Abstract
BACKGROUND: The disease and mortality rates of patients with laryngeal squamous cell carcinoma (LSCC) stabilize after peaking at the age of 60 years. This study aimed to identify risk factors associated with early death (death within 6 months) in elderly (≥60 years) patients with LSCC and to establish predictive nomograms to aid clinicians in developing individualized treatment plans. METHODS: Data pertaining to elderly patients with LSCC between 2004 and 2015 was obtained from the Surveillance, Epidemiology, and End Results database (version 8.4.0). Multiple logistic models were used to identify the independent risk factors associated with early mortality. The overall risk of early death was predicted using a web-based probability calculator and predictive nomogram. The cohort underwent decision curve analysis (DCA), calibration, and receiver operating characteristic curves to evaluate the clinical applicability and predictability of the models during the training and validation stages. RESULTS: This study included 10,031 patients, of which 1,711 (17.0%) experienced all-cause early death, and 1,129 died from cancer-specific causes. Patients with LSCC who had overlapping laryngeal lesions, advanced age, unmarried status, high tumour and node stages, presence of distant metastases, and lack of treatment were at risk for early death. According to the nomograms, the risk of all-cause death and cancer-specific early death had an area under the curve of 0.796 and 0.790, respectively. Internal validation and DCA revealed that the prediction model was accurate and could be applied clinically. CONCLUSION: The study provides an overview of the characteristics of early death in patients with LSCC. Among the prognostic factors, T stage and radiotherapy demonstrated the strongest predictive value for early mortality, while marital status and tumor grade had the worst prognostic value. Two nomogram plots were constructed to facilitate accurate prediction of all-cause and cancer-specific early mortality within 6 months in elderly patients with LSCC, thereby helping clinicians in providing more personalised treatment plans.