Establishment and Validation of a Novel Nomogram for Predicting Distant Metastasis in Patients with Invasive Lung Adenocarcinoma.

Abstract

To establish and verify a nomogram for predicting distant metastasis in invasive lung adenocarcinoma (IAC). Observational study. Department of Thoracic Surgery, Jinan Central Hospital, Jinan, China, from December 2021 to May 2022. To create a nomogram, univariate and multivariate logistic regression analyses wereused to identify the independent predictors of distant metastasis. The calibration, discrimination, and clinical performance of the nomogram were tested by calibration plots, area under receiver operating characteristic curve (AUC), and decision curve analysis (DCA). Age at diagnosis (<70 years), histological type (invasive mucinous adenocarcinoma), T stage, N stage, surgical approach, and lymph node dissection were independent predictors for the development of nomogram. Compared with the American Joint Committee on Cancer-8th edition staging system, AUC showed that this prediction model has a higher predictive performance (training set: 0.922 vs. 0.790; verification set: 0.919 vs. 0.779). In addition, the overall survival time (OS) of IAC patients was meaningfully different among the three groups of different risks stratified based on model score (p <0.001). The prediction model constructed according to factors such as histological type and surgical approach in this study can accurately predict distant metastasis in IAC patients and define high-risk patients according to nomogram score. Invasive adenocarcinoma IAC, Distant metastasis, Nomogram, Surveillance, Epidemiology and end results SEER.