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Changelog

Source: NEWS.md

OncoPath 1.0.0 (2026-07-13)

jamovi library readiness

  • Aligned all four analysis versions and the module manifest at 1.0.0.
  • Removed the unfinished clinical-preset and orphaned stage-migration code.
  • Reduced references and dependencies to the analyses that actually ship.
  • Replaced the misleading HSROC label with the implemented Holling proportional-hazards SROC model and corrected its parameter descriptions.
  • Honored estimator and confidence-level selections in auxiliary metafor models, with finite-value guards for zero-cell studies.
  • Hardened validation/error rendering and translation-ready message assembly.

OncoPath 0.0.47 (2026-07-05)

Changes

  • Declared data.table, htmltools, psych, and stringr (used via :: but previously undeclared) so they install reliably with the module.

OncoPath 0.0.46 (2026-07-04)

This release rolls up all changes from 0.0.33 through 0.0.46 (intermediate versions 0.0.38.1, 0.0.43, and 0.0.45). The headline themes are a security/robustness hardening pass ahead of a jamovi-library refactor (HTML/XSS escaping of user-supplied text and error messages across every analysis, removal of an unreliable variable-name mangling helper), migration of the Swimmer Plot to a serialization-safe notices mechanism, a new suite of exported stage-migration utility functions, new bundled example datasets, and an upgrade of the module’s minimum jamovi app and tooling requirements.

Security & Robustness

HTML/XSS Hardening (all analyses)

  • Diagnostic Test Meta-Analysis (diagnosticmeta):
    • Wrapped error messages with htmltools::htmlEscape() in all five tryCatch handlers that write table notes: bivariate, HSROC, heterogeneity, meta-regression, and publication-bias analyses
    • Escaped the user-supplied meta-regression covariate label (safe_covariate_label) before it is written into the meta-regression results table
    • Escaped user-supplied study names in the zero-cell-correction warning note and HTML disclosure (safe_studies_note, safe_studies_html)
  • Swimmer Plot (swimmerplot):
    • Escaped the best-response category in interpretation and manuscript-summary text
    • Escaped user-derived example values in the “Data Type Mismatch” and “Date Format Detected” guidance panels, and the detected date-format string
    • Escaped validation and analysis error messages before HTML interpolation
  • Treatment Response Analysis (waterfall):
    • Escaped missing/available column names in the data-validation message
    • Escaped patient IDs lacking a baseline measurement, and the printed data-frame rows for invalid tumor-shrinkage and unusually-large-growth warnings
    • Replaced a bare stop(plain_message) with jmvcore::reject("{}", code = NULL, plain_message)
  • IHC Heterogeneity Analysis (ihcheterogeneity):
    • Escaped the spatial_id variable name in the “not found in data” error message

Variable-name Handling Bug Fix

  • diagnosticmeta: removed the .escapeVar() helper, which mangled column names containing spaces or punctuation (e.g. Study Name (2020) became Study_Name_2020_) and then used the mangled string as a self$data[[...]] key, silently returning NULL and breaking the analysis. Study/TP/FP/FN/TN variables now use their raw option values as lookup keys.
  • diagnosticmeta: narrowed package imports from @import mada / @import metafor to @importFrom mada reitsma phm and @importFrom metafor rma, and set dontrun: true on the analysis example.

Output Cleanup

  • Removed emoji from all HTML output panels (welcome/about/interpretation/glossary/plot-explanation panels, notice icons, and the Swimmer Plot clinical-event glyph mapping) across diagnosticmeta, swimmerplot, waterfall, and ihcheterogeneity, and replaced % with the word “percent” in waterfall and ihcheterogeneity option descriptions.

Enhanced Existing Modules

Swimmer Plot (swimmerplot) — Notices Migration

  • NEW output notices (type Preformatted, title “Important Information”) with clearWith on patientID, startTime, endTime, responseVar, censorVar, and timeUnit
  • Added .noticeList, .addNotice(), and .renderNotices() helpers that render plain-text notices via the Preformatted item, avoiding both the jmvcore::Notice serialization error and HTML in notice content
  • Re-enabled the small-sample-size STRONG_WARNING (n < 10 patients), which was previously commented out to avoid serialization errors
  • Emit an ERROR notice when required variables (Patient ID, Start Time, End Time) are missing
  • Reset the notice list at the top of .run() to prevent accumulation across runs

New Stage Migration Utility Functions

Four new R source files add an exported stagemigration_* helper suite (with man pages and STAGEMIGRATION_CONSTANTS) supporting staging-system comparison and validation: - Discrimination: stagemigration_calculateConcordance, stagemigration_bootstrapConcordance, stagemigration_competingRisksDiscrimination - Competing risks & survival: stagemigration_competingRisksAnalysis, stagemigration_calculateRMST, stagemigration_cutpointAnalysis - Data validation & quality: stagemigration_validateData, stagemigration_validateCovariates, stagemigration_validateStagingVars, stagemigration_createEventBinary, stagemigration_convertLabelled, stagemigration_detectOutliers, stagemigration_dataQualityReport, stagemigration_checkSampleSize - Safe execution & formulas: stagemigration_safeAtomic, stagemigration_safeExecute, stagemigration_buildFormula, stagemigration_escapeVar

Shared Survival-Formula Helpers (R/utils.R)

  • Added .asSurvivalFormula(), which wraps jmvcore::asFormula with an extended function allow-list for survival/Cox/Fine-Gray formula paths under jamovi 2.7.27’s hardened parser
  • Added .buildSurvivalFormula(), .escapeVariableNames(), load_required_package(), the %notin% / %!in% operators, and a print.sensSpecTable S3 method

New Example Datasets

  • NEW R/data.R documents five bundled datasets: diagnostic_studies, histopathology, swimmerplot_sample, waterfall_percentage_basic, and waterfall_raw_longitudinal
  • NEW .rda files: diagnostic_studies (5 studies with study_name, tp, fp, fn, tn), swimmerplot_sample, waterfall_percentage_basic, and waterfall_raw_longitudinal
  • NEW jamovi .omv versions under inst/extdata/: swimmerplot_sample.omv, waterfall_percentage_basic.omv, waterfall_raw_longitudinal.omv

Dependencies

  • Added Imports: cluster, cmprsk, haven, maxstat, survRM2 (supporting the new competing-risks, RMST, cutpoint, and labelled-data utilities)
  • Added Depends: R (>= 3.5.0)

Package Infrastructure

  • Bumped version 0.0.33 → 0.0.46 (rolling up 0.0.38.1, 0.0.43, 0.0.45)
  • Raised minApp from 1.6.0 to 2.7.27 to align with jamovi’s hardened as.formula allow-list
  • Migrated roxygen configuration from RoxygenNote: 7.3.3 to Config/roxygen2/version: 8.0.0
  • De-bracketed the BugReports URL in DESCRIPTION
  • Added module audit report docs/audit/MODULE_AUDIT_REPORT_20260514-1844.md

OncoPath 0.0.32.64 (2025-12-31)

Major New Features

Stage Migration Analysis Tools

  • NEW: Comprehensive suite of statistical helper functions for stage migration analysis
  • Advanced discrimination and reclassification metrics for comparing staging systems
  • Designed for cancer staging research and prognostic model evaluation
  • Supports survival analysis with Cox proportional hazards models

Advanced Discrimination Metrics

  • Concordance Index (C-index): Paired comparison of staging system discrimination
  • Bootstrap Validation: Robust C-index comparison accounting for data correlation
    • Configurable bootstrap replicates (default: 200)
    • Correlation-aware variance estimation for dependent staging systems
    • Automatic convergence handling and error recovery
  • Confidence Intervals: Both analytical and bootstrap-based 95% CI estimation
  • Statistical Testing: Two-sided hypothesis testing for C-index improvement

Reclassification Metrics

  • Net Reclassification Improvement (NRI):
    • Time-dependent NRI calculation at multiple time points
    • Separate event and non-event reclassification statistics
    • Risk category-based patient stratification (tertiles by default)
    • Variance estimation with confidence intervals and p-values
  • Integrated Discrimination Improvement (IDI):
    • Discrimination slope comparison between staging systems
    • Bootstrap validation option for robust inference
    • Separate discrimination for events and non-events
    • Direct probability-based assessment

Model Comparison Statistics

  • Information Criteria: AIC and BIC for both staging systems with improvement metrics
  • Likelihood Ratio Tests:
    • Combined model testing for incremental value
    • Individual model likelihood ratio statistics
    • Chi-square test statistics with degrees of freedom and p-values
  • Linear Trend Analysis:
    • Wald tests for ordinal staging progression
    • Automatic handling of categorical and ordinal stage variables
    • Separate trend tests for old and new staging systems

Pseudo R² Measures

  • Multiple Pseudo R² Variants:
    • McFadden R²: Log-likelihood ratio measure
    • Adjusted McFadden R²: Penalized for model complexity
    • Cox-Snell R²: Exponential transformation approach
    • Nagelkerke R²: Normalized Cox-Snell (0-1 range)
    • Royston R²: Placeholder for future implementation
  • All measures calculated for both staging systems with improvement deltas
  • Robust handling of edge cases (zero log-likelihoods, division by zero)

Technical Improvements

Statistical Robustness

  • Correlation-Aware Variance Estimation:
    • Spearman correlation coefficient for linear predictor correlation
    • Covariance adjustment for paired C-index comparisons
    • Conservative variance bounds (non-negative constraint)
  • Bootstrap Methods for Correlated Data:
    • Stratified sampling preserving event/non-event ratios
    • Percentile-based confidence intervals
    • Automatic outlier detection and removal
    • Progress checkpoint callbacks for long-running analyses

Error Handling and Validation

  • Comprehensive try-catch blocks throughout all functions
  • Graceful degradation with informative error messages
  • Automatic handling of:
    • Model convergence failures in bootstrap samples
    • Zero cells in contingency tables
    • Insufficient sample sizes
    • Missing or invalid data
  • Validation of minimum sample requirements for reliable inference

Flexible Staging System Support

  • Categorical Staging: Nominal categories without ordering assumptions
  • Ordinal Staging: Ordered stages with linear trend analysis
  • Mixed Systems: Comparison between different staging paradigms
  • Automatic detection of stage levels and appropriate statistical tests
  • Support for varying numbers of stages between old and new systems

Dependencies

Updated Imports

  • Enhanced survival package utilization for Cox models and concordance
  • Extended Hmisc usage for survival correlation metrics (rcorrp.cens)
  • boot package integration for bootstrap confidence intervals
  • Comprehensive stats imports for statistical distributions and tests

Internal Improvements

  • Modular helper function architecture for maintainability
  • Consistent naming conventions (stagemigration_* prefix)
  • Progress callback support for computationally intensive operations
  • Null coalescing operator (%||%) for default parameter handling
  • Safe mathematical operations with bounds checking

Use Cases

These stage migration tools are designed for: - Cancer Research: Evaluating new TNM staging editions (e.g., AJCC 7th vs. 8th edition) - Prognostic Models: Comparing traditional staging with molecular or imaging-based classifiers - Clinical Guidelines: Evidence-based assessment of staging system updates - Meta-Research: Systematic evaluation of staging system performance across studies - Quality Improvement: Hospital-level assessment of staging accuracy and clinical impact

OncoPath 0.0.32 (2025-10-09)

Documentation Improvements

README.Rmd

  • NEW: Created comprehensive README.Rmd with detailed module description
  • Enhanced feature descriptions with emojis for better readability
  • Added detailed installation instructions (3 methods)
  • Included quick start examples for both swimmer and waterfall plots
  • Added comprehensive use cases section (Clinical Research, Pathology Research, Publication Support)
  • Expanded acknowledgements section with gratitude to package developers
  • Integrated with ClinicoPath ecosystem documentation

Documentation Website

  • All documentation now available at: https://www.serdarbalci.com/OncoPath/
  • Direct links to swimmer plot and waterfall plot guides
  • Clear integration with main ClinicoPath documentation hub

Vignette Additions

  • NEW: Added 9 comprehensive vignettes for enhanced documentation
  • Clinical Heatmap: clinicalheatmap_comprehensive.Rmd - Clinical heatmap visualization
  • Digital Pathology Suite (4 files):
    • digital_pathology_chatgpt.md - AI-generated pathology analysis guide
    • digital_pathology_claude.md - Comprehensive digital pathology documentation
    • digital_pathology_gemini.md - Alternative AI perspective on digital pathology
    • digital-pathology-analysis-suite.md - Complete digital pathology analysis overview
  • Texture Analysis: HARALICK_TESTING_GUIDE.md - Haralick texture feature analysis testing
  • Agreement Analysis (3 files):
    • COMBINED_USUBUTUN_GUIDE.md - Combined Usubutun plot guide
    • USUBUTUN_ENHANCED_TEST_GUIDE.md - Enhanced testing procedures
    • USUBUTUN_TEST_GUIDE.md - Standard testing guide for agreement visualization
  • Oncoplot: ggoncoplot_documentation.md - Genomic alteration visualization documentation

Function Documentation

  • Added waterfall plot legacy documentation: 09-waterfall-legacy.Rmd
  • Function-specific vignette: 06-function-waterfall.Rmd - Detailed waterfall function guide

Features Summary

Patient Follow-Up Plots

  • 🏊‍♂️ Swimmer Plot Analysis: Timeline visualization with ggswim integration
  • 🌊 Waterfall Plot Analysis: RECIST criteria treatment response analysis
  • Complete support for clinical trial reporting and oncological research

Pathology Analysis Tools

  • 🔬 IHC Heterogeneity Analysis: Immunohistochemistry marker analysis
  • 📊 Diagnostic Test Meta-Analysis: Bivariate meta-analysis with HSROC

OncoPath 0.0.31.84 (2025-10-03)

Major New Features

Diagnostic Test Meta-Analysis for Pathology

  • NEW: Comprehensive diagnostic test accuracy meta-analysis module
  • Bivariate random-effects meta-analysis using the Reitsma method
  • Hierarchical Summary ROC (HSROC) curve analysis
  • Meta-regression capabilities for exploring heterogeneity
  • Publication bias assessment with funnel plots
  • Support for multiple estimation methods (REML, ML, Fixed Effects, etc.)
  • Forest plots for sensitivity and specificity
  • SROC plots with confidence regions
  • Designed specifically for:
    • AI/ML algorithm validation in pathology
    • Biomarker diagnostic accuracy synthesis
    • Systematic reviews of diagnostic tests

IHC Heterogeneity Analysis

  • NEW: Statistical analysis of immunohistochemistry marker heterogeneity
  • Multi-marker evaluation capabilities
  • Robust statistical methods for heterogeneity assessment
  • Specialized tools for pathology biomarker research

Enhancements

Treatment Response Analysis (Waterfall Plot)

  • Improved RECIST criteria implementation
  • Enhanced visualization options
  • Better handling of longitudinal data

Swimmer Plot

  • Continued integration improvements with ggswim package
  • Enhanced data validation
  • Better error handling and user feedback

Dependencies

New Package Dependencies

  • mada: Meta-analysis of diagnostic accuracy studies
  • metafor: Advanced meta-analysis and meta-regression
  • pROC: ROC curve analysis
  • survival & survminer: Survival analysis support
  • boot: Bootstrap methods
  • dcurves: Decision curve analysis
  • Hmisc: Statistical utilities
  • rms: Regression modeling strategies
  • timeROC: Time-dependent ROC curves
  • tidyr: Data tidying operations

Bug Fixes

  • Fixed menu organization for diagnostic meta-analysis
  • Improved variable name handling with special characters
  • Enhanced error messages and user guidance

Internal Changes

  • Updated NAMESPACE with new imports
  • Reorganized menu structure for better discoverability
  • Added comprehensive validation for meta-analysis inputs
  • Improved handling of zero cells in diagnostic data

OncoPath 0.0.31.69 (Previous Version)

Features

  • Swimmer Plot Analysis with ggswim integration
  • Waterfall Plot Analysis with RECIST criteria
  • Treatment Response Visualization
  • Patient Timeline Tracking

Initial Release Features

  • Comprehensive patient follow-up visualization tools
  • RECIST criteria analysis
  • Clinical event tracking
  • Publication-ready visualizations