Ekaterina Petrova1, Hryhoriy Lapshyn1, Dirk Bausch1, Jan D'Haese2, Jens Werner2, Thomas Klier3, Natascha C Nüssler3, Jochen Gaedcke4, Michael Ghadimi4, Waldemar Uhl5, Orlin Belyaev5, Olga Kantor6, Marshall Baker7, Tobias Keck8, Ulrich F Wellner1. 1. Department of Surgery, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany. 2. Department of General, Visceral, and Transplant Surgery, University Hospital Munich, LMU, Munich, Germany. 3. Klinik für Allgemein-, Viszeralchirurgie und endokrine Chirurgie, Städtisches Klinikum München GmbH, Klinikum Neuperlach, Munich, Germany. 4. Klinik für Allgemein-, Viszeral- und Kinderchirurgie, Universitätsmedizin Göttingen, Göttingen, Germany. 5. St. Josef-Hospital Bochum, Department of Surgery, Hospital of the Ruhr-University, Bochum, Germany. 6. University of Chicago, Department of Surgery, Chicago, IL, USA. 7. Associate Professor of Surgery at Loyola University, Stritch School of Medicine, Maywood, IL, USA. 8. Department of Surgery, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany. Electronic address: tobias.keck@uksh.de.
Abstract
BACKGROUND: Postoperative pancreatic fistula (POPF) is a major factor for morbidity and mortality after pancreatic resection. Risk stratification for POPF is important for adjustment of treatment, selection of target groups in trials and quality assessment in pancreatic surgery. In this study, we built a risk-prediction model for POPF based on a large number of predictor variables from the German pancreatic surgery registry StuDoQ|Pancreas. METHODS: StuDoQ|Pancreas was searched for patients, who underwent pancreatoduodenectomy from 2014 to 2016. A multivariable logistic regression model with elastic net regularization was built including 66 preoperative und intraoperative parameters. Cross-validation was used to select the optimal model. The model was assessed via area under the ROC curve (AUC) and calibration slope and intercept. RESULTS: A total of N = 2488 patients were included. In the optimal model the predictors selected were texture of the pancreatic parenchyma (soft versus hard), body mass index, histological diagnosis pancreatic ductal adenocarcinoma and operation time. The AUC was 0.70 (95% CI 0.69-0.70), the calibration slope 1.67 and intercept 1.12. In the validation set the AUC was 0.65 (95% CI 0.64-0.66), calibration slope and intercept were 1.22 and 0.42, respectively. CONCLUSION: The model we present is a valid measurement instrument for POPF risk based on four predictor variables. It can be applied in clinical practice as well as for risk-adjustment in research studies and quality assurance in surgery.
BACKGROUND:Postoperative pancreatic fistula (POPF) is a major factor for morbidity and mortality after pancreatic resection. Risk stratification for POPF is important for adjustment of treatment, selection of target groups in trials and quality assessment in pancreatic surgery. In this study, we built a risk-prediction model for POPF based on a large number of predictor variables from the German pancreatic surgery registry StuDoQ|Pancreas. METHODS: StuDoQ|Pancreas was searched for patients, who underwent pancreatoduodenectomy from 2014 to 2016. A multivariable logistic regression model with elastic net regularization was built including 66 preoperative und intraoperative parameters. Cross-validation was used to select the optimal model. The model was assessed via area under the ROC curve (AUC) and calibration slope and intercept. RESULTS: A total of N = 2488 patients were included. In the optimal model the predictors selected were texture of the pancreatic parenchyma (soft versus hard), body mass index, histological diagnosis pancreatic ductal adenocarcinoma and operation time. The AUC was 0.70 (95% CI 0.69-0.70), the calibration slope 1.67 and intercept 1.12. In the validation set the AUC was 0.65 (95% CI 0.64-0.66), calibration slope and intercept were 1.22 and 0.42, respectively. CONCLUSION: The model we present is a valid measurement instrument for POPF risk based on four predictor variables. It can be applied in clinical practice as well as for risk-adjustment in research studies and quality assurance in surgery.