CRAN/E | ePCR

ePCR

Ensemble Penalized Cox Regression for Survival Prediction

Installation

About

The top-performing ensemble-based Penalized Cox Regression (ePCR) framework developed during the DREAM 9.5 mCRPC Prostate Cancer Challenge presented in Guinney J, Wang T, Laajala TD, et al. (2017) doi:10.1016/S1470-2045(16)30560-5 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.

Key Metrics

Version 0.11.0
R ≥ 3.5.0
Published 2024-02-19 38 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks ePCR results

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Maintainer

Maintainer

Teemu Daniel Laajala

teelaa@utu.fi

Authors

Teemu Daniel Laajala

aut / cre

Mika Murtojarvi

ctb

Material

README
NEWS
Reference manual
Package source

Vignettes

User guide to the ePCR R-package

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

ePCR archive

Depends

R ≥ 3.5.0

Imports

grDevices
graphics
stats
methods
glmnet
hamlet
survival
timeROC
pracma
Bolstad2
impute

Suggests

MASS
ROCR
c060
utils
Matrix ≥ 1.5-0
knitr
rmarkdown

Reverse Suggests

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