Document Type

Article

Publication Date

12-15-2020

Publication Title

Cancer

Abstract

BACKGROUND: The prognostic performance of the recently updated American Joint Committee on Cancer lymph node classification of cutaneous head and neck squamous cell carcinoma (HNSCC) has not been validated. The objective of this study was to assess the prognostic role of extranodal extension (ENE) in cutaneous HNSCC.

METHODS: This was a retrospective analysis of 1258 patients with cutaneous HNSCC who underwent surgery with or without adjuvant therapy between 1995 and 2019 at The University of Texas MD Anderson Cancer Center. The primary outcome was disease-specific survival (DSS). Local, regional, and distant metastases-free survival were secondary outcomes. Recursive partitioning analysis (RPA) and a Cox proportional hazards regression model were used to assess the fitness of staging models.

RESULTS: No significant differences in 5-year DSS were observed between patients with pathologic lymph node-negative (pN0) disease (67.4%) and those with pN-positive/ENE-negative disease (68.2%; hazard ratio, 1.02; 95% CI, 0.61-1.79) or between patients with pN-positive/ENE-negative disease and those with pN-positive/ENE-positive disease (52.7%; hazard ratio, 0.57; 95% CI, 0.31-1.01). The RPA-derived model achieved better stratification between high-risk patients (category III, ENE-positive with >2 positive lymph nodes) and low-risk patients (category I, pN0; category II, ENE-positive/pN1 and ENE-negative with >2 positive lymph nodes). The performance of the RPA-derived model was better than that of the pathologic TNM classification (Akaike information criterion score, 1167 compared with 1176; Bayesian information criterion score, 1175 compared with 1195).

CONCLUSIONS: The number of metastatic lymph nodes and the presence of ENE are independent prognostic factors for DSS in cutaneous HNSCC, and incorporation of these factors in staging systems improves the performance of the American Joint Committee on Cancer lymph node classification.

PubMed ID

33320343

ePublication

ePub ahead of print

Share

COinS