surrosurv-package: Evaluation of Failure Time Surrogate Endpoints in Individual...

Description Details Author(s) References See Also


Provides functions for the evaluation of surrogate endpoints when both the surrogate and the true endpoint are failure time variables. The approaches implemented are: (1) the two-step approach (Burzykowski et al, 2001) <DOI:10.1111/1467-9876.00244> with a copula model (Clayton, Plackett, Hougaard) at the first step and either a linear regression of log-hazard ratios at the second step (either adjusted or not for measurement error); (2) mixed proportional hazard models estimated via mixed Poisson GLM (Rotolo et al, 2019 <DOI:10.1177/0962280217718582>).


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Federico Rotolo [aut], Xavier Paoletti [ctr], Marc Buyse [ctr], Tomasz Burzykowski [ctr], Stefan Michiels [ctr, cre]

Maintainer: Stefan Michiels <>


Rotolo F, Paoletti X, Michiels S. surrosurv: an R Package for the Evaluation of Failure Time Surrogate Endpoints in Individual Patient Data Meta-Analyses of Randomized Clinical Trials. Computer Methhods and Programs in Biomedicine 2018; doi: 10.1016/j.cmpb.2017.12.005

Rotolo F, Paoletti X, Burzykowski T, Buyse M, Michiels S. A Poisson approach for the validation of failure time surrogate endpoints in individual patient data meta-analyses. Statistical Methhods in Medical Research 2019; 28(1). doi: 10.1177/0962280217718582

Burzykowski T, Molenberghs G, Buyse M et al. Validation of surrogate end points in multiple randomized clinical trials with failure time end points. Journal of the Royal Statistical Society C 2001; 50:405–422. doi: 10.1111/1467-9876.00244

Gasparrini A, Armstrong B, Kenward MG. Multivariate meta-analysis for non-linear and other multi-parameter associations. Statistics in Medicine 2012; 31:3821–39. doi: 10.1002/sim.5471

Burzykowski T, Molenberghs G, Buyse M (2005). The Evaluation of Surrogate Endpoints. Springer, New York.

See Also

Surrogate, mvmeta

surrosurv documentation built on May 2, 2019, 9:57 a.m.