A nomogram for predicting postoperative overall survival of patients with lung squamous cell carcinoma: a SEER-based study

Abstract

Background: Lung squamous cell carcinoma (LSCC) is a common subtype of non-small cell lung cancer. Our study aimed to construct and validate a nomogram for predicting overall survival (OS) for postoperative LSCC patients. Methods: A total of 8,078 patients eligible for recruitment between 2010 and 2015 were selected from the Surveillance, Epidemiology and End Results database. The study outcomes were 1-, 2-, and 3-year OS. Analyses performed included univariable and multivariable Cox regression, receiver the operating characteristic (ROC) curves, calibration plots, decision curve analysis (DCA), and Kaplan-Meier survival curves.Results: Seven variables were selected to establish the nomogram for LSCC. The area under the curve in ROC curve revealed 0.658, 0.651, and 0.647 in the training cohort and 0.673, 0.667, and 0.658 in the validation cohort at 1-, 2-, and 3-year survival. The calibration curves showed satisfactory consistencies between nomogram-predicted and observed survival probability. DCA showed great clinical net benefit. In risk stratification systems, patients were divided into three risk groups with a significant difference in OS in Kaplan-Meier curves (P＜0.001).Conclusions: A prognostic nomogram for OS of postoperative LSCC patients was developed and validated, which may assist clinicians in evaluating prognosis and providing highly individualized therapy.