Preoperative Risk Prediction for Pancreatectomy: A Comparative Analysis of Three Scoring Systems.

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The Journal of surgical research


oregon; portland; cards; cards publication


INTRODUCTION: Pancreatectomy is associated with high morbidity and mortality. Therefore, patient selection and risk prediction is paramount. In this study, three validated perioperative risk scoring systems were compared among patients undergoing pancreatectomy to identify the most clinically useful model.

MATERIALS AND METHODS: The 2014-2017 American College of Surgeons National Surgical Quality Improvement Program database was queried for pancreatectomy patients. Three models were evaluated: National Surgical Quality Improvement Program Universal Risk Calculator (URC), Model for End-Stage Liver Disease (MELD), and Modified Frailty Index-5 Factor (mFI-5). Outcomes were 30-d mortality and complications. Predictive performance of the models was compared using area under the receiver operating characteristic curve (AUC) and Brier scores.

RESULTS: Twenty two thousand one hundred twenty three pancreatectomy patients were identified. The 30-d mortality rate was 1.4% (n = 319). Complications occurred in 6020 cases (27.2%). AUC (95% CI) for 30-d mortality were 0.70 (0.67-0.73), 0.63 (0.60-0.67), and 0.60 (0.57-0.63) for URC, MELD, and mFI-5, respectively, with Brier score of 0.014 for all three models. AUC (95% confidence interval) for any complication was 0.59 (0.58-0.59) for URC, 0.53 (0.52-0.54) for MELD, and 0.53 (0.52-0.54) for mFI-5, with Brier scores 0.193 (URC), 0.200 (MELD), and 0.197 (mFI-5). For individual complications, URC was more predictive than MELD or mFI-5.

CONCLUSIONS: Of the validated preoperative risk scoring systems, URC was most predictive of both complications and 30-d mortality. None of the models performed better than fair to good. The lack of predictive accuracy of currently existing models highlights the need for development of improved perioperative risk models.

Clinical Institute

Cardiovascular (Heart)