Prediction of postoperative pancreatic fistula and pancreatitis after pancreatoduodenectomy or distal pancreatectomy: A review

Background and objective: Postoperative pancreatic fistula (POPF) is the leading cause of morbidity and early mortality in patients undergoing pancreatic resection. In addition, recent studies have identified postoperative acute pancreatitis (POAP) as an independent contributor to morbidity. Most perioperative mitigation strategies experimented for POPF have been shown to be in vain with no consensus on the best perioperative management. Clinical prediction models have been developed with the hope of identifying high POPF risk patients with the leading idea of finding subpopulations possibly benefiting from pre-existing or novel mitigation strategies. The aim of this review was to map out the existing prediction modeling studies to better understand the current stage of POPF prediction modeling, and the methodology behind them.

Methods: A narrative review of the existing POPF prediction model studies was performed. Studies published before September 2022 were included.

Results: While the number of POPF prediction models for pancreatoduodenectomy has increased, none of the currently existing models stand out from the crowd. For distal pancreatectomy, two unique POPF prediction models exist, but due to their freshness, no further external validation or adoption in clinics or research has been reported. There seems to be a lack of adherence to correct methodology or reporting guidelines in most of the studies, which has rendered external validity-if assessed-low. Few of the most recent studies have demonstrated preoperative assessment of pancreatic aspects from computed tomography (CT) scans to provide relatively strong predictors of POPF.

Conclusions: Main goal for the future would be to reach a consensus on the most important POPF predictors and prediction model. At their current state, few models have demonstrated adequate transportability and generalizability to be up to the task. Better understanding of POPF pathophysiology and the possible driving force of acute inflammation and POAP might be required before such a prediction model can be accessed.