Head & neck · 2026
Age Does Not Influence Cancer Mortality After Transoral Laser Microsurgery for Glottic Cancer: A Competing-Risks Analysis of 676 Patients.
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Chu Francesco, Tagliabue Marta, Zorzi Stefano Filippo, Bandi Francesco, Moglio Simone, Ruju Francesca, Ansarin Mohssen
Аннотация
BACKGROUND: The influence of chronological age on survival after transoral laser microsurgery (TOLMS) for laryngeal squamous cell carcinoma (LSCC) remains unclear, largely because most studies rely on arbitrary age cutoffs and do not account for competing non-cancer mortality.
METHODS: We retrospectively analyzed 676 patients with pT1-3 LSCC treated with primary TOLMS (2000-2025). Age was modeled per 10-year increase. Overall survival (OS) and disease-specific survival (DSS) were evaluated using Cox, cause-specific Cox, and Fine-Gray competing-risk models. Cumulative incidence of death of disease (DOD) and death from other causes (DOC) were estimated with the Aalen-Johansen method.
RESULTS: During a median follow-up of 68 months, 95 patients died from non-cancer causes and 43 from LSCC. Age strongly predicted OS (HR = 1.90 per decade) but showed only a weak association with DSS and was not significant in Fine-Gray analysis (sHR = 1.26). The pT category and margin status were the dominant predictors of DOD.
CONCLUSIONS: Age does not meaningfully influence cancer-specific mortality after TOLMS. Apparent age-related differences in survival largely reflect competing non-cancer deaths, supporting treatment decisions based on tumor biology rather than chronological age.
METHODS: We retrospectively analyzed 676 patients with pT1-3 LSCC treated with primary TOLMS (2000-2025). Age was modeled per 10-year increase. Overall survival (OS) and disease-specific survival (DSS) were evaluated using Cox, cause-specific Cox, and Fine-Gray competing-risk models. Cumulative incidence of death of disease (DOD) and death from other causes (DOC) were estimated with the Aalen-Johansen method.
RESULTS: During a median follow-up of 68 months, 95 patients died from non-cancer causes and 43 from LSCC. Age strongly predicted OS (HR = 1.90 per decade) but showed only a weak association with DSS and was not significant in Fine-Gray analysis (sHR = 1.26). The pT category and margin status were the dominant predictors of DOD.
CONCLUSIONS: Age does not meaningfully influence cancer-specific mortality after TOLMS. Apparent age-related differences in survival largely reflect competing non-cancer deaths, supporting treatment decisions based on tumor biology rather than chronological age.