Identifying optimal candidates for primary tumor surgery in patients with metastatic head and neck cancer

Abstract

Read online

BackgroundPrimary tumor surgery (PTS) may enhance survival among part of patients with metastatic head and neck cancer (mHNC). Herein, a predictive model was needed to construct to identify who can gain benefit remarkably from tumor resection.MethodsData of patients with mHNC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The best cut-off value of age were analyzed using the X-tile software. One-to-one PSM, Kaplan–Meier method, and log-rank test were performed for survival analysis.The independent factors determined using the multivariate Cox proportional hazard regression were used to construct the nomogram.ResultsA total of 1,614 patients diagnosed with mHNC were included; among them, 356 (22.0%) underwent a surgical procedure for the excision of the primary tumor. cancer-specific survival (CSS) was remarkably prolonged in the PTS group relative to the non-PTS group following PSM [Median:19 months vs. 9 months; hazard ratio (HR) 0.52, P < 0.001]. Patients with mHNC who were younger than 52 years old, had well-differentiated tumors, had T1 and N0 stages, and were married at the time of the study may have significantly benefited from PTS. In addition, we constructed a nomogram based on the factors that independently affect the CSS in multivariate Cox analysis. The nomogram showed excellent discrimination in both the training and validation sets (AUC: 0.732 and 0.738, respectively).ConclusionA practical predictive model was constructed to determine the appropriate patients with mHNC, who would benefit from surgical resection.

Keywords

• metastasis
• predictive models
• nomogram
• head and neck cancer
• SEER