A novel nomogram for predicting the risk of major complications after pancreaticoduodenectomy in patients with obstructive jaundice

Background: The aim of this study was to construct and internally validate a nomogram for predicting major complications in obstructive jaundice patients planned to undergo pancreaticoduodenectomy (PD). Methods: The clinical data of 835 obstructive jaundice patients who underwent PD in a high-volume center were collected and retrospectively analyzed during an 8-year period. Factors affecting the major complication rate were optimized by least absolute shrinkage and selection operator (LASSO) regression analysis and were incorporated in logistic regression analysis. The performance of this nomogram was evaluated by discrimination, calibration, internal validation and clinical utility. Results: Predictors included in the model were sex, American Society of Anesthesiologists (ASA) score, preoperative biliary drainage (PBD), neutrophil-to-lymphocyte ratio (NLR), hemoglobin, prealbumin, total bilirubin, transfusion, and pathology category. The model had good discrimination and calibration with a C-index of 0.700. Internal validation generated an acceptable C-index of 0.701. Decision curve analysis indicated this nomogram was clinically useful for predicting the possibility of major complications at a threshold between 1% and 59%. Conclusion: This novel nomogram could be conveniently used and assist in decisions for PBD in clinical practice.

Automated summary

A nomogram was constructed and internally validated for predicting major complications in patients with obstructive jaundice planned to undergo pancreaticoduodenectomy. The model showed good discrimination and calibration, providing clinical utility in predicting the possibility of major complications.