping strategies. In the proposed approach, a directed and weighted graph is used to represent the generated gatekeeping strategy where each node corresponds to a family of hypotheses and two simple updating rules are used for updating the critical value of each family and the transition coefficient between any two families. Theoretically, we show that the proposed graphical approach strongly controls the overall familywise error rate at a pre-specified level. Through some case studies and a real clinical example, we demonstrate simplicity and flexibility of the proposed *** Codes 62J15 Copyright © 2018, The Authors. All rights reserved.

关键词： Directed graphs

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Considerations on trial design and data analysis for multi-regional clinical trials

Considerations on trial design and data analysis for multi-r...

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2017第七届临床评价方法与应用国际研讨会暨生物统计国际研讨会

作者： Hui Quan Biostatistics and Programming Department of Sanofi

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1411P Tusamitamab ravtansine plus ramucirumab as 2L therapy or beyond in patients with metastatic NSq NSCLC and high CEACAM5 expression (CARMEN-LC04)

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Annals of Oncology 2023年 34卷 S807-S807页

作者： G.K. Dy B.C. Cho J. Oliveira M.D. Isla Casado A. Blasco Cordellat M. Zemanova J. Roubec L. Vila Martinez L. Charbonnier C. Soufflet J. de Castro Carpeño Department of Medicine Roswell Park Comprehensive Cancer Center Buffalo NY USA Division of Medical Oncology Yonsei Cancer Center Yonsei University College of Medicine Seoul Republic of Korea Medical Oncology Service Early Phase Clinical Trial Unit-IPO Porto/RISE@CI-IPOP (Health Research Network Experimental Pathology and Therapeutics Group Research Center (CI-IPOP)/RISE@CI-IPOP (Health Research Network) Portuguese Oncology Institute of Porto (IPO Porto)/Porto Comprehensive Cancer Center Porto Portugal Medical Oncology Department Hospital Clínico Universitario Lozano Blesa Zaragoza Spain Medical Oncology Department Hospital General de Valencia Valencia Spain Department of Oncology First Faculty of Medicine Charles University and General University Hospital in Prague Prague Czech Republic Pneumooncology Nemocnice AGEL Ostrava-Vítkovice Ostrava-Vítkovice Czech Republic Oncology Department Consorci Corporació Sanitària Parc Taulí de Sabadell Sabadell Spain Biostatistics & Programming Sanofi Chilly-Mazarin France Clinical Development Sanofi Vitry-sur-Seine France Medical Oncology Service Hospital Universitario La Paz Madrid Spain

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P0054 - An integrated analysis of the efficacy of desvenlafaxine succinate compared with placebo in the treatment of major depressive disorder

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European Psychiatry 2020年第S2期23卷 S208-S208页

作者： M.E. Thase S.G. Kornstein R. Tummala J.M. Germain Q. Jiang S. Ahmed P.T. Ninan Department of Psychiatry Mood and Anxiety Disorders Treatment and Research Program University of Pennsylvania Philadelphia PA USA Department of Psychiatry and Obstetrics and Gynecology Mood Disorders Institute and The Institute for Womens Health Virginia Commonwealth University School of Medicine Virginia Commonwealth University Richmond VA USA Department of Global Medical Affairs Wyeth Research Collegeville PA USA Department of Neuroscience Wyeth Research Paris France Department of Global Biostatistics and Programming Wyeth Research Collegeville PA USA

Objective:To assess the efficacy of desvenlafaxine succinate (DVS) treatment in patients with major depressive disorder (MDD).Methods:Seven randomized, double-blind, placebo-controlled, short-term studies were pooled to evaluate the efficacy of DVS in MDD. Adult outpatients with DSM-IV MDD were enrolled in all studies. Eligible patients were randomly assigned to DVS (n=1186) at doses of 100–400 mg/d, or placebo (n=797) for 8 weeks. The 17-item Hamilton Depression Rating Scale (HAM-D17) was the primary efficacy variable. Other efficacy variables were the Clinical Global Impressions scale (CGI), HAM-D6, Montgomery Åsberg Depression Rating Scale (MADRS), Covi Anxiety scale, Sheehan Disability Scale (SDS), WHO-5 Well-Being Index, and the Visual Analog Scale–Pain Intensity (VAS-PI). A mixed-effect model for repeated measures (MMRM) analysis was used to analyze continuous variables. Logistic regression was used to analyze response and remission ***:An adjusted mean difference of –2.8 points on HAM-D17 total score at end point for DVS vs placebo (95% confidence limits: –2.2, –3.4; P<0.001) was demonstrated. Response and remission rates were significantly elevated for DVS-treated patients compared with placebo (P<0.001) across rating scales (HAM-D17, MADRS, and CGI). For other secondary measures at end point, including the CGI, HAM-D6, MADRS, Covi, SDS, WHO-5, and VAS-PI, significant differences from placebo were also observed. No additional benefit was observed for DVS doses above 100 mg/d in analyses of fixed-dose ***:DVS was efficacious in treating MDD based on standard depression rating scales and measures of anxiety, global severity/improvement, functioning, well being, and pain.

