Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials

In a clinical trial, it frequently occurs that the most credible outcome to evaluate the effectiveness of a new therapy (the true endpoint) is difficult to measure. In such a situation, it can be an effective strategy to replace the true endpoint by a (bio)marker that is easier to measure and that allows for a prediction of the treatment effect on the true endpoint (a surrogate endpoint). The package 'Surrogate' allows for an evaluation of the appropriateness of a candidate surrogate endpoint based on the meta-analytic, information-theoretic, and causal-inference frameworks. Part of this software has been developed using funding provided from the European Union's Seventh Framework Programme for research, technological development and demonstration (Grant Agreement no 602552), the Special Research Fund (BOF) of Hasselt University (BOF-number: BOF2OCPO3), GlaxoSmithKline Biologicals, Baekeland Mandaat (HBC.2022.0145), and Johnson & Johnson Innovative Medicine.

Getting started

Package details

AuthorWim Van Der Elst [cre, aut], Florian Stijven [aut], Fenny Ong [aut], Dries De Witte [aut], Paul Meyvisch [aut], Alvaro Poveda [aut], Ariel Alonso [aut], Hannah Ensor [aut], Christoper Weir [aut], Geert Molenberghs [aut]
MaintainerWim Van Der Elst <wim.vanderelst@gmail.com>
LicenseGPL (>= 2)
Version3.3.0
URL https://github.com/florianstijven/Surrogate-development
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("Surrogate")

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Surrogate documentation built on June 22, 2024, 9:16 a.m.