肝细胞癌肝切除术后肝衰竭发生的危险因素分析及预测模型构建

Risk factors for posthepatectomy liver failure in patients with hepatocellular carcinoma and construction of prediction model

  • 摘要:
    目的 探讨影响肝细胞癌肝切除术后肝衰竭(PHLF)发生的危险因素及预测模型构建。
    方法 采用回顾性病例对照研究方法。收集2019年1月至2022年1月中国科学技术大学附属第一医院收治的116例行肝细胞癌肝切除术患者的临床病理资料;男99例,女17例;年龄为(59±10)岁。观察指标:(1)PHLF发生情况。(2)影响PHLF发生的因素分析。(3)PHLF发生预测模型构建及评价。正态分布的计量资料以x±s表示,组间比较采用t检验;偏态分布的计量资料以MQ1,Q3)表示,组间比较采用秩和检验。计数资料以绝对数表示,组间比较采用χ²检验或Fisher确切概率法。单因素分析根据资料类型选择对应的统计学方法。多因素分析采用Logistic回归模型(前进法)。采用回归系数构建预测模型,绘制受试者工作特征曲线并计算曲线下面积进行效能评价。
    结果 (1)PHLF发生情况。116例患者中,27例发生PHLF,89例未发生PHLF。27例发生PHLF的患者中,行腹腔镜肝切除术13例,行开腹肝切除术14例。(2)影响PHLF发生的因素分析。多因素分析结果显示:术前门静脉癌栓、术前吲哚菁绿15 min滞留率(ICG R15)≥10%是影响PHLF发生的独立危险因素(优势比=13.463,4.702,95%可信区间为3.140~57.650,1.600~13.800,P<0.05)。(3)PHLF发生预测模型构建及评价。根据多因素分析结果,纳入术前门静脉癌栓和术前ICG R15构建预测肝细胞癌患者PHLF发生预测模型。预测模型曲线下面积为0.750(95%可信区间为0.654~0.846,P<0.05),灵敏度为0.551,特异度为0.852。
    结论 术前门静脉癌栓、术前ICG R15≥10%是影响PHLF发生的独立危险因素。以此构建预测肝细胞癌患者PHLF发生预测模型,预测效能良好。

     

    Abstract:
    Objective To investigate the risk factors for posthepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma and construction of prediction model.
    Methods The retrospective case‑control study was conducted. The clinicopathological data of 116 patients with hepatocellular carcinoma who underwent hepatectomy in the First Affiliated Hospital of University of Science and Technology of China from January 2019 to January 2022 were collected. There were 99 males and 17 females, aged (59±10)years. Observation indicators: (1) occurrence of PHLF; (2) analysis of factors influencing the occurrence of PHLF; (3) construction and evaluation of prediction model for PHLF. Measurement data with normal distribution were represented as Mean±SD, and comparison between groups was conducted using the t test. Measurement data with skewed distri-bution were represented as M(Q1,Q3), and comparison between groups was conducted using the rank sum test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test or Fisher exact probability. The univariate analysis was conducted using the corresponding statistical methods based on data type. Multivariate analysis was conducted using the Logistic regression model with forward method. The regression coefficient was used to construct the prediction model. The receiver operating characteristic curve was drawn, and the area under curve (AUC) was used to evaluate the predictive ability of prediction model.
    Results (1) Occurrence of PHLF. Of the 116 patients, there were 27 cases with PHLF and 89 cases without PHLF, respectively. Of the 27 patients with PHLF, 13 cases underwent laparoscopic hepatectomy and 14 cases underwent open hepatectomy. (2) Analysis of factors influencing the occurrence of PHLF. Results of multivariate analysis showed preoperative portal vein tumor thrombus and preoperative indocyanine green retention at 15 minutes (ICG R15) ≥10% were independent risk factors influencing the occurrence of PHLF (odds ratio=13.463, 4.702, 95% confidence interval as 3.140-57.650, 1.600-13.800, P<0.05). (3) Construction and evaluation of prediction model for PHLF. According to the multivariate analysis, preoperative portal vein tumor thrombus and preoperative ICG R15 were included to construct the prediction model for predicting the occurrence of PHLF in patients with hepatocellular carcinoma. The AUC, sensitivity, specificity of prediction model was 0.750 (95% confidence interval as 0.654-0.846, P<0.05), 0.551, 0.852, respectively.
    Conclusions Preoperative portal vein tumor thrombus and preoperative ICG R15 ≥10% are independent risk factors influen-cing the occurrence of PHLF. The prediction model based on these two factors has good efficacy in predicting PHLF of patients with hepatocellular carcinoma.

     

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