Journal of the Formosan Medical Association
Volume 107, Issue 12, Supplement , Pages S52-S60, December 2008

On Two-stage Seamless Adaptive Design in Clinical Trials

  • Shein-Chung Chow

      Affiliations

    • Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, USA
    • Corresponding Author InformationCorrespondence to: Professor Shein-Chung Chow, Department of Biostatistics and Bioinformatics, Duke University School of Medicine, 2400 Pratt Street, Room 0311 Terrace Level, Durham, NC 27705, USA
    • ,
  • Yi-Hsuan Tu

      Affiliations

    • Department of Statistics, National Cheng Kung University, Tainan, Taiwan

Received 26 July 2008; received in revised form 9 September 2008; accepted 25 September 2008.

Article Outline

In recent years, the use of adaptive design methods in clinical research and development based on accrued data has become very popular because of its efficiency and flexibility in modifying trial and/or statistical procedures of ongoing clinical trials. One of the most commonly considered adaptive designs is probably a two-stage seamless adaptive trial design that combines two separate studies into one single study. In many cases, study endpoints considered in a two-stage seamless adaptive design may be similar but different (e.g. a biomarker versus a regular clinical endpoint or the same study endpoint with different treatment durations). In this case, it is important to determine how the data collected from both stages should be combined for the final analysis. It is also of interest to know how the sample size calculation/allocation should be done for achieving the study objectives originally set for the two stages (separate studies). In this article, formulas for sample size calculation/allocation are derived for cases in which the study endpoints are continuous, discrete (e.g. binary responses), and contain time-to-event data assuming that there is a well-established relationship between the study endpoints at different stages, and that the study objectives at different stages are the same. In cases in which the study objectives at different stages are different (e.g. dose finding at the first stage and efficacy confirmation at the second stage) and when there is a shift in patient population caused by protocol amendments, the derived test statistics and formulas for sample size calculation and allocation are necessarily modified for controlling the overall type I error at the prespecified level.

Key Words:  adaptation , adaptive dose-escalation trial , adaptive seamless phase II/III trial , moving target patient population , protocol amendments

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References 

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PII: S0929-6646(09)60009-7

doi:10.1016/S0929-6646(09)60009-7

Journal of the Formosan Medical Association
Volume 107, Issue 12, Supplement , Pages S52-S60, December 2008

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