Risk Models for Developing Pancreatic Fistula after Pancreatoduodenectomy: Validation in a Nationwide Prospective Cohort

To evaluate the performance of published fistula risk models by external validation, and to identify independent risk factors for postoperative pancreatic fistula (POPF).Multiple risk models have been developed to predict POPF after pancreatoduodenectomy. External validation in high-quality prospective cohorts is, however, lacking or only performed for individual models.A post hoc analysis of data from the stepped-wedge cluster cluster-randomized Care After Pancreatic Resection According to an Algorithm for Early Detection and Minimally Invasive Management of Pancreatic Fistula versus Current Practice (PORSCH) trial was performed. Included were all patients undergoing pancreatoduodenectomy in the Netherlands (January 2018-November 2019). Risk models on POPF were identified by a systematic literature search. Model performance was evaluated by calculating the area under the receiver operating curves (AUC) and calibration plots. Multivariable logistic regression was performed to identify independent risk factors associated with clinically relevant POPF.Overall, 1358 patients undergoing pancreatoduodenectomy were included, of whom 341 patients (25%) developed clinically relevant POPF. Fourteen risk models for POPF were evaluated, with AUCs ranging from 0.62 to 0.70. The updated alternative fistula risk score had an AUC of 0.70 (95% confidence intervals [CI]: 0.69-0.72). The alternative fistula risk score demonstrated an AUC of 0.70 (95% CI: 0.689-0.71), whilst an AUC of 0.70 (95% CI: 0.699-0.71) was also found for the model by Petrova and colleagues. Soft pancreatic texture, pathology other than pancreatic ductal adenocarcinoma or chronic pancreatitis, small pancreatic duct diameter, higher body mass index, minimally invasive resection and male sex were identified as independent predictors of POPF.Published risk models predicting clinically relevant POPF after pancreatoduodenectomy have a moderate predictive accuracy. Their clinical applicability to identify high-risk patients and guide treatment strategies is therefore questionable.