肝纤维化评分（Hepascore）：慢性丙型肝炎感染中肝纤维化的一种经过验证的准确预测指标。

Hepascore: an accurate validated predictor of liver fibrosis in chronic hepatitis C infection.

作者信息

Adams Leon A, Bulsara Max, Rossi Enrico, DeBoer Bastiaan, Speers David, George Jacob, Kench James, Farrell Geoffrey, McCaughan Geoffrey W, Jeffrey Gary P

机构信息

Department of Gastroenterology and Hepatology, Sir Charles Gairdner Hospital, Perth, Australia.

出版信息

Clin Chem. 2005 Oct;51(10):1867-73. doi: 10.1373/clinchem.2005.048389. Epub 2005 Jul 28.

DOI:10.1373/clinchem.2005.048389

PMID:16055434

Abstract

BACKGROUND

Staging hepatic fibrosis by liver biopsy guides prognosis and treatment of hepatitis C, but is invasive and expensive. We sought to create an algorithm of serum markers that accurately and reliably predict liver fibrosis stage among hepatitis C patients.

METHODS

Ten biochemical markers were measured at time of liver biopsy in 117 untreated hepatitis C patients (training set). Multivariate logistic regression and ROC curve analyses were used to create a predictive model for significant fibrosis (METAVIR F2, F3, and F4), advanced fibrosis (F3 and F4), and cirrhosis (F4). The model was validated in 104 patients from other institutions.

RESULTS

A model (Hepascore) of bilirubin, gamma-glutamyltransferase, hyaluronic acid, alpha(2)-macroglobulin, age, and sex produced areas under the ROC curves (AUCs) of 0.85, 0.96, and 0.94 for significant fibrosis, advanced fibrosis, and cirrhosis, respectively. In the training set, a score > or = 0.5 (range, 0.0-1.0) was 92% specific and 67% sensitive for significant fibrