应用 Hy's 法则和一种新的复合算法预测药物性肝损伤患者的急性肝衰竭。
Use of Hy's law and a new composite algorithm to predict acute liver failure in patients with drug-induced liver injury.
机构信息
Unidad de Gestión Clínica de Enfermedades Digestivas, Servicio de Farmacología Clínica, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Universitario Virgen de la Victoria, Universidad de Málaga, Málaga, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Barcelona, Spain.
Unidad de Gestión Clínica de Enfermedades Digestivas, Servicio de Farmacología Clínica, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Universitario Virgen de la Victoria, Universidad de Málaga, Málaga, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Barcelona, Spain.
出版信息
Gastroenterology. 2014 Jul;147(1):109-118.e5. doi: 10.1053/j.gastro.2014.03.050. Epub 2014 Apr 1.
BACKGROUND & AIMS: Hy's Law, which states that hepatocellular drug-induced liver injury (DILI) with jaundice indicates a serious reaction, is used widely to determine risk for acute liver failure (ALF). We aimed to optimize the definition of Hy's Law and to develop a model for predicting ALF in patients with DILI.
METHODS
We collected data from 771 patients with DILI (805 episodes) from the Spanish DILI registry, from April 1994 through August 2012. We analyzed data collected at DILI recognition and at the time of peak levels of alanine aminotransferase (ALT) and total bilirubin (TBL).
RESULTS
Of the 771 patients with DILI, 32 developed ALF. Hepatocellular injury, female sex, high levels of TBL, and a high ratio of aspartate aminotransferase (AST):ALT were independent risk factors for ALF. We compared 3 ways to use Hy's Law to predict which patients would develop ALF; all included TBL greater than 2-fold the upper limit of normal (×ULN) and either ALT level greater than 3 × ULN, a ratio (R) value (ALT × ULN/alkaline phosphatase × ULN) of 5 or greater, or a new ratio (nR) value (ALT or AST, whichever produced the highest ×ULN/ alkaline phosphatase × ULN value) of 5 or greater. At recognition of DILI, the R- and nR-based models identified patients who developed ALF with 67% and 63% specificity, respectively, whereas use of only ALT level identified them with 44% specificity. However, the level of ALT and the nR model each identified patients who developed ALF with 90% sensitivity, whereas the R criteria identified them with 83% sensitivity. An equal number of patients who did and did not develop ALF had alkaline phosphatase levels greater than 2 × ULN. An algorithm based on AST level greater than 17.3 × ULN, TBL greater than 6.6 × ULN, and AST:ALT greater than 1.5 identified patients who developed ALF with 82% specificity and 80% sensitivity.
CONCLUSIONS
When applied at DILI recognition, the nR criteria for Hy's Law provides the best balance of sensitivity and specificity whereas our new composite algorithm provides additional specificity in predicting the ultimate development of ALF.
背景与目的
Hy's 法则指出，伴有黄疸的肝细胞性药物性肝损伤（DILI）提示严重反应，广泛用于确定急性肝衰竭（ALF）的风险。我们旨在优化 Hy's 法则的定义，并开发一种预测 DILI 患者 ALF 的模型。
方法
我们从 1994 年 4 月至 2012 年 8 月间西班牙 DILI 登记处的 771 例 DILI 患者（805 例发作）中收集数据。我们分析了在 DILI 识别时和丙氨酸氨基转移酶（ALT）和总胆红素（TBL）峰值时收集的数据。
结果
在 771 例 DILI 患者中，32 例发展为 ALF。肝细胞损伤、女性、高 TBL 水平和天冬氨酸氨基转移酶（AST）与 ALT 的比值高是 ALF 的独立危险因素。我们比较了 3 种使用 Hy's 法则预测哪些患者会发生 ALF 的方法；所有方法均包括 TBL 大于正常值上限（×ULN）的 2 倍，以及 ALT 水平大于 3×ULN、比值（R）值（ALT×ULN/碱性磷酸酶×ULN）大于 5 或更高，或新比值（nR）值（ALT 或 AST，产生的最高×ULN/碱性磷酸酶×ULN 值）大于 5 或更高。在 DILI 识别时，R 模型和 nR 模型分别以 67%和 63%的特异性识别出发生 ALF 的患者，而仅使用 ALT 水平的识别特异性为 44%。然而，ALT 水平和 nR 模型均以 90%的敏感性识别出发生 ALF 的患者，而 R 标准的敏感性为 83%。发生 ALF 和未发生 ALF 的患者碱性磷酸酶水平均大于 2×ULN 的患者数量相等。基于 AST 水平大于 17.3×ULN、TBL 大于 6.6×ULN 和 AST:ALT 大于 1.5 的算法识别出发生 ALF 的患者特异性为 82%，敏感性为 80%。
结论
在 DILI 识别时应用，nR 标准的 Hy's 法则提供了最佳的敏感性和特异性平衡，而我们的新综合算法在预测最终 ALF 的发展方面提供了额外的特异性。
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