Clinical Trials with an Adaptive Choice of Hypotheses


In a clinical trial with an adaptive interim analysis it is possible to modify not only the design, but even the hypothesis(es) of interest, in a formally correct manner. Two examples of clinical trials are described where modifications of hypotheses are based on substantial scientific reasons. Generally, it is emphasized that the danger of manipulation caused by flexible designs must be controlled by very restrictive guidelines.

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  1. 1.

    Armitage P. Sequential Medical Trials. Oxford, England: Blackwell; 1975.

    Google Scholar 

  2. 2.

    Pocock SJ. Group sequential methods in the design and analysis of clinical trials. Biometrika. 1977;64: 191–199.

    Article  Google Scholar 

  3. 3.

    Pampallona S, Tsiatis AA. Group sequential designs for one-sided and two-sided hypothesis testing with provision for early stopping in favour of the null hypothesis. J Stat Plann Inf. 1994;42:19–35.

    Article  Google Scholar 

  4. 4.

    Jennison C, Turnbull BW. Group Sequential Methods with Applications to Clinical Trials. Boca Raton, FL: Chapman & Hall; 1999.

    Google Scholar 

  5. 5.

    Bauer P. Multistage testing with adaptive designs. Biom Inf Med Biol. 1989;20:130–136.

    Google Scholar 

  6. 6.

    Muller HH, Schafer H. Adaptive group sequential designs for clinical trials: combining the advantages of adaptive and of classical group sequential approaches. Biometrics. 2001;57:Forthcoming.

  7. 7.

    Bauer P, Kohne K. Evaluation of experiments with adaptive interim analyses. Biometrics. 1994;50: 1029–1041.

    CAS  Article  Google Scholar 

  8. 8.

    Fisher RA. Statistical Methods for Research Workers. London, England: Oliver & Boyd; 1932.

    Google Scholar 

  9. 9.

    Bauer P, Rohmel J. An adaptive method for establishing a dose-response relationship. Stat Med. 1995;14: 1595–1607.

    CAS  Article  Google Scholar 

  10. 10.

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

    CAS  Article  Google Scholar 

  11. 11.

    Wassmer G. Statistical Test Procedures for Group Sequential and Adaptive Designs in Clinical Trials. Koln, Germany: Verlag Alexander Mönch; 1999.

    Google Scholar 

  12. 12.

    Wassmer G, Eisebitt R, Coburger S. Flexible interim analyses in clinical trials using multistage adaptive test designs. Drug Inf J. 2001.

    Google Scholar 

  13. 13.

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

    CAS  Article  Google Scholar 

  14. 14.

    Hochberg Y, Tamhane AC. Multiple Comparison Procedures. New York, NY: Wiley; 1987.

    Book  Google Scholar 

  15. 15.

    Marcus R, Peritz E, Gabriel KR. On closed testing procedures with special reference to ordered analysis of variance. Biometrika. 1976;63:655–660.

    Article  Google Scholar 

  16. 16.

    Holm S. A simple sequentially rejective multiple test procedure. Scand J Stat. 1979;6:65–70.

    Google Scholar 

  17. 17.

    Hochberg Y. A sharper Bonferroni procedure for multiple tests of significance. Biometrika. 1988;75: 800–803.

    Article  Google Scholar 

  18. 18.

    Hommel G. A stagewise rejective multiple test procedure based on a modified Bonferroni test. Biometrika. 1988;75:383–386.

    Article  Google Scholar 

  19. 19.

    Tang DI, Geller NL. Closed testing procedures for group sequential clinical trials with multiple end-points. Biometrics. 1999;55:1188–1192.

    CAS  Article  Google Scholar 

  20. 20.

    Kieser M, Bauer P, Lehmacher W. Inference on multiple endpoints in clinical trials with adaptive interim analyses. Biom J. 1999;41:261–277.

    Article  Google Scholar 

  21. 21.

    Bauer P, Kieser M. Combining different phases in the development of medical treatments within a single trial. Stat Med. 1999;18:1833–1848.

    CAS  Article  Google Scholar 

  22. 22.

    Hommel G. Adaptive modifications of hypotheses after an interim analysis. Biom J. 2001;43:in press.

  23. 23.

    Posch M, Bauer P. Adaptive two stage designs and the conditional error function. Biom J. 1999;41:689–696.

    Article  Google Scholar 

  24. 24.

    Hommel G. Multiple test procedures for arbitrary dependence structures. Metrika. 1986;33:321–336.

    Article  Google Scholar 

  25. 25.

    Bauer P, Rohmel J, Maurer W, Hothorn L. Testing strategies in multi-dose experiments including active control. Stat Med. 1998;17:2133–2146.

    CAS  Article  Google Scholar 

  26. 26.

    Kropf S, Hommel G, Schmidt U, Brickwedel J, Jensen MS. Multiple comparisons of treatments with stable multivariate tests in a two-stage adaptive design, including a test for non-inferiority. Biom J. 2000;42:951–965.

    Article  Google Scholar 

  27. 27.

    O’Brien PC. Procedures for comparing samples with multiple endpoints. Biometrics. 1984;40:1079–1087.

    Article  Google Scholar 

  28. 28.

    Lauter J. Exact t and F tests for analyzing studies with multiple endpoints. Biometrics. 1996;52:964–970.

    Article  Google Scholar 

  29. 29.

    Lauter J, Glimm E, Kropf S. New multivariate tests for data with an inherent structure. Biom J. 1996;38:5–22. Erratum: Biom J. 1998;40:1015.

    Article  Google Scholar 

  30. 30.

    Lauter J, Glimm E, Kropf S. Multivariate tests based on left-spherically distributed linear scores. Ann Statist. 1998;26:1972–1988. Erratum: Ann Statist. 1999;27:1441.

    Article  Google Scholar 

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Correspondence to Gerhard Hommel PhD.

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Hommel, G., Kropf, S. Clinical Trials with an Adaptive Choice of Hypotheses. Ther Innov Regul Sci 35, 1423–1429 (2001).

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Key Words

  • Adaptive design
  • Group-sequential design
  • Closure test
  • Multiple endpoints; A priori ordered hypotheses