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Statistical Inference after an Adaptive Group Sequential Design: A Case Study

  • Biostatistics
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Abstract

The adaptive group sequential design of Lehmacher and Wassmer allows fully flexible redetermination of sample size after each of a predetermined number of interim looks. Study 02CLLIII, a large, randomized, multicenter trial in chronic lymphocytic leukemia, was based on this approach, with five planned analyses. The study terminated for efficacy at the third interim analysis. While it was clear how statistical significance was to be determined, calculations of proper P values as well as point and interval estimates turned out to be much less straightforward. We extend existing analysis approaches to the stratified binary and time-to-event data from this trial, investigate the properties of the estimators for the primary endpoint, and highlight remaining issues with full statistical inference after such a design. In conclusion, the flexibility offered by the adaptive features renders statistical inference more difficult and less precise. We believe that there are situations where it may be worth paying this price.

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References

  1. Pocock SJ. Clinical Trials: A Practical Approach. New York: Wiley; 1983.

    Google Scholar 

  2. Lan KKG, DeMets DL. Discrete sequential boundaries for clinical trials. Biomeirika. 1983;70:659–663.

    Article  Google Scholar 

  3. Jennison C, Turnbull BW. Group Sequential Methods With Applications to Clinical Trials. Boca Raton, FL: Chapman & Hall/CRC; 2000.

    Google Scholar 

  4. Proschan MA, Hunsberger SA. Designed extension of studies based on conditional power. Biometrics. 1995;51:1315–1324.

    Article  CAS  Google Scholar 

  5. Lehmacher W. Wassmer G. Adaptive sample size calculations in group sequential trials. Biometrics. 1999;55:1286–1290.

    Article  CAS  Google Scholar 

  6. Knauf WU, Lissichkov T. Aldaoud A. et al. Phase III randomized study of bendamustine versus chlorambucil in previously untreated patients with chronic lymphocytic leukemia. J Clin Oncol. 2009;27:4378–4384.

    Article  CAS  Google Scholar 

  7. Fleming TR, Richardson BA. Some design issues in microbicide HIV prevention trials. J Infect Dis. 2004;190:666–674.

    Article  CAS  Google Scholar 

  8. Insightful. S+ SeqTrial 2 User’s Guide. Insightful Corp.; 2002.

  9. Whitehead J. On the bias of maximum likelihood estimation following a sequential test. Biometrika. 1986;73: 573–581.

    Article  Google Scholar 

  10. Emerson SS, Kittelson JM. A computationally simpler algorithm for the UMVUE of a normal mean following a group sequential design. Biometrics. 1997;53:365–369.

    Article  CAS  Google Scholar 

  11. Coburger S, Wassmer G. Conditional point estimation in adaptive group sequential test designs. Biometric J. 2001;43:821–833.

    Article  Google Scholar 

  12. Wright PS. Adjusted P-values for simultaneous inference. Biometrics. 1992;48:1005–1013.

    Article  Google Scholar 

  13. Wassmer G. Planning and analyzing adaptive group sequential survival trials. Biometric J. 2006; 48:714–729.

    Article  Google Scholar 

  14. Cytel Inc. East 5 (v5.2). 2008.

  15. Lan KK, Wittes J. The B-value: a tool for monitoring data. Biometrics. 1988;44:579–585.

    Article  CAS  Google Scholar 

  16. Tsiatis AA. The asymptotic joint distribution of the efficient scores test for the proportional hazards model calculated over time. Biometrika, 1981;68:311–315.

    Article  Google Scholar 

  17. Jahn-Eimermacher A, Ingel K. Adaptive trial design: a general methodology for censored time to event data. Contemp Clin Trials. 2009;30: 171–177.

    Article  Google Scholar 

  18. Marubini E, Valsecchi MG. Analysing Survival Data From Clinical Trials and Observational Studies. Chichester, UK: Wiley; 1995.

    Google Scholar 

  19. Bauer P, Koenig F. The reassessment of trial perspectives from interim data—a critical view. Stat Med. 2006;25:23– 36.

    Article  Google Scholar 

  20. Armitage P. McPherson CK, Rowe BC. Repeated significance tests on accumulating data. J R Stat Soc A. 1969;132:235–244.

    Article  Google Scholar 

  21. Brannath W, Posch M, Bauer P. Recursive combination tests. J Am Stat Assoc. 2002;97: 236–243.

    Article  Google Scholar 

  22. Brannath W, Mehta CR, Posch M. Exact confidence bounds following adaptive group sequential tests. Biometrics. 2009;65:539–546.

    Article  Google Scholar 

  23. Brannath W, Koenig F, Bauer P. Estimation in confirmatory adaptive designs with treatment selection. Adaptive Trials 2008, Barcelona.

  24. Tsiatis AA, Mehta G. On the inefficiency of the adaptive design for monitoring clinical trials. Biometrika. 2003;90: 367–387.

    Article  Google Scholar 

  25. Jennison C, Turnbull BW. Efficient group sequential designs when there are several effect sizes under consideration. Stat Med. 2006;25: 917–932.

    Article  Google Scholar 

  26. Jennison C. Critical appraisal of adaptive methods. Adaptive Trials 2008, Barcelona.

  27. Lee PM. Bayesian Statistics: An Introduction. 2nd ed. London: Arnold; 1997.

    Google Scholar 

  28. Cook TD, Benner RJ, Fisher MR. The WIZARD trial as a case study of flexible clinical trial design. Drug Inf J. 2006;40:345–353.

    Article  Google Scholar 

  29. Lan KKG, DeMets DL. Changing frequency of interim analysis in sequential monitoring. Biometrics. 1989;45:1017–1020.

    Article  CAS  Google Scholar 

  30. Koch CG, Amara IA, Stokes ME, Uryniak TJ. Categorical data analysis. In: Berry DA (ed.). Statistical Methodology in the Pharmaceutical Sciences. New York: Marcel Decker; 1990.

    Google Scholar 

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Authors and Affiliations

  1. Clinical Oncology, Cephalon Inc, 41 Moores Road, Frazer, Pennsylvania, USA

    Lothar T. Tremmel PhD (Sr. Director and Group Leader)

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  1. Lothar T. Tremmel PhD
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Correspondence to Lothar T. Tremmel PhD.

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Tremmel, L.T. Statistical Inference after an Adaptive Group Sequential Design: A Case Study. Ther Innov Regul Sci 44, 589–598 (2010). https://doi.org/10.1177/009286151004400506

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