Data mining model using simple and readily available factors could identify patients at high risk for hepatocellular carcinoma in chronic hepatitis C
Data mining model using simple and readily available factors could identify patients at high risk for hepatocellular carcinoma in chronic hepatitis C
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DOI：
10.1016/j.jhep.2011.09.011
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发表时间：
2012-03-01
影响因子：
25.7
通讯作者：
Izumi, Namiki
中科院分区：
文献类型：
--
作者：
Kurosaki, Masayuki;Hiramatsu, Naoki;Izumi, Namiki
背景与目的：评估肝细胞癌（HCC）发生的风险对于制定慢性丙型肝炎的个性化监测或抗病毒治疗计划至关重要。我们的目的是建立一个简单的模型来识别发生HCC高风险的患者。方法：通过数据挖掘对随访至少5年的慢性丙型肝炎患者（n = 1003）进行分析，建立HCC的预测模型 发展。该模型使用 1072 名患者进行了外部验证（472 名患者出现持续病毒学应答 (SVR)，600 名患者接受 PEG 干扰素加利巴韦林治疗后未出现 SVR）。结果：根据年龄、血小板、白蛋白和天冬氨酸转氨酶等因素，HCC 风险预测模型确定了 HCC 高、中、低风险亚组 5 年 HCC 发生率分别为 20.9%、6.3-7.3% 和 0-1.5%。通过外部验证确认了模型的再现性（r(2) = 0.981）。高风险和中风险组的 10 年 HCC 发生率也显着高于低风险组（24.5% vs. 4.8%；p
Background & Aims: Assessment of the risk of hepatocellular carcinoma (HCC) development is essential for formulating personalized surveillance or antiviral treatment plan for chronic hepatitis C. We aimed to build a simple model for the identification of patients at high risk of developing HCC.Methods: Chronic hepatitis C patients followed for at least 5 years (n = 1003) were analyzed by data mining to build a predictive model for HCC development. The model was externally validated using a cohort of 1072 patients (472 with sustained virological response (SVR) and 600 with nonSVR to PEG-interferon plus ribavirin therapy).Results: On the basis of factors such as age, platelet, albumin, and aspartate aminotransferase, the HCC risk prediction model identified subgroups with high-, intermediate-, and low-risk of HCC with a 5-year HCC development rate of 20.9%, 6.3-7.3%, and 0-1.5%, respectively. The reproducibility of the model was confirmed through external validation (r(2) = 0.981). The 10-year HCC development rate was also significantly higher in the high- and intermediate-risk group than in the low-risk group (24.5% vs. 4.8%; p