A nomogram to predict prognosis after surgery in early stage non-small cell lung cancer in elderly patients

Abstract

BackgroundThe aim of this study was to identify risk factors affecting overall survival (OS) of elderly patients with early stage NSCLC, and develop a nomogram for prognostic prediction of these patients using data from the Surveillance, Epidemiology, and End Results (SEER) database. MethodsData from the SEER database of patients aged ≥ 65 years with early (T1N0M0) NSCLC diagnosed between 2004 and 2013 were examined. The prognostic effect of each variable on survival was evaluated using the Kaplan–Meier method and the Cox proportional hazards regression model. A nomogram was formulated to predict the 3- and 5-year OS rates of elderly patients with early stage NSCLC. ResultsFinally, a total of 20,782 patients were included in this research. Cox regression analysis showed that sex, age, pathological type, diameter, differentiation, and surgery type were independent risk factors. A nomogram was formulated based on the results of multivariate analysis (all p < 0.001) and validated using an internal bootstrap resampling approach, which showed that the nomogram exhibited a sufficient level of discrimination according to the C-index (0.638, 95% CI = 0.629–0.647). ConclusionsThe nomogram developed in this study demonstrated its discrimination capability to predict the 3- and 5-year OS rates of elderly patients with early stage NSCLC based on individual characteristics.