Literature DB >> 23307913

A logrank test-based method for sizing clinical trials with two co-primary time-to-event endpoints.

Tomoyuki Sugimoto1, Takashi Sozu, Toshimitsu Hamasaki, Scott R Evans.   

Abstract

We discuss sample size determination for clinical trials evaluating the joint effects of an intervention on two potentially correlated co-primary time-to-event endpoints. For illustration, we consider the most common case, a comparison of two randomized groups, and use typical copula families to model the bivariate endpoints. A correlation structure of the bivariate logrank statistic is specified to account for the correlation among the endpoints, although the between-group comparison is performed using the univariate logrank statistic. We propose methods to calculate the required sample size to compare the two groups and evaluate the performance of the methods and the behavior of required sample sizes via simulation.

Keywords:  Bivariate dependence; Censored data; Copula model; Logrank statistic; Power

Mesh:

Substances:

Year:  2013        PMID: 23307913      PMCID: PMC4148615          DOI: 10.1093/biostatistics/kxs057

Source DB:  PubMed          Journal:  Biostatistics        ISSN: 1465-4644            Impact factor:   5.899


  10 in total

1.  Comparing sample size formulae for trials with unbalanced allocation using the logrank test.

Authors:  F Y Hsieh
Journal:  Stat Med       Date:  1992-06-15       Impact factor: 2.373

2.  A convenient formula for sample size calculations in clinical trials with multiple co-primary continuous endpoints.

Authors:  Tomoyuki Sugimoto; Takashi Sozu; Toshimitsu Hamasaki
Journal:  Pharm Stat       Date:  2012 Mar-Apr       Impact factor: 1.894

3.  Sample size determination in clinical trials with multiple co-primary binary endpoints.

Authors:  Takashi Sozu; Tomoyuki Sugimoto; Toshimitsu Hamasaki
Journal:  Stat Med       Date:  2010-09-20       Impact factor: 2.373

4.  Method of balanced adjustment in testing co-primary endpoints.

Authors:  George Kordzakhia; Ohidul Siddiqui; Mohammad F Huque
Journal:  Stat Med       Date:  2010-08-30       Impact factor: 2.373

5.  Some controversial multiple testing problems in regulatory applications.

Authors:  H M James Hung; Sue-Jane Wang
Journal:  J Biopharm Stat       Date:  2009       Impact factor: 1.051

6.  An asymptotic analysis of the logrank test.

Authors:  R L Strawderman
Journal:  Lifetime Data Anal       Date:  1997       Impact factor: 1.588

7.  Inferences on the association parameter in copula models for bivariate survival data.

Authors:  J H Shih; T A Louis
Journal:  Biometrics       Date:  1995-12       Impact factor: 2.571

8.  Tables of the number of patients required in clinical trials using the logrank test.

Authors:  L S Freedman
Journal:  Stat Med       Date:  1982 Apr-Jun       Impact factor: 2.373

9.  Power and sample size for clinical trials when efficacy is required in multiple endpoints: application to an Alzheimer's treatment trial.

Authors:  Chengjie Xiong; Kai Yu; Feng Gao; Yan Yan; Zhengjun Zhang
Journal:  Clin Trials       Date:  2005       Impact factor: 2.486

10.  Sample size determination for clinical trials with co-primary outcomes: exponential event times.

Authors:  Toshimitsu Hamasaki; Tomoyuki Sugimoto; Scott Evans; Takashi Sozu
Journal:  Pharm Stat       Date:  2012-10-19       Impact factor: 1.894

  10 in total
  10 in total

Review 1.  Design, data monitoring, and analysis of clinical trials with co-primary endpoints: A review.

Authors:  Toshimitsu Hamasaki; Scott R Evans; Koko Asakura
Journal:  J Biopharm Stat       Date:  2017-10-30       Impact factor: 1.051

2.  Group-Sequential Strategies in Clinical Trials with Multiple Co-Primary Outcomes.

Authors:  Toshimitsu Hamasaki; Koko Asakura; Scott R Evans; Tomoyuki Sugimoto; Takashi Sozu
Journal:  Stat Biopharm Res       Date:  2015       Impact factor: 1.452

3.  Sample size determination in group-sequential clinical trials with two co-primary endpoints.

Authors:  Koko Asakura; Toshimitsu Hamasaki; Tomoyuki Sugimoto; Kenichi Hayashi; Scott R Evans; Takashi Sozu
Journal:  Stat Med       Date:  2014-03-27       Impact factor: 2.373

4.  Group-sequential logrank methods for trial designs using bivariate non-competing event-time outcomes.

Authors:  Tomoyuki Sugimoto; Toshimitsu Hamasaki; Scott R Evans; Susan Halabi
Journal:  Lifetime Data Anal       Date:  2019-04-12       Impact factor: 1.588

5.  Sizing clinical trials when comparing bivariate time-to-event outcomes.

Authors:  Tomoyuki Sugimoto; Toshimitsu Hamasaki; Scott R Evans; Takashi Sozu
Journal:  Stat Med       Date:  2017-01-24       Impact factor: 2.373

6.  Sample Size Considerations in Clinical Trials when Comparing Two Interventions using Multiple Co-Primary Binary Relative Risk Contrasts.

Authors:  Yuki Ando; Toshimitsu Hamasaki; Scott R Evans; Koko Asakura; Tomoyuki Sugimoto; Takashi Sozu; Yuko Ohno
Journal:  Stat Biopharm Res       Date:  2015-06-24       Impact factor: 1.452

7.  Interim evaluation of efficacy or futility in group-sequential trials with multiple co-primary endpoints.

Authors:  Koko Asakura; Toshimitsu Hamasaki; Scott R Evans
Journal:  Biom J       Date:  2016-10-19       Impact factor: 2.207

8.  Interim Monitoring for Futility in Clinical Trials with Two Co-primary Endpoints Using Prediction.

Authors:  Koko Asakura; Scott R Evans; Toshimitsu Hamasaki
Journal:  Stat Biopharm Res       Date:  2019-11-04       Impact factor: 1.452

Review 9.  Clinical end points for drug treatment trials in BCR-ABL1-negative classic myeloproliferative neoplasms: consensus statements from European LeukemiaNET (ELN) and Internation Working Group-Myeloproliferative Neoplasms Research and Treatment (IWG-MRT).

Authors:  G Barosi; A Tefferi; C Besses; G Birgegard; F Cervantes; G Finazzi; H Gisslinger; M Griesshammer; C Harrison; R Hehlmann; S Hermouet; J-J Kiladjian; N Kröger; R Mesa; M F Mc Mullin; A Pardanani; F Passamonti; J Samuelsson; A M Vannucchi; A Reiter; R T Silver; S Verstovsek; G Tognoni; T Barbui
Journal:  Leukemia       Date:  2014-08-25       Impact factor: 11.528

10.  Sample size estimation using a latent variable model for mixed outcome co-primary, multiple primary and composite endpoints.

Authors:  Martina E McMenamin; Jessica K Barrett; Anna Berglind; James M S Wason
Journal:  Stat Med       Date:  2022-02-23       Impact factor: 2.497

  10 in total

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