Literature DB >> 16022174

Two-stage adaptive design for clinical trials with survival data.

Gang Li1, Weichung J Shih, Yining Wang.   

Abstract

In long-term clinical trials we often need to monitor the patients' enrollment, compliance, and treatment effect during the study. In this paper we take the conditional power approach and consider a two-stage design based on the ideas of Li et al. (2002) for trials with survival endpoints. We make projections and decisions regarding the future course of the trial from the interim data. The decision includes possible early termination of the trial for convincing evidence of futility or efficacy, and projection includes how many additional patients are needed to enroll and how long the enrollment and follow-up may be when continuing the trial. The flexibility of the adaptive design is demonstrated by an example, the Coumadin Aspirin Reinfarction Study.

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Year:  2005        PMID: 16022174     DOI: 10.1081/BIP-200062293

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


  3 in total

1.  Design and analysis of clinical trials in the presence of delayed treatment effect.

Authors:  Tony Sit; Mengling Liu; Michael Shnaidman; Zhiliang Ying
Journal:  Stat Med       Date:  2016-02-02       Impact factor: 2.373

2.  A practical simulation method to calculate sample size of group sequential trials for time-to-event data under exponential and Weibull distribution.

Authors:  Zhiwei Jiang; Ling Wang; Chanjuan Li; Jielai Xia; Hongxia Jia
Journal:  PLoS One       Date:  2012-09-05       Impact factor: 3.240

3.  A review and re-interpretation of a group-sequential approach to sample size re-estimation in two-stage trials.

Authors:  J Bowden; A Mander
Journal:  Pharm Stat       Date:  2014-04-02       Impact factor: 1.894

  3 in total

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