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Approche Bayésienne de la survie dans les essais cliniques pour les cancers rares

Abstract : Bayesian approach augments the information provided by the trial itself by incorporating external information into the trial analysis. In addition, this approach allows the results to be expressed in terms of probability of some treatment effect, which is more informative and interpretable than a p-value and a confidence interval. In addition, the frequent reduction of an analysis to a binary interpretation of the results (significant versus non-significant) is particularly harmful in rare diseases.In this context, the objective of my work was to explore the feasibility, constraints and contribution of the Bayesian approach in clinical trials in rare cancers with a primary censored endpoint. A review of the literature confirmed that the implementation of Bayesian methods is still limited in the analysis of clinical trials with a censored endpoint.In the second part of our work, we developed a Bayesian design, integrating historical data in the setting of a real clinical trial with a survival endpoint in a rare disease (osteosarcoma). The prior incorporated individual historical data on the control arm and aggregate historical data on the relative treatment effect. Through a large simulation study, we evaluated the operating characteristics of the proposed design and calibrated the model while exploring the issue of commensurability between historical and current data. Finally, the re-analysis of three clinical trials allowed us to illustrate the contribution of Bayesian approach to the expression of the results, and how this approach enriches the frequentist analysis of a trial.
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Submitted on : Monday, December 2, 2019 - 1:06:46 AM
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  • HAL Id : tel-02388500, version 1



Caroline Brard. Approche Bayésienne de la survie dans les essais cliniques pour les cancers rares. Santé publique et épidémiologie. Université Paris Saclay (COmUE), 2018. Français. ⟨NNT : 2018SACLS474⟩. ⟨tel-02388500⟩