Nomogram for predicting survival in patients with pancreatic cancer

Background The purpose of this study was to develop a nomogram to predict cancer-specific survival (CSS) in pancreatic cancer (PC). Patients and methods We used the Surveillance, Epidemiology, and End Results (SEER) database to analyze 53,028 patients diagnosed with PC from 2004 to 2014 and randomly divided them into the training (n=26,583) cohort and validation (n=26,445) cohort. Univariate and multivariate analyses were used to select independent prognostic factors. We used significant prognostic factors for constructing a nomogram based on Cox regression analyses. Validation of the nomogram was assessed by discrimination and calibration. Results According to the multivariate models of training cohort, a nomogram that combined age, race, tumor location, marital status, tumor size, TNM stage, tumor grade, and surgery was constructed for predicting CSS. The internally validated and externally validated C-indexes were 0.741 and 0.734, respectively. The calibration curves showed that the nomogram was able to predict 1-, 3-, and 5-year CSS accurately. Conclusion A nomogram effectively predicts survival in patients with PC. This prognostic model may be considered for use in clinical practice.