Ensemble Penalized Cox Regression for Survival Prediction

The top-performing ensemble-based Penalized Cox Regression (ePCR) framework developed during the DREAM 9.5 mCRPC Prostate Cancer Challenge < https://www.synapse.org/ProstateCancerChallenge> presented in Guinney J, Wang T, Laajala TD, et al. (2017) is provided here-in, together with the corresponding follow-up work. While initially aimed at modeling the most advanced stage of prostate cancer, metastatic Castration-Resistant Prostate Cancer (mCRPC), the modeling framework has subsequently been extended to cover also the non-metastatic form of advanced prostate cancer (CRPC). Readily fitted ensemble-based model S4-objects are provided, and a simulated example dataset based on a real-life cohort is provided from the Turku University Hospital, to illustrate the use of the package. Functionality of the ePCR methodology relies on constructing ensembles of strata in patient cohorts and averaging over them, with each ensemble member consisting of a highly optimized penalized/regularized Cox regression model. Various cross-validation and other modeling schema are provided for constructing novel model objects.


ePCR v0.9.9-6 (Release date: 2018-05-28)


  • Trimming functions and modified .RData for both ePCR S4-objects as well as glmnet model fits to reduce tarball size and installed package size
  • Using R.rsp to create vignettes from pre-computed .tex

ePCR v0.9.9-5 (Release date: 2018-05-23)


  • Minor improvements to the code, such as how the x.expand slot is called inside PSPs
  • New extensive step-by-step vignette
  • Attempted to reduce the size of the /data/ folder, since on some platforms the installed package exceeds 5 MB just barely

Reference manual

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0.9.9-11 by Teemu Daniel Laajala, 2 years ago

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

Authors: Teemu Daniel Laajala <[email protected]> [aut, cre] , Mika Murtoj<e4>rvi <[email protected]> [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports grDevices, graphics, stats, glmnet, hamlet, survival, timeROC, pracma, Bolstad2, impute

Suggests MASS, Matrix, ROCR, c060, methods, utils, R.rsp

See at CRAN