Prediction of Isolated Local Recurrence After Resection of Pancreatic Ductal Adenocarcinoma: A Nationwide Study

Background: Distinguishing postoperative fibrosis from isolated local recurrence (ILR) after resection of pancreatic ductal adenocarcinoma (PDAC) is challenging. A prognostic model that helps to identify patients at risk of ILR can assist clinicians when evaluating patients’ postoperative imaging. This nationwide study aimed to develop a clinically applicable prognostic model for ILR after PDAC resection. Patients and Methods: An observational cohort study was performed, including all patients who underwent PDAC resection in the Netherlands (2014–2019; NCT04605237). On the basis of recurrence location (ILR, systemic, or both), multivariable cause-specific Cox-proportional hazard analysis was conducted to identify predictors for ILR and presented as hazard ratios (HRs) with 95% confidence intervals (CIs). A predictive model was developed using Akaike’s Information Criterion, and bootstrapped discrimination and calibration indices were assessed. Results: Among 1194/1693 patients (71%) with recurrence, 252 patients (21%) developed ILR. Independent predictors for ILR were resectability status (borderline versus resectable, HR 1.42; 95% CI 1.03–1.96; P = 0.03, and locally advanced versus resectable, HR 1.11; 95% CI 0.68–1.82; P = 0.66), tumor location (head versus body/tail, HR 1.50; 95% CI 1.00–2.25; P = 0.05), vascular resection (HR 1.86; 95% CI 1.41–2.45; P < 0.001), perineural invasion (HR 1.47; 95% CI 1.01–2.13; P = 0.02), number of positive lymph nodes (HR 1.04; 95% CI 1.01–1.08; P = 0.02), and resection margin status (R1 < 1 mm versus R0 ≥ 1 mm, HR 1.64; 95% CI 1.25–2.14; P < 0.001). Moderate performance (concordance index 0.66) with adequate calibration (slope 0.99) was achieved. Conclusions: This nationwide study identified factors predictive of ILR after PDAC resection. Our prognostic model, available through www.pancreascalculator.com, can be utilized to identify patients with a higher a priori risk of developing ILR, providing important information in patient evaluation and prognostication.