终末期肝病模型评分和标准化残肝体积比预测肝细胞癌肝切除术后肝功能衰竭

摘要/Abstract

摘要： 目的评价标准化残肝体积比(sFLR)和终末期肝病模型(MELD)评分预测肝细胞癌(HCC)患者肝切除术后肝功能衰竭(PHLF)的价值。方法 2015年10月至2021年2月术前腹部三维CT重建、施行肝切除术HCC患者74例(男58例、女16例)。采用单因素和多因素Logistic回归分析探讨与PHLF相关的影响因素,ROC曲线分析确定PHLF独立影响因素。结果 74例HCC患者PHLF 28例(PHLF组)、非PHLF 46例(非PHLF组)。PHLF组、非PHLF组患者PLT分别为123(29,238)×10⁹/L、168(38,538)×10⁹/L,差异具有统计学意义(P<0.05);Alb分别为36.3(26.0,41.2)g/L、42.8(25.6,48.8)g/L,差异具有统计学意义(P<0.05);sFLR分别为0.50(0.38,0.78)、0.67(0.36,0.99),差异具有统计学意义(P<0.05);MELD评分分别为9(6,12)分、7(6,10)分,差异具有统计学意义(P<0.05)。而两组年龄、性别、PT、INR、ALT、HBsAg及肿瘤直径等均不存在显著差异(P>0.05)。将PLT、Alb、sFLR及MELD评分纳入多因素Logistic回归分析,提示PLT、Alb、sFLR及MELD评分均是HCC患者PHLF发生的独立预测因素(P<0.05)。sFLR诊断HCC患者PHLF发生时的截断值、敏感度、特异度分别为0.54、76.9%及73.9%,MELD评分诊断HCC患者PHLF发生时的截断值、敏感度、特异度分别为8.5、53.8%及82.6%,两者联合诊断时敏感度、特异度为80.8%、91.3%。sFLR联合MELD评分诊断HCC患者PHLF发生时的AUC值均分别显著高于sFLR、MELD评分(P<0.05)。结论 sFLR联合MELD评分是预测HCC患者PHLF发生的有效指标,该预测模型能有效指导肝切除术后的早期处理,改善预后,降低死亡率,为肝切除术的术前评估提供了新思路。

关键词: 肝细胞癌, 肝切除术后肝功能衰竭, 标准化残肝体积比, 终末期肝病模型评分

Abstract: Objective To evaluate the value of standardized future liver remnant (sFLR) and score of model for end-stage liver disease (MELD) in predicting post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC). Methods From October 2015 to February 2021, seventy-four HCC patients including 58 males and 16 females who underwent abdominal three-dimensional CT reconstruction and hepatectomy were enrolled in this study. Univariate and multivariate Logistic regression analysis were used to explore the influencing factors related to PHLF. Receiver operating characteristic curve (ROC) analysis was used to determine the independent influencing factors of PHLF. Results There were 28 PHLF cases (PHLF group) and 46 non-PHLF cases (non-PHLF group) in 74 HCC patients. The PLT, Alb, sFLR and MELD scores of patients in PHLF group and non-PHLF group were 123 (29, 238)×10⁹/L and 168 (38, 538)×10⁹/L, 36.3 (26.0, 41.2) g/L and 42.8 (25.6, 48.8) g/L, 0.50 (0.38, 0.78) and 0.67(0.36, 0.99), 9 (6,12) points and 7 (6,10) points, respectively, with statistically significant differences (P<0.05). There was no significant difference in age, sex, PT, INR, ALT, HBsAg and tumor diameter between these two groups (P>0.05). The scores of PLT, Alb, sFLR and MELD were included in multivariate Logistic regression analysis, and the result showed that PLT, Alb, sFLR and MELD were independent predictors of PHLF in HCC patients (P<0.05). The cutoff value, sensitivity and specificity of sFLR in diagnosing PHLF in HCC patients were 0.54, 76.9% and 73.9%, respectively, while the cutoff value, sensitivity and specificity of MELD score in diagnosing PHLF in HCC patients were 8.5, 53.8% and 82.6%, respectively. The AUC value of sFLR in combination with MELD score in diagnosing PHLF in HCC patients were significantly higher than that of sFLR or MELD score alone (P<0.05). Conclusion sFLR in combination with MELD score is an effective index to predict PHLF in HCC patients. This prediction model can effectively guide the early treatment, improve prognosis and reduce mortality of HCC patients after hepatectomy, and provide a new method for preoperative evaluation.

Key words: Hepatocellular carcinoma, Post-hepatectomy liver failure, Standardized future liver remnant, Model for end-stage liver disease

张丰晓, 白雪松, 胡敬华. 终末期肝病模型评分和标准化残肝体积比预测肝细胞癌肝切除术后肝功能衰竭[J]. 肝脏, 2022, 27(2): 196-198.

ZHANG Feng-xiao, BAI Xue-song, HU Jinghua. Prediction of post-hepatectomy liver failure for hepatocellular carcinoma by model for end-stage liver disease and standardized future liver remnant[J]. Chinese Hepatolgy, 2022, 27(2): 196-198.

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