Development and validation of a nomogram for predicting overall survival in patients with early-onset endometrial cancer

Abstract

Abstract Background The aim of this study was to investigate the differences in the clinicopathological characteristics of younger and older endometrial cancer (EC)patients, and further assess the prognosis of early-onset EC in terms of overall survival by developing a nomogram. Methods Patients with EC diagnosed from surveillance, epidemiology and end results (SEER) between 2004 and 2015 were selected. Clinicopathological characteristics were compared between younger and older patients, and survival analysis was performed in both groups. Prognostic factors affecting overall survival in young EC patients were identified by Cox regression, a nomogram was created and internal validation was performed by consistency index, decision curve analysis, receiver operating characteristic curves and calibration curves. Data from 70 early-onset EC patients for external validation. Finally, Kaplan-Meier curves were plotted to compare survival outcomes across risk subgroups. Results A total of 5037 young patients and 60612 older patients were included in this study. Younger patients were divided into a training cohort (3526) and a validation cohort (1511) in a 7:3 ratio. Cox analysis yielded age, marital status, race, SEER stage and T stage as independent risk factors for overall survival, and a nomogram was constructed based on these factors. Internal and external validation demonstrated the good predictive power of the nomogram. In particular, the C-index for the overall survival nomogram was 0.839 [95% confidence interval (0.814–0.864)] in the training cohort and 0.826 (0.785–0.867) in the internal validation cohort. The differences in Kaplan-Meier curves between the different risk subgroups were statistically significant. Conclusions In this study, the nomogram predicting overall survival of early-onset endometrial cancer patients based on the SEER database was developed to help assess the prognosis of patients and guide clinical treatment.