Construction and validation of a nomogram for non small cell lung cancer patients with liver metastases based on a population analysis

Abstract

AbstractLung cancer is one of the most common malignancies in the United States, and the common metastatic sites in advanced non-small cell lung cancer (NSCLC) are bone, brain, adrenal gland, and liver, respectively, among which patients with liver metastases have the worst prognosis. We retrospectively analyzed 1963 patients diagnosed with NSCLC combined with liver metastases between 2010 and 2015. Independent prognostic factors for patients with liver metastases from NSCLC were identified by univariate and multivariate Cox regression analysis. Based on this, we developed a nomogram model via R software and evaluated the performance and clinical utility of the model by calibration curve, receiver operating characteristic curves, and decision curve analysis (DCA). The independent prognostic factors for NSCLC patients with liver metastases included age, race, gender, grade, T stage, N stage, brain metastases, bone metastases, surgery, chemotherapy, and tumor size. The area under the curve predicting OS at 6, 9, and 12 months was 0.793, 0.787, and 0.784 in the training cohort, and 0.767, 0.771, and 0.773 in the validation cohort, respectively. Calibration curves of the nomogram showed high agreement between the outcomes predicted by the nomogram and the actual observed outcomes, and the DCA further demonstrated the value of the clinical application of the nomogram. By analyzing the Surveillance, Epidemiology, and End Results database, we established and verified a prognostic nomogram for NSCLC patients with liver metastases, to personalize the prognosis of patients. At the same time, the prognostic nomogram has a satisfactory accuracy and the results are a guide for the development of patient treatment plans.