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.


Surrogate

R-CMD-check

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.

Installation

You can install the development version of Surrogate from GitHub with:

# install.packages("devtools")
devtools::install_github("florianstijven/Surrogate-development")

Reference manual

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install.packages("Surrogate")

3.4.2 by Wim Van Der Elst, 4 months ago


https://github.com/florianstijven/Surrogate-development


Report a bug at https://github.com/florianstijven/Surrogate-development/issues


Browse source code at https://github.com/cran/Surrogate


Authors: Wim Van Der Elst [cre, aut] , Florian Stijven [aut] , Fenny Ong [aut] , Dries De Witte [aut] , Gokce Deliorman [aut] , Paul Meyvisch [aut] , Alvaro Poveda [aut] , Ariel Alonso [aut] , Hannah Ensor [aut] , Christoper Weir [aut] , Geert Molenberghs [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports MASS, lattice, latticeExtra, survival, nlme, lme4, logistf, rms, ks, extraDistr, pbapply, flexsurv, rvinecopulib, maxLik, purrr, MBESS, tidyr, dplyr, tibble, lifecycle, fastmatrix, mratios, Matrix

Suggests copula, FNN, mgcv, testthat, vdiffr, parallel, fitdistrplus, kdecopula, cubature, mvtnorm, withr, stringr, ggplot2, sn, pracma


See at CRAN