External Validation of a Risk Model for Severe Complications following Pancreatoduodenectomy Based on Three Preoperative Variables

SIMPLE SUMMARY: Up to 30% of patients develop severe complications following pancreatoduodenectomy (PD). With respect to risk stratification and shared decision making, prediction models to predict complications are crucial. In 2015, a risk model for severe complications was developed by Schroder et al. based on three preoperative variables: BMI, ASA classification and mean Hounsfield Units of the pancreatic body on the preoperative abdominal CT scan. However, external validation of this model has not yet been performed. It is important to validate prediction models externally before implementing them in clinical practice to confirm their accuracy and generalizability when applied to a different patient population. Our aim was to externally validate this risk prediction model using an independent cohort of patients. ABSTRACT: Background: Pancreatoduodenectomy (PD) is the only cure for periampullary and pancreatic cancer. It has morbidity rates of 40–60%, with severe complications in 30%. Prediction models to predict complications are crucial. A risk model for severe complications was developed by Schroder et al. based on BMI, ASA classification and Hounsfield Units of the pancreatic body on the preoperative CT scan. These variables were independent predictors for severe complications upon internal validation. Our aim was to externally validate this model using an independent cohort of patients. Methods: A retrospective analysis was performed on 318 patients who underwent PD at our institution from 2013 to 2021. The outcome of interest was severe complications Clavien–Dindo ≥ IIIa. Model calibration, discrimination and performance were assessed. Results: A total of 308 patients were included. Patients with incomplete data were excluded. A total of 89 (28.9%) patients had severe complications. The externally validated model achieved: C-index = 0.67 (95% CI: 0.60–0.73), regression coefficient = 0.37, intercept = 0.13, Brier score = 0.25. Conclusions: The performance ability, discriminative power, and calibration of this model were acceptable. Our risk calculator can help surgeons identify high-risk patients for post-operative complications to improve shared decision-making and tailor perioperative management.