Literature DB >> 28966722

Group Sequential Survival Trial Design and Monitoring Using the Log-Rank Test.

Jianrong Wu1, Xiaoping Xiong1.   

Abstract

For randomized group sequential survival trial designs with unbalanced treatment allocation, the widely used Schoenfeld formula is inaccurate, and the commonly used information time as the ratio of number of events at interim look to the number of events at the end of trial can be biased. In this paper, a sample size formula for the two-sample log-rank test under the proportional hazards model is proposed that provides more accurate sample size calculation for unbalanced survival trial designs. Furthermore, a new information time is introduced for the sequential survival trials such that the new information time is more accurate than the traditional information time when the allocation of enrollments is unbalanced in groups. Finally, we demonstrate the monitoring process using the sequential conditional probability ratio test and compare it with two other well known group sequential procedures. An example is given to illustrate unbalanced survival trial design using available software.

Entities:  

Keywords:  group sequential trial design; information time; log-rank test; proportional hazards model; sample size; time-to-event; unequal allocation

Year:  2017        PMID: 28966722      PMCID: PMC5619877          DOI: 10.1080/19466315.2016.1189355

Source DB:  PubMed          Journal:  Stat Biopharm Res        ISSN: 1946-6315            Impact factor:   1.452


  16 in total

1.  Designing complex group sequential survival trials.

Authors:  Edward Lakatos
Journal:  Stat Med       Date:  2002-07-30       Impact factor: 2.373

2.  Sample size determination for comparing several survival curves with unequal allocations.

Authors:  Susan Halabi; Bahadur Singh
Journal:  Stat Med       Date:  2004-06-15       Impact factor: 2.373

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Authors:  K K Lan; D M Zucker
Journal:  Stat Med       Date:  1993-04-30       Impact factor: 2.373

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Authors:  J Whitehead; I Stratton
Journal:  Biometrics       Date:  1983-03       Impact factor: 2.571

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

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Authors:  P C O'Brien; T R Fleming
Journal:  Biometrics       Date:  1979-09       Impact factor: 2.571

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Journal:  Br J Radiol       Date:  1971-10       Impact factor: 3.039

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Authors:  K K Lan; J M Lachin
Journal:  Biometrics       Date:  1990-09       Impact factor: 2.571

9.  Evaluation of sample size and power for analyses of survival with allowance for nonuniform patient entry, losses to follow-up, noncompliance, and stratification.

Authors:  J M Lachin; M A Foulkes
Journal:  Biometrics       Date:  1986-09       Impact factor: 2.571

10.  Evaluation of sample size and power for multi-arm survival trials allowing for non-uniform accrual, non-proportional hazards, loss to follow-up and cross-over.

Authors:  F M-S Barthel; A Babiker; P Royston; M K B Parmar
Journal:  Stat Med       Date:  2006-08-15       Impact factor: 2.373

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  1 in total

1.  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

  1 in total

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