Literature DB >> 24138439

Selection of hypothesis weights and ordering when testing multiple hypotheses in clinical trials.

Brian L Wiens1, Alex Dmitrienko, Olga Marchenko.   

Abstract

This article discusses the problem of selecting free parameters of multiple testing procedures in confirmatory Phase III clinical trials with multiple objectives, including hypothesis weights and hypothesis ordering. We identify classes of multiple testing procedures that provide different interpretations of these parameters. This includes basic single-step procedures (Bonferroni procedure) that employ fixed hypothesis weights, as well as more powerful stepwise procedures (Holm, fallback, and chain procedures) that reweight the hypotheses during the testing process. We examine the behavior of different classes of multiple testing procedures in problems with unequally weighted hypotheses and a priori ordered hypotheses and provide practical guidelines for the choice of hypothesis weights and hypothesis ordering. The concepts discussed in the article are illustrated using case studies based on clinical trials with multiple endpoints, multiple dose-placebo comparisons, and multiple patient populations.

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Year:  2013        PMID: 24138439     DOI: 10.1080/10543406.2013.834920

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  5 in total

1.  Post Genome-Wide Gene-Environment Interaction Study Using Random Survival Forest: Insulin Resistance, Lifestyle Factors, and Colorectal Cancer Risk.

Authors:  Su Yon Jung; Jeanette C Papp; Eric M Sobel; Zuo-Feng Zhang
Journal:  Cancer Prev Res (Phila)       Date:  2019-09-25

2.  Pro-inflammatory cytokine polymorphisms in ONECUT2 and HNF4A and primary colorectal carcinoma: a post genome-wide gene-lifestyle interaction study.

Authors:  Su Yon Jung; Jeanette C Papp; Eric M Sobel; Matteo Pellegrini; Herbert Yu; Zuo-Feng Zhang
Journal:  Am J Cancer Res       Date:  2020-09-01       Impact factor: 6.166

3.  Post genome-wide gene-environment interaction study: The effect of genetically driven insulin resistance on breast cancer risk using Mendelian randomization.

Authors:  Su Yon Jung; Nicholas Mancuso; Jeanette Papp; Eric Sobel; Zuo-Feng Zhang
Journal:  PLoS One       Date:  2019-06-27       Impact factor: 3.240

4.  Pro-inflammatory cytokine polymorphisms and interactions with dietary alcohol and estrogen, risk factors for invasive breast cancer using a post genome-wide analysis for gene-gene and gene-lifestyle interaction.

Authors:  Su Yon Jung; Jeanette C Papp; Eric M Sobel; Matteo Pellegrini; Herbert Yu; Zuo-Feng Zhang
Journal:  Sci Rep       Date:  2021-01-13       Impact factor: 4.379

5.  Genome-wide Association Analysis of Proinflammatory Cytokines and Gene-lifestyle Interaction for Invasive Breast Cancer Risk: The WHI dbGaP Study.

Authors:  Su Yon Jung; Peter A Scott; Jeanette C Papp; Eric M Sobel; Matteo Pellegrini; Herbert Yu; Sihao Han; Zuo-Feng Zhang
Journal:  Cancer Prev Res (Phila)       Date:  2020-09-14
  5 in total

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