Two-Stage Adaptive Design for Clinical Trials with Survival Data

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.

[1]  J. Bigger,et al.  Changes in sample size and length of follow-up to maintain power in the coronary artery bypass graft (CABG) patch trial. , 1998, Controlled clinical trials.

[2]  P. Bauer,et al.  Evaluation of experiments with adaptive interim analyses. , 1994, Biometrics.

[3]  J. Wittes On changing a long‐term clinical trial midstream , 2002, Statistics in medicine.

[4]  K. K. Lan,et al.  Discrete sequential boundaries for clinical trials , 1983 .

[5]  T. Cook,et al.  Methods for mid‐course corrections in clinical trials with survival outcomes , 2003, Statistics in medicine.

[6]  D. Zucker,et al.  Internal pilot studies II: comparison of various procedures. , 1999, Statistics in medicine.

[7]  Coumadin Aspirin Reinfarction Study Investigators Randomised double-blind trial of fixed low-dose warfarin with aspirin after myocardial infarction , 1997, The Lancet.

[8]  W. Shih Sample size re‐estimation – journey for a decade , 2001, Statistics in medicine.

[9]  Zhiliang Ying,et al.  Towards a general asymptotic theory for Cox model with staggered entry , 1997 .

[10]  Zhiliang Ying,et al.  A General Theory on Stochastic Curtailment for Censored Survival Data , 1999 .

[11]  M A Proschan,et al.  Designed extension of studies based on conditional power. , 1995, Biometrics.

[12]  F E Young,et al.  The preliminary report of the findings of the aspirin component of the ongoing Physicians' Health Study. The FDA perspective on aspirin for the primary prevention of myocardial infarction. , 1988, JAMA.

[13]  J. Elashoff,et al.  Two-stage clinical trial stopping rules. , 1984, Biometrics.

[14]  A. Tsiatis,et al.  On the inefficiency of the adaptive design for monitoring clinical trials , 2003 .

[15]  W. Shih,et al.  A sample size adjustment procedure for clinical trials based on conditional power. , 2002, Biostatistics.

[16]  Zhenming Shun,et al.  Sample Size Reestimation in Clinical Trials , 2001 .

[17]  T. Cook Adjusting survival analysis for the presence of unadjudicated study events. , 2000, Controlled clinical trials.

[18]  Sue-Jane Wang,et al.  Modification of Sample Size in Group Sequential Clinical Trials , 1999, Biometrics.

[19]  W J Shih,et al.  Modifying the design of ongoing trials without unblinding. , 1998, Statistics in medicine.

[20]  L Fisher,et al.  Statistical Inference for Self‐Designing Clinical Trials with a One‐Sided Hypothesis , 1999, Biometrics.

[21]  J. Cui,et al.  Nonparametric Estimation of a Delay Distribution Based on Left‐Censored and Right‐Truncated Data , 1999, Biometrics.

[22]  J M Lachin,et al.  Evaluation of sample size and power for analyses of survival with allowance for nonuniform patient entry, losses to follow-up, noncompliance, and stratification. , 1986, Biometrics.

[23]  Weichung Joe Shih,et al.  Group sequential, sample size re‐estimation and two‐stage adaptive designs in clinical trials: a comparison , 2006, Statistics in medicine.

[24]  J. Buring,et al.  Methodologic considerations in the design and conduct of randomized trials: the U.S. Physicians' Health Study. , 1989, Controlled clinical trials.

[25]  P. O'Brien,et al.  A multiple testing procedure for clinical trials. , 1979, Biometrics.