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EFFICACY AND SAFETY OF EXPERIMENTAL CHIMERIC ANTIGEN RECEPTOR (CAR) T-CELLS VERSUS AXICABTAGENE CILOLEUCEL (YESCARTA) FOR THE TREATMENT OF RELAPSED/REFRACTORY LARGE B-CELL LYMPHOMA: MATCHING ADJUSTED INDIRECT COMPARISONS AND SYSTEMATIC REVIEW

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Hematology, Transfusion and Cell Therapy 2021年 43卷 S256-S256页

作者： B Weinstein B Muresan S Solano AV Macedo Y Lee Y Su Y Ahn C Camargo G Kim D Carpenter Department of Environmental Health Sciences School of Public Health University at Albany Rensselaer United Kingdom Health Sciences Unit University of Groningen University Medical Center Groningen Groningen The Netherlands Principles and Practice of Clinical Research (PPCR) Program ECPE Harvard T.H. Chan School of Public Health Boston United Kingdom Hematology Clinic Hospital da Polícia Militar Belo Horizonte MG Brazil Department of Pharmaceutical Sciences School of Pharmacy Texas Tech University Health Sciences Center Amarillo United Kingdom Inari Medical Biostatistics and Programming Department Irvine United Kingdom Department of Plastic Surgery Faculdade de Medicina Universidade de São Paulo (FMUSP) São Paulo SP Brazil Institute of Experimental and Clinical Pharmacology and Toxicology Faculty of Medicine University of Freiburg Freiburg Germany Institute for Health and the Environment University at Albany Rensselaer United Kingdom

Introduction Despite the high response rates seen with Chimeric Antigen Receptor (CAR) T-cell therapy for relapsed/refractory Large B-cell lymphoma (R/R LBCL), post-therapy relapse remains a key challenge. To date, no study has evaluated the comparative efficacy and safety of experimental CAR T-cell products versus currently approved CAR T-cell therapies. Objective To indirectly compare the efficacy and safety of novel, experimental CAR T-cell products against the first FDA-approved CAR T-cell construct, Axicabtagene ciloleucel (Yescarta). Methods In compliance with the PRISMA guidelines, we performed a systematic review, which identified 16 independent, early-phase clinical trials consisting of 193 LBCL patients with individual patient data (IPD). We categorized eight pooled populations based on the target antigens (CD19, CD20), co-stimulatory domains (CD28, 4-1BB), and CAR T-cells administered with or without concomitant autologous stem cell transplant (ASCT). The pooled populations were categorized as follows: (1) dual targeting strategies, such as tandem ***20, n = 28; (2) co-infusion of CD19 and CD20 CARs, n = 21; (3) third-generation CARs, n = 26; (4) CD19 CARs with modified constructs for reduced toxicity, including ***.86, n = 21; and (5) ***828Z, n = 14; (6) CD19. 4-1BB.S manufactured in China, n = 24; (7) concomitant ASCT and ***28, n = 45; and (8) CD20 CARs with a 4-1BB co-stimulatory domain, n = 14. A Matching Adjusted Indirect Comparison (MAIC) statistical technique was applied to account for heterogeneity in the study population across trials. Estimates for the experimental CAR T-cell trials were adjusted using patient-level data to match the ZUMA-1 (Yescarta, n = 108) study population based on mutually reported key baseline covariates, including age, disease stage, histology, refractoriness, number of prior lines of therapy, and extranodal disease. The study endpoints for this study included progression-free survival (PFS), cytokine r

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K-groups: A generalization of k-means clustering

arXiv

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arXiv 2017年

作者： Li, Songzi Rizzo, Maria L. Biostatistics and Programming Department Pharmaceutical Product Deparment LLC WilmingtonNC28401 Dept. of Mathematics & Statistics Bowling Green State University Bowling GreenOH43403 United States

We propose a new class of distribution-based clustering algorithms, called k-groups, based on energy distance between samples. The energy distance clustering criterion assigns observations to clusters according to a multi-sample energy statistic that measures the distance between distributions. The energy distance determines a consistent test for equality of distributions, and it is based on a population distance that characterizes equality of distributions. The k-groups procedure therefore generalizes the k-means method, which separates clusters that have different means. We propose two k-groups algorithms: k-groups by first variation;and k-groups by second variation. The implementation of k-groups is partly based on Hartigan and Wong's algorithm for k-means. The algorithm is generalized from moving one point on each iteration (first variation) to moving m (m > 1) points. For univariate data, we prove that Hartigan and Wong's k-means algorithm is a special case of k-groups by first variation. The simulation results from univariate and multivariate cases show that our k-groups algorithms perform as well as Hartigan and Wong's k-means algorithm when clusters are well-separated and normally distributed. Moreover, both k-groups algorithms perform better than k-means when data does not have a finite first moment or data has strong skewness and heavy tails. For non-spherical clusters, both k-groups algorithms performed better than k-means in high dimension, and k-groups by first variation is consistent as dimension increases. In a case study on dermatology data with 34 features, both k-groups algorithms performed better than k-means. Copyright © 2017, The Authors. All rights reserved.

关键词： Cluster analysis

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277MO SAR439859, an oral selective estrogen receptor (ER) degrader (SERD), in ER+/ HER2- metastatic breast cancer (mBC): Biomarker analyses from a phase I/II study

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Annals of Oncology 2020年 31卷 S351-S351页

作者： S. Chandarlapaty A. Bardia S. Lord H. Linden V. Pelekanou N. Ternes J. Ming V. Boutet E. Boitier A. Gosselin J. Sang Lee W. Dos-Santos Bele A. Protopopov M. Celanovic A-L. Bauchet M. Campone Medicine Memorial Sloan Kettering Cancer Center New York NY USA Medical Oncology Massachusetts General Hospital Harvard Medical School Boston MA USA Department of Oncology University of Oxford Churchill Hospital Oxford UK Department of Medicine University of Washington Medical Center Seattle WA USA Clinical Precision Oncology-Tranlsational Medicine Early Development Sanofi Cambridge MA USA Biostatistics and Programming Sanofi Paris France Oncology Sanofi Bridgewater NJ USA TMED & Biomarkers & Clinical Bioanalyses Sanofi Paris France Precision Oncology Sanofi Cambridge MA USA Molecular Profiling Precision Oncology Sanofi Paris France Oncology-OMD Sanofi Cambridge MA USA Medical Oncology Institut de Cancérologie de l'Ouest Saint-Herblain France

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