Dr Virginie Rondeau, University of Bordeau, will present the Department of Statistical Sciences seminar with a talk entitled "The use of joint modelling to validate surrogate failure-time endpoints". 

Abstract: In many Biomedical areas, the identification and validation of surrogate endpoints is of prime interest to reduce the duration and/or size of clinical trials. Numerous validation methods have been proposed, the most popular is based on a two-step analysis strategy in the context of meta-analysis. For two failure time endpoints, two association measurements are usually considered, one at the individual level and one at the trial level. However, this approach is not always available mainly due to convergence or estimation problems in clinical trials. We are presenting here different approaches based on joint frailty models and a one-step validation method with new attractive and well-developed tools for the validation of failure time surrogate endpoints. Both individual- and trial-level surrogacy were evaluated using a new definition of Kendall’s tau and the coefficient of determination.

We aim in this work to popularize these new surrogate endpoints validation approaches by making the methods available in a user-friendly R package. Thus, we provide in the frailtypack R package numerous tools, including more flexible functions, for the validation of candidate surrogate endpoints, using data from multiple randomized clinical trials. We have especially the surrogate threshold effect which is used in combination with R2trial to make a decision concerning the validity of the surrogate endpoints. It is also possible thanks to frailtypack to predict the treatment effect on the true endpoint in a new trial using the treatment effect observed on the surrogate endpoint. The leave-one-out cross-validation is available for the assessment of the accuracy of the prediction using the joint surrogate model. Other tools concerned data generation, studies simulation and graphic representations. We illustrate the use of the new functions with both real data and simulated data.

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Meeting ID: 915 3146 1374

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