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Nomogram to predict liver surgery-specific complications for hepatocellular carcinoma: A multicenter study
Weili Qi1, Junlong Dai1, Zhancheng Qiu1
1Department of Liver Surgery, West China Hospital, Sichuan University, Chengdu, 610041, China.
Summary
This study developed a nomogram to predict liver surgery complications in hepatocellular carcinoma (HCC) patients. The model identifies key predictors, aiding surgeons in better treatment decisions and resource allocation for improved patient outcomes.
Area of Science:
- Hepatocellular Carcinoma (HCC) Research
- Surgical Oncology
- Predictive Modeling in Medicine
Background:
- Early identification of patients at risk for surgical complications is crucial for optimizing treatment decisions and resource utilization.
- Hepatocellular carcinoma (HCC) patients undergoing hepatectomy face risks of liver surgery-specific complications.
- Developing predictive tools can enhance preoperative risk assessment for HCC patients.
Purpose of the Study:
- To develop and validate a nomogram for predicting the risk of moderate-to-severe liver surgery-specific complications after hepatectomy in HCC patients.
- To identify significant preoperative predictors of post-hepatectomy complications in HCC.
Main Methods:
- Retrospective enrollment of HCC patients who underwent radical hepatectomy across four medical centers in China (January 2014 - January 2019).
- Patients were randomly divided into training (70%) and validation (30%) cohorts.
- Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression was employed to construct the nomogram model.
Main Results:
- The nomogram incorporated six predictive variables: diabetes mellitus, major hepatectomy, platelet count (PLT), prothrombin time (PT), albumin-indocyanine green evaluation grade (ALICE grade), and prognostic nutrient index (PNI).
- The model demonstrated good predictive performance with a concordance index (C-index) of 0.751 and an area under the receiver operating characteristic curve (AUC) of 0.743 in the validation cohort.
- Decision curve analysis (DCA) confirmed the nomogram's significant clinical utility.
Conclusions:
- The developed nomogram provides reliable preoperative prediction of moderate-to-high risk complications for HCC patients undergoing hepatectomy.
- The identified predictors (diabetes, major hepatectomy, PLT, PT, ALICE grade, PNI) are valuable for risk stratification.
- This tool can assist surgeons in making informed treatment decisions and managing resources effectively for patients with HBV-related HCC.
