NOS-TLPlot: A Specialized Python Tool for Visualizing Newcastle–Ottawa Scale Risk-of-Bias Assessments in Systematic Reviews and Meta-Analysis.

Objective: To develop a specialized Python tool for visualizing Newcastle–Ottawa Scale (NOS) risk-of-bias assessments that addresses the limitations of existing generic visualization tools.Methods: The author developed NOS-TLPlot, an open-source Python package and accompanying Streamlit-based web application. The tool automatically converts raw NOS star ratings (0–9) into standardized risk categories (Low, Moderate, High) and generates twelve distinct visualization types, including star distribution plots, traffic-light plots, radar charts, heatmaps, dot profiles, donut charts, and lollipop charts. It offers both an interactive web application and a command-line interface for batch processing and integration into reproducible analytical pipelines. Users can customize output themes (e.g., traffic-light or grayscale), figure sizes, and export formats (PNG, PDF, SVG, EPS).Results: NOS-TLPlot successfully produces publication-quality visualizations for NOS risk-of-bias assessments. The tool's web application provides an intuitive interface for data upload, plot selection, and customization. The command-line interface allows for automated plot generation, facilitating reproducibility. The variety of visualization options enhances the flexibility and comprehensiveness of risk-of-bias reporting.Conclusion: NOS-TLPlot provides a dedicated, user-friendly, and reproducible solution for NOS data visualization, enhancing the transparency, consistency, and efficiency of reporting study quality in systematic reviews and meta-analyses involving non-randomized studies.Keywords: Newcastle–Ottawa Scale, risk of bias, data visualization, Python, systematic review, meta-analysis, open-source software.