Establishment and validation of a clinicopathological prediction model for postoperative recurrence of stage IA lung adenocarcinoma.

Abstract

With the popularization of low-dose spiral computed tomography (CT), an increasing number of stage IA lung cancers have been discovered. Patients with stage IA lung adenocarcinoma who undergo radical surgical resection tend to have a favourable prognosis. However, A significant proportion of patients undergo postoperative recurrence and metastasis. The purpose of this study was to screen out the risk factors in patients with stage IA lung adenocarcinoma and establish a nomogram model to help clinicians identify high-risk patient groups. A nomogram was conducted based on a retrospective study of 731 patients with stage IA lung adenocarcinoma. Concordance index (C-index), clinical decision analysis, receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the discrimination and calibration of the nomogram. Survival curves were drawn by Kaplan-Meier method, and significance was determined by log-rank test. According to nomogram scores, the patients were divided into low- and high-risk subgroups. The internal and external cohorts included 731 and 235 eligible patients. In univariate and multivariate analyses, the independent factors for recurrence-free survival (RFS) were all selected in the nomogram. C-indexes of the nomogram were 0.812 (95% confidence interval: 0.756-0.868) and 0.817 in the internal and external validation, respectively, showing that the prominent prediction performance was great. Nomogram scores showed that patients in the low-risk group (5-RFS rate, 0.797 to 0.99) had better RFS than patients in the high-risk group (5-RFS rate, 0.10 to 0.797) (P<0.001). A nomogram model was established that can be beneficial to evaluate RFS in patients with stage IA lung adenocarcinoma after curative resection. It can be of value in helping clinicians develop treatment strategies to improve patient survival.