TwoCutoff: Deriving Clinically Interpretable Cutoffs for Disease Biomarkers

Provides a reproducible pipeline for deriving two clinically meaningful cutoffs for disease biomarkers using a unified two-stage framework. The package integrates finite mixture modeling with risk prediction using biomarker plus clinical features, followed by decision curve analysis to evaluate clinical utility. Outputs include biomarker density plots, risk calibration curves, decision curves, and summary tables of diagnostic performance. Designed for researchers in bio-statistics, neurology, and data science, this package emphasizes reproducibility, transparency, and clear clinical relevance.

Version:	0.1.0
Depends:	R (≥ 4.0.0)
Imports:	dplyr, mixtools, stats, pROC, xgboost, ggplot2, caret, patchwork, gridExtra
Suggests:	rmarkdown, DiagrammeR, knitr, devtools
Published:	2026-06-24
DOI:	10.32614/CRAN.package.TwoCutoff (may not be active yet)
Author:	Bhrigu Kumar Rajbongshi [aut, cre, ctb], Seyed Ehsan Saffari [aut, ctb], Nastaran Marzban [aut, ctb]
Maintainer:	Bhrigu Kumar Rajbongshi <kumarbhrigu536 at gmail.com>
License:	MIT + file LICENSE
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	TwoCutoff results

Documentation:

Reference manual:	TwoCutoff.html , TwoCutoff.pdf
Vignettes:	Introduction to TwoCutoff (source, R code)

Downloads:

Package source:	TwoCutoff_0.1.0.tar.gz
Windows binaries:	r-devel: not available, r-release: TwoCutoff_0.1.0.zip, r-oldrel: not available
macOS binaries:	r-release (arm64): TwoCutoff_0.1.0.tgz, r-oldrel (arm64): TwoCutoff_0.1.0.tgz, r-release (x86_64): TwoCutoff_0.1.0.tgz, r-oldrel (x86_64): TwoCutoff_0.1.0.tgz

Linking:

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