A population-based model identifying optimal candidate for primary tumor resection in distant metastatic laryngeal carcinoma.

Abstract

To developed a model to screen distant metastatic laryngeal carcinoma (DMLC) patients who would benefit from the primary tumor resection. The propensity score matching (PSM) was utilized to avoid disproportionate distributions of the confounding factors. We hypothesized that patients who underwent surgery would benefit from surgery by having a longer median cancer-specific survival (CSS) than patients without surgery. Multivariable Cox model was used to explore the independent factors of CSS and overall survival (OS) among PSM population. We used these factors to construct a nomogram to identify surgery benefit patients. The predictive performance and clinical practicability of the nomogram were determined by area under the curve (AUC), calibration curve, and decision curve. The CSS and OS for patients who received primary tumor resection were significantly longer than those without resection (median CSS: 19months vs. 10months, P = 0.009; median OS: 21months vs. 10months, P = 0.001). The nomogram displayed a good degree of discrimination and calibration. The mean AUC of the nomogram was 0.70 (95% confidence interval [CI] 0.66-0.76) through threefold cross-validation. A predictive model was established and might be used to screen the optimal candidates for primary tumor surgery in DMLC patients.