Preoperative risk stratification of postoperative pancreatic fistula: A risk-tree predictive model for pancreatoduodenectomy

Background: Existing postoperative pancreatic fistula risk scores rely on intraoperative parameters, which limits their value in the preoperative setting. A preoperative predictive model to stratify the risk of developing postoperative pancreatic fistula before pancreatoduodenectomy was built and externally validated. Methods: A regression risk-tree model for preoperative postoperative pancreatic fistula risk stratification was developed in the Verona University Hospital training cohort using preoperative variables and then tested prospectively in a validation cohort of patients who underwent pancreatoduodenectomy at San Raffaele Hospital of Milan. Results: In the study period 566 (training cohort) and 456 (validation cohort) patients underwent pancreatoduodenectomy. In the multivariable analysis body mass index, radiographic main pancreatic duct diameter and American Society of Anesthesiologists score ≥3 were independently associated with postoperative pancreatic fistula. The regression tree analysis allocated patients into 3 preoperative risk groups with an 8%, 21%, and 32% risk of postoperative pancreatic fistula (all P < .01) based on main pancreatic duct diameter (≥ or <5 mm) and body mass index (≥ or <25). The 3 groups were labeled low, intermediate, and high risk and consisted of 206 (37%), 188 (33%), and 172 (30%) patients, respectively. The risk-tree was applied to validation cohort, successfully reproducing 3 risk groups with significantly different postoperative pancreatic fistula risks (all P < .01). Conclusion: In candidates for pancreatoduodenectomy, the risk of postoperative pancreatic fistula can be quickly and accurately determined in the preoperative setting based on the body mass index and main pancreatic duct diameter at radiology. Preoperative risk stratification could potentially guide clinical decision-making, improve patient counseling and allow the establishment of personalized preoperative protocols.