A model for predicting pancreatic leakage after pancreaticoduodenectomy based on the international study group of pancreatic surgery classification

Abstract

Backgrounds/Aims: With recent advances in pancreatic surgery, pancreaticoduodenectomy (PD) has become increasingly safe. However, pancreatic leakage is still one of the leading postoperative complications. An accurate prediction model for pancreatic leakage after PD can be helpful for pancreas surgeons. The aim of this study was to provide a new model that was simple and useful with high accuracy for predicting pancreatic leakage after PD. Methods: To predict the occurrence of pancreatic leakage, several factors were selected using bivariate analysis and univariate logistic regression analysis. The final model was developed using multivariable logistic regression analysis in the model construction data set. Results: Overall, 41 of 100 patients had pancreatic leakage by the International Study Group on Pancreatic Fistula (ISGPF) criteria. Soft pancreatic parenchyma, small pancreatic duct diameter (≤3 mm), and combined resection of SMV and portal vein were independently predictive of pancreatic leakage. The risk score (R) for individual patients can be calculated by combining the 3 prognostic values with the regression test: R= 0.5986+(0.5533×pancreatic parenchyma)+(0.5448×pancreatic duct diameter)+(0.8453×combined resection). The overall predictive accuracy of the model, as measured by the receiver operating characteristic (ROC) curve, was 0.728 Conclusions: Although continued refinements and improvements in the model are needed, the present model may assist pancreatic surgeons in the prediction of pancreatic leakage after PD.