Construction of a Nomogram After Using Propensity Score Matching to Reveal the Prognostic Benefit of Tumor Resection of Stage IV M1a Nonsmall Cell Lung Cancer Patients

Abstract

The aim of this work was to determine whether tumor resection could improve the prognosis of M1a nonsmall-cell lung cancer (NSCLC) patients. We obtained patient data from the Surveillance, Epidemiology, and End Results (SEER) database and used propensity score matching (PSM) to reduce the influence of confounding variables. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors, and the prediction results were visualized using the nomogram. A total of 772 patients with and without tumor resection were enrolled after PSM, and the nomogram combined with independent prognostic factors including age, sex, histological type, grade, T stage, N stage, chemotherapy, and surgery showed great prediction and discriminatory ability. Tumor resection is possibly a better choice for these patients.