A comparative analysis of cancer stage classification systems for registries

Area of Science:

• Oncology
• Public Health
• Biostatistics

Background:

• Cancer stage at diagnosis significantly impacts survival and cancer surveillance metrics.
• Existing staging systems vary in utility, with their comparative value poorly understood.
• Accurate staging is vital for effective cancer control strategies and epidemiological studies.

Purpose of the Study:

• To comprehensively evaluate and compare various cancer staging systems.
• To introduce a framework for assessing staging system utility in different contexts.
• To guide cancer registries in selecting appropriate staging methods for improved data quality.

Main Methods:

• Systematic review and comparative analysis of traditional TNM, SEER Summary, Condensed TNM, Essential TNM, registry-derived, and extent-of-disease staging systems.
• Evaluation focused on principles, data requirements, and practical utility, particularly data collection and consolidation.
• Development of a conceptual framework for staging system evaluation.

Main Results:

• Traditional TNM staging provides high clinical and prognostic value but suffers from poor completeness in population-based registries.
• Simplified staging systems achieve higher completion rates but offer limited clinical utility.
• A balanced approach combining clinical value and practical feasibility is essential, suggesting hybrid solutions.

Conclusions:

• Effective cancer registration requires balancing clinical utility with practical feasibility in staging systems.
• Electronic tools like AI and staging applications can enhance data extraction and accuracy.
• Future efforts should focus on accessible, multilingual platforms to standardize surveillance and improve accuracy globally, especially in resource-limited settings.