Abstract

Introduction The use of valid surrogate endpoints can accelerate the development of phase III trials. Numerous validation methods have been proposed with the most popular used in a context of meta-analyses, based on a two-step analysis strategy. For two failure time endpoints, two association measures are usually considered, Kendall's tau at individual level and adjusted R2 (adjR2trial) at trial level. However, adjR2trial is not always available mainly due to model estimation constraints. More recently, we proposed a one-step validation method based on a joint frailty model and a joint frailty-copula model, with the aim of reducing estimation issues and estimation bias on the surrogacy evaluation criteria. The model was quite robust with satisfactory results obtained in simulation studies. This study seeks to popularise this new surrogate endpoints validation approach by making the methods available in a user-friendly R package. Methods We provide numerous tools in the frailtypack R package, including more flexible functions, for the validation of candidate surrogate endpoints using data from multiple randomised clinical trials. Results We implemented the surrogate threshold effect which is used in combination with R2trial to make decisions 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 assessing the accuracy of the prediction using the joint surrogate models. Other tools include data generation, simulation study and graphic representations. We illustrate the use of the new functions with both real data and simulated data. Conclusion This work proposes new attractive and well developed tools for validating failure time surrogate endpoints.

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