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Inference in response‐adaptive clinical trials when the enrolled population varies over time

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  • Massimiliano Russo
  • Steffen Ventz
  • Victoria Wang
  • Lorenzo Trippa

Abstract

A common assumption of data analysis in clinical trials is that the patient population, as well as treatment effects, do not vary during the course of the study. However, when trials enroll patients over several years, this hypothesis may be violated. Ignoring variations of the outcome distributions over time, under the control and experimental treatments, can lead to biased treatment effect estimates and poor control of false positive results. We propose and compare two procedures that account for possible variations of the outcome distributions over time, to correct treatment effect estimates, and to control type‐I error rates. The first procedure models trends of patient outcomes with splines. The second leverages conditional inference principles, which have been introduced to analyze randomized trials when patient prognostic profiles are unbalanced across arms. These two procedures are applicable in response‐adaptive clinical trials. We illustrate the consequences of trends in the outcome distributions in response‐adaptive designs and in platform trials, and investigate the proposed methods in the analysis of a glioblastoma study.

Suggested Citation

  • Massimiliano Russo & Steffen Ventz & Victoria Wang & Lorenzo Trippa, 2023. "Inference in response‐adaptive clinical trials when the enrolled population varies over time," Biometrics, The International Biometric Society, vol. 79(1), pages 381-393, March.
    • Handle: RePEc:bla:biomet:v:79:y:2023:i:1:p:381-393
    DOI: 10.1111/biom.13582
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    References listed on IDEAS

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    4. Steffen Ventz & William T. Barry & Giovanni Parmigiani & Lorenzo Trippa, 2017. "Bayesian response-adaptive designs for basket trials," Biometrics, The International Biometric Society, vol. 73(3), pages 905-915, September.
    5. Vaart,A. W. van der, 2000. "Asymptotic Statistics," Cambridge Books, Cambridge University Press, number 9780521784504, October.
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