Abstract

Background

Advanced liver disease due to hepatitis C virus (HCV) is a leading cause of human immunodeficiency virus (HIV)-related morbidity and mortality. There remains a need to develop noninvasive predictors of clinical outcomes in persons with HIV/HCV coinfection.

Methods

We conducted a nested case-control study in 126 patients with HIV/HCV and utilized multiple quantitative metabolomic assays to identify a prognostic profile that predicts end-stage liver disease (ESLD) events including ascites, hepatic encephalopathy, hepatocellular carcinoma, esophageal variceal bleed, and spontaneous bacterial peritonitis. Each analyte class was included in predictive modeling, and area under the receiver operator characteristic curves (AUC) and accuracy were determined.

Results

The baseline model including demographic and clinical data had an AUC of 0.79. Three models (baseline plus amino acids, lipid metabolites, or all combined metabolites) had very good accuracy (AUC, 0.84–0.89) in differentiating patients at risk of developing an ESLD complication up to 2 years in advance. The all combined metabolites model had sensitivity 0.70, specificity 0.85, positive likelihood ratio 4.78, and negative likelihood ratio 0.35.

Conclusions

We report that quantification of a novel set of metabolites may allow earlier identification of patients with HIV/HCV who have the greatest risk of developing ESLD clinical events.

中文翻译：

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代谢组学特征可预测HIV / HCV合并感染患者的肝病事件。

摘要

背景

丙型肝炎病毒（HCV）导致的晚期肝病是人类免疫缺陷病毒（HIV）相关发病率和死亡率的主要原因。仍然需要开发HIV / HCV合并感染患者临床结果的非侵入性预测因子。

方法

我们对126例HIV / HCV患者进行了巢式病例对照研究，并利用多种定量代谢组学分析方法确定了预测终末期肝病（ESLD）事件的预后资料，包括腹水，肝性脑病，肝细胞癌，食道静脉曲张出血，和自发性细菌性腹膜炎。每个分析物类别都包括在预测建模中，并确定了接收器操作员特征曲线（AUC）和准确性下的面积。

结果

包括人口统计学和临床​​数据的基线模型的AUC为0.79。三种模型（基线加氨基酸，脂质代谢物或所有组合代谢物）在区分最可能提前2年发展为ESLD并发症风险的患者中具有非常好的准确性（AUC，0.84-0.89）。所有合并的代谢物模型的敏感性为0.70，特异性为0.85，正似然比为4.78，负似然比为0.35。

结论

我们报告说，对一组新的代谢产物进行定量可能可以更早地鉴定出具有发展ESLD临床事件最大风险的HIV / HCV患者。