A nomogram for predicting the disease-free survival of patients with pancreatic ductal adenocarcinoma

Abstract Background Accurate prediction of disease-free survival after radical resection in patients with pancreatic ductal adenocarcinoma (PDAC) remains challenging. Therefore, this study establishes and validates a predictive model for disease-free survival (DFS) after radical resection in patients diagnosed with PDAC. Methods This study gathered clinical and preoperative imaging characteristics of 258 patients with PDAC who underwent radical resection at our institution. The patients were randomly allocated into a training set (n = 218) and a validation set (n = 40) at an 8:2 ratio. Survival outcomes were analyzed using Kaplan–Meier survival analysis with the log-rank test. A nomogram was developed following univariate and multivariate Cox analyses. The performance of the nomogram was assessed using the concordance index (C-index), calibration curves, and decision curves analysis (DCA). An X-tile analysis was conducted to identify three risk groups. Results Body mass index, preoperative carbohydrate antigen 19 − 9 (CA19-9) > 1000 U/mL, N stage, superior mesenteric vein involvement, and superior mesenteric artery involvement were independent influencing factors of DFS (p < 0.05). Subsequently, a predictive nomogram was developed. The C-index of the model in the training set and validation set was 0.66 (95% confidence interval (95% CI): 0.64–0.68) and 0.60 (95% CI: 0.53–0.67), respectively, with calibration curves indicating good agreement. DCAs demonstrated the clinical utility of the nomogram model. Additionally, the nomogram classified patients into three distinct score groups (low, medium, and high). Conclusions We successfully identified independent factors influencing DFS and developed a user-friendly and efficient prediction nomogram.