Usefulness of the estimation of physiologic ability and surgical stress (E-PASS) system for prediction of complication and prognosis in hepatocellular carcinoma patients after hepatectomy

评估生理能力和手术应激(E-PASS)系统在预测肝细胞癌患者肝切除术后并发症和预后中的应用价值

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Abstract

BACKGROUND: Estimation of physiologic ability and surgical stress (E-PASS) system was verified in predicting postoperative complications or mortality in many surgical operations. This research aimed to investigate whether the E-PASS system could predict postoperative complications and was related with long-term prognosis in primary hepatocellular carcinoma (HCC) patients. METHODS: A total of 236 HCC patients who underwent liver resection were collected in this study. We performed univariate analyses to determine the potential risk factors for complications after hepatectomy. The potential independent risk factors were then included in the logistic regression for multivariable analysis. The optimal cutoff value of Comprehensive Risk Score (CRS) was identified by a receiver operating characteristic (ROC) curve. Based on this value, the patients were divided into two groups to investigate the relation between CRS with postoperative complications. The relation between CRS and overall survival (OS) or recurrence-free survival (RFS) was analyzed further in these two groups. RESULTS: Postoperative complications occurred in 79 patients. Multivariable analysis suggested that CRS was independent factor for predicting postoperative complications (P<0.001). The optimal CRS cutoff value in our study was 0.126. Patients with high Preoperative Risk Score (PRS) had a higher rate of postoperative complications occurrence, both major and mild complications (P<0.001). Our study showed that HCC patients with higher CRS had poorer survival prognosis [hazard ratio (HR): 3.735, 95% confidence interval (CI): 1.200-11.631, P=0.023]. The 3-year OS rate of high CRS group (CRS ≥0.126) and low CRS group (CRS <0.126) were 66.2% vs. 84.8% (P<0.001), respectively. CONCLUSIONS: For HCC patients after liver resection, E-PASS was an effective predictive system for evaluating the risks of postoperative complications and may can predict prognosis in long term.

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