Liver and Bile
Model to predict major complications following liver resection for HCC in patients with metabolic syndrome
Background: Metabolic syndrome (MS) is rapidly growing as risk factor for hepatocellular carcinoma (HCC). Liver resection for HCC in patients with MS is associated with increased postoperative risks. There are no data on factors associated with postoperative complications.
Aims: The aim was to identify risk factors and develop and validate a model for postoperative major morbidity after liver resection for HCC in patients with MS, using a large multicentric Western cohort.
Materials and methods: The univariable logistic regression analysis was applied to select predictive factors for 90 days major morbidity. The model was built on the multivariable regression and presented as a nomogram. Performance was evaluated by internal validation through the bootstrap method. The predictive discrimination was assessed through the concordance index.
Results: A total of 1087 patients were gathered from 24 centers between 2001 and 2021. 484 patients (45.2%) were obese. Most liver resections were performed using an open approach (59.1%), and 743 (68.3%) underwent minor hepatectomies. 376 patients (34.6%) developed postoperative complications, with 13.8% major morbidity and 2.9% mortality rates. 713 patients had complete data and were included in the prediction model. The model identified obesity, diabetes, ischemic heart disease, portal hypertension, open approach, major hepatectomy, and changes in the non-tumoral parenchyma as risk factors for major morbidity. The model demonstrated an AUC of 72.8% (95% confidence interval: 67.2–78.2%) (https://childb.shinyapps.io/NomogramMajorMorbidity90days/).
Conclusions: Patients undergoing liver resection for hepatocellular carcinoma and metabolic syndrome are at high risk of postoperative major complications and death. Careful patient selection, considering baseline characteristics, liver function, and type of surgery, is key to achieving optimal outcomes.