Development and Validation of a Prediction Score for Complications after Hepatectomy in Hepatitis B-Related Hepatocellular Carcinoma Patients

Haiqing Wang, Jian Yang, Jiayin Yang, Li Jiang, Tianfu Wen, Wentao Wang, Mingqing Xu, Bo Li and Lunan Yan

PLOS ONE, 2014, vol. 9, issue 8, 1-8

Abstract: Objective and Background: The aim of the present study was to develop and validate a prediction score for postoperative complications by severity and guide perioperative management and patient selection in hepatitis B-related hepatocellular carcinoma patients undergoing liver resection. Methods: A total of 1543 consecutive liver resections cases were included in the study. Randomly selected sample set of 70% of the study cohort was used to develop a score to predict complications III–V and the remaining 30% was used to validate the score. Based on the preoperative and predictable intraoperative parameters, logistic regression analysis was used to identify risk factors and create an integer score for the predicting of complication. Results: American Society of Anesthesiologists category, portal hypertension, major liver resection (more than 3 segments) and extrahepatic procedures were identified as independent predictors for complications III–V by logistic regression analysis. A score system integrating these 4 factors was stratified into three groups and significantly predicted the risk of complications III–V, with a rate of 1.6%, 11.9% and 65.6% for low, moderate and high risk, respectively. Using the score, the complications risk could be predicted accurately in the validation set, without significant differences between predicted (10.4%) and observed (8.4%) risks for complications III–V (P = 0.466). Conclusions: Based on four preoperative risk factors, we have developed and validated an integer-based risk score to predict postoperative severe complications after liver resection for hepatitis B-related hepatocellular carcinoma patients in high-volume surgical center. This score may contribute to preoperative risk stratification and clinical decision-making.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0105114

DOI: 10.1371/journal.pone.0105114

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