A nomogram for predicting overall survival in patients with Merkel cell carcinoma: A population-based analysis

Abstract Background: Merkel cell carcinoma (MCC) is a rare neuroendocrine skin cancer with increasing incidence and poor prognosis. We sought to develop and validate a nomogram to estimate overall survival (OS) of MCC patients. Methods: 1863 MCC patients between 2010-2015 from the Surveillance, Epidemiology and End Results (SEER) database were randomly divided into the training and validation cohort. Independent prognostic factors determined by Cox regression analysis in the training cohort were used to establish a nomogram. We evaluated prognostic performance using the concordance index (C-index), area under receiver operating characteristic curve (AUC) and calibration curves. Decision curve analysis (DCA), net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to compared the the nomogram’s clinical utility with that of the staging system.Results: eight independent prognostic factors were incorporated in the nomogram. The C-index of the nomogram was 0.744, which was superior to the C-index of AJCC TNM Stage (0.659). The AUC was greater than 0.75 and the calibration plots of this model exhibited good performance. Additionally, the positive NRI and IDI of nomogram versus the staging system illustrated that the nomogram had better predictive accuracy than the staging system (P<0.001) and the DCA showed great clinical usefulness of the nomogram. MCC patients were perfectly classified into three risk groups by the nomogram, showing better discrimination than the staging system.Conclusions: We developed and validated a nomogram to assist clinicians in evaluating prognosis of MCC patients.