The Diagnostic Gap Between Clinical and Pathological Extranodal Extension in Head and Neck Cancers: A 5-Year Nationwide Trend Analysis in Taiwan

TL;DR

This study finds a consistent gap between clinical and pathological diagnosis of cancer spread in head and neck cancers in Taiwan, suggesting imaging limitations and the need for better tools.

Contribution

The study introduces the 'Quality-Gap Paradox' and reveals persistent diagnostic discrepancies in head and neck cancer staging over five years in Taiwan.

Findings

A diagnostic gap of 9.9% to 20.8% was found across different head and neck cancer sites in Taiwan.

The gap in oral cavity cancer did not improve over five years.

Medical centers showed a larger diagnostic gap than non-medical centers in oral cavity cancer.

Abstract

Background: Extranodal extension (ENE) is a critical prognostic factor in head and neck squamous cell carcinoma (HNSCC) and was incorporated into the AJCC eighth-edition staging system. However, the concordance between clinical (cENE) and pathological (pENE) ENE remains poorly understood in real-world practice. Methods: We conducted a retrospective analysis using Taiwan Cancer Registry (TCR) long-form data from 2018 to 2022, focusing on four major HNSCC sites (oral cavity, oropharynx, hypopharynx, and larynx). The diagnostic gap was defined as the difference between pENE and cENE positivity rates. Results: Among 29,830 patients, a persistent diagnostic gap was observed across all sites: laryngeal (20.8%), hypopharyngeal (20.4%), oropharyngeal (11.5%), and oral cavity (9.9%). For oral cavity cancer, the gap did not narrow over the 5-year period (p = 0.9788). Furthermore, in oral cavity cancer, medical centers demonstrated a larger gap than non-medical centers (10.5% vs. 8.4%), a phenomenon we term the “Quality-Gap Paradox”. Conclusions: A significant diagnostic gap persists in HNSCC, highlighting the limitations of current imaging. The Quality-Gap Paradox, observed in oral cavity cancer, suggests this is driven by a complex interplay of factors including superior pathological detection in high-volume centers. Our findings underscore the need for advanced, personalized risk-stratification tools to bridge this gap and improve patient management.

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