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Compound optimal allocation for individual and collective ethics in binary clinical trials

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  • Alessandro Baldi Antognini
  • Alessandra Giovagnoli

Abstract

In recent years, several authors have investigated response-adaptive allocation rules for comparative clinical trials, in order to favour, at each stage of the trial, the treatment that appears to be best. In this paper, we define admissible allocations, namely treatment assignments that cannot be simultaneously improved upon with respect to both a specific design criterion, reflecting the inferential properties of the experiment, and the proportion of patients assigned to the best treatment or treatments; we survey existing designs from this viewpoint. We also suggest combining information and ethical considerations by taking a suitable weighted mean of two corresponding standardized criteria, with weights that depend on the actual treatment effects. This compound criterion leads to a locally optimal allocation that can be targeted by some response-adaptive randomization rule. The paper mainly deals with the case of two treatments, but the suggested methodology is shown to extend to more than two. Copyright 2010, Oxford University Press.

Suggested Citation

  • Alessandro Baldi Antognini & Alessandra Giovagnoli, 2010. "Compound optimal allocation for individual and collective ethics in binary clinical trials," Biometrika, Biometrika Trust, vol. 97(4), pages 935-946.
    • Handle: RePEc:oup:biomet:v:97:y:2010:i:4:p:935-946
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    File URL: http://hdl.handle.net/10.1093/biomet/asq055
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    Cited by:

    1. Alessandro Baldi Antognini & Marco Novelli & Maroussa Zagoraiou, 2022. "A simple solution to the inadequacy of asymptotic likelihood-based inference for response-adaptive clinical trials," Statistical Papers, Springer, vol. 63(1), pages 157-180, February.
    2. Jianhua Hu & Hongjian Zhu & Feifang Hu, 2015. "A Unified Family of Covariate-Adjusted Response-Adaptive Designs Based on Efficiency and Ethics," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 357-367, March.
    3. Yanqing Yi & Yuan Yuan, 2013. "An optimal allocation for response-adaptive designs," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(9), pages 1996-2008, September.
    4. Alessandra Giovagnoli, 2021. "The Bayesian Design of Adaptive Clinical Trials," IJERPH, MDPI, vol. 18(2), pages 1-15, January.
    5. Yi, Yanqing & Wang, Xikui, 2023. "A Markov decision process for response adaptive designs," Econometrics and Statistics, Elsevier, vol. 25(C), pages 125-133.
    6. Alessandro Baldi Antognini & Marco Novelli & Maroussa Zagoraiou, 2022. "A new inferential approach for response-adaptive clinical trials: the variance-stabilized bootstrap," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 235-254, March.

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