Package: OptSurvCutR 0.11.1

Payton Yau

OptSurvCutR: Optimal Survival Cut-Point Discovery for Time-to-Event Analysis with 'OptSurvCutR'

Provides a robust workflow for optimal cut-point analysis in time-to-event ('survival') data. Functions determine the optimal number of cut-points via find_cutpoint_number(), find their precise locations via find_cutpoint() using systematic or genetic algorithms (via the 'rgenoud' package), and validate stability via bootstrapping using validate_cutpoint(). Features include covariate adjustment, parallel processing, and an extensible S3 plotting engine for clinical dashboards and diagnostics.

Authors:Payton Yau [aut, cre, cph], Suhirthakumar Puvanendran [aut]

OptSurvCutR_0.11.1.tar.gz
OptSurvCutR_0.11.1.zip(r-4.7-x86_64)OptSurvCutR_0.11.1.zip(r-4.7-arm64)OptSurvCutR_0.11.1.zip(r-4.6-x86_64)OptSurvCutR_0.11.1.zip(r-4.6-arm64)OptSurvCutR_0.11.1.zip(r-4.5-x86_64)
OptSurvCutR_0.11.1.tgz(r-4.6-x86_64)OptSurvCutR_0.11.1.tgz(r-4.6-arm64)OptSurvCutR_0.11.1.tgz(r-4.5-x86_64)OptSurvCutR_0.11.1.tgz(r-4.5-arm64)
OptSurvCutR_0.11.1.tar.gz(r-4.7-arm64)OptSurvCutR_0.11.1.tar.gz(r-4.7-x86_64)OptSurvCutR_0.11.1.tar.gz(r-4.6-arm64)OptSurvCutR_0.11.1.tar.gz(r-4.6-x86_64)
OptSurvCutR_0.11.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
OptSurvCutR/json (API)

# Install 'OptSurvCutR' in R:
install.packages('OptSurvCutR', repos = c('https://ropensci-staging.r-universe.dev', 'https://cloud.r-project.org'))

Reviews:rOpenSci Software Review #()

Bug tracker:https://github.com/paytonyau/optsurvcutr/issues

Pkgdown/docs site:https://paytonyau.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

bioinformatics-pipelinecut-pointssurvival-analysisvalidationcpp

5.56 score 2 stars 8 scripts 219 downloads 8 exports 99 dependencies

Last updated from:6386f69187. Checks:15 OK, 1 ERROR. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK244
linux-devel-x86_64OK234
pkgdown docsERROR137
source / vignettesOK296
linux-release-arm64OK220
linux-release-x86_64OK278
macos-release-arm64OK202
macos-release-x86_64OK347
macos-oldrel-arm64OK194
macos-oldrel-x86_64OK249
windows-devel-arm64OK318
windows-devel-x86_64OK223
windows-release-arm64OK329
windows-release-x86_64OK223
windows-oldrel-x86_64OK226
wasm-releaseOK157

Exports:find_cutpointfind_cutpoint_numberplot_cutpoint_residualsplot_landmark_stratificationplot_optimisation_curveplot_validationtheme_optsurvvalidate_cutpoint

Dependencies:abindbackportsbootbroomcarcarDataclicodetoolscolorspacecommonmarkcorrplotcowplotcpp11curlDerivdigestdoBydoParalleldoRNGdplyrexactRankTestsfarverforeachforecastFormulafracdiffgenericsggplot2ggpubrggrepelggsciggsignifggtextgluegridExtragridtextgtableisobanditeratorsjpeglabelinglatticelifecyclelitedownlme4lmtestmagrittrmarkdownMASSMatrixMatrixModelsmaxstatmgcvminqamodelrmvtnormnlmenloptrnnetnumDerivpatchworkpbkrtestpillarpkgconfigpngpolynompurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrgenoudrlangrngtoolsrstatixS7scalesSparseMstringistringrsurvivalsurvminertibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrxfunxml2zoo

Analysing Clinical Survival Data with OptSurvCutR
Introduction | How this differs from a single optimal cut-point | The data | 1. Data preparation | 2. How many cut-points? | 3. Where are the boundaries? | 4. Are the boundaries stable? | Reading the tier | 5. Results at 500 replicates | 6. Reporting | Group composition | Hazard ratios and diagnostics | Joint stability | 7. Conclusion | Reference
Rendered frombilirubin.Rmdusingknitr::rmarkdown

Last update: 2026-09-18
Started: 2026-06-03

Thresholds in a Discrete Predictor
Introduction | The data | 1. Setup | 2. Data preparation | 3. Finding the cut-points | How many? | Where? | 4. Stability | Results at 500 replicates | 5. Reporting and diagnostics | Group composition | Hazard ratios | Proportional hazards | Landmark analysis | Survival curves | 6. Conclusion | References
Rendered fromcrc.Rmdusingknitr::rmarkdown

Last update: 2026-09-18
Started: 2026-09-04

Readme and manuals

Help Manual

Help pageTopics
Find Optimal Cut-points for Survival Datafind_cutpoint print.find_cutpoint summary.find_cutpoint
Find Optimal Number of Cut-points for Survival Datafind_cutpoint_number plot.find_cutpoint_number_result print.find_cutpoint_number_result summary.find_cutpoint_number_result
Diagnostic Plot of Schoenfeld Residualsplot_cutpoint_residuals
Plot Landmark Stratification Curvesplot_landmark_stratification
Plot Optimisation Curve or Surface from Searchplot_optimisation_curve
Plot Cut-point Optimisation Stability Surface and Help Catalog Pageplot.validate_cutpoint_result plot_validation print.validate_cutpoint_result summary.validate_cutpoint_result
Master S3 Plot Router for find_cutpointplot.find_cutpoint
Custom Clinical Theme for OptSurvCutRtheme_optsurv
Validate an Optimal Cut-point Using Bootstrappingvalidate_cutpoint