Approches innovantes des essais cliniques en oncologie : intégration de modèles adaptatifs et de données de vie réelle en recherche clinique

Abstract

The development of clinical trial methodologyin oncology, is incorporating adaptive models and the use of real-world data (RWD). Traditionally, randomized controlled trials (RCTs) have been the gold standard for assessing treatment efficacy. Adaptive trials offer flexible experimental designs that allow clinical studies to evolve according to interim results without compromising the statistical validity of the results. This approach is of particular interest in oncology, where many drugs are being tested in a limited number of patients and resources need to be allocated efficiently. In certain situations, RWD can provide results that are complementary to those of RCTs and are particularly valuable in rare cancers where randomized trials may not be feasible due to logistical or ethical constraints. This article examines the principles and applications of adaptive trials, including the Bayesian approach to interim analyses and comparative analysis of the efficacy of an experimental treatment using RWD, in particular through target trial emulation.