An R package for biomarker evaluation that introduces a two‑stage cutoff framework. Instead of a single threshold, it defines both a rule‑out cutoff (cL) and a rule‑in cutoff (cH), creating three groups: non‑diseased, diseased, and an intermediate gray zone. This approach improves diagnostic interpretability and supports clinical decision‑making.
✨ Features
The TwoCutoff package supports reproducible diagnostic pipelines by integrating:
- 📌 adjust_score() – Gaussian mixture + confounder‑adjusted XGBoost risk modeling
- 📊 derive_cutoffs_percentile() – percentile‑based cutoff derivation
- 📊 derive_cutoffs_sensspec() – ROC‑based cutoff derivation
- 📈 evaluate_performance() – sensitivity, specificity, PPV, NPV metrics
- 🔍 compare_performance() – side‑by‑side comparison of cutoff methods
- 📉 dca_analysis() – decision curve analysis for clinical utility
- 🎨 plot_two_cutoff() – visualization of cutoffs and confusion matrix
🛠 Installation
# Install from CRAN (when available)
install.packages("TwoCutoff")
# Or install the development version from GitHub:
install.packages("remotes")
remotes::install_github("kumarbhrigu/TwoCutoff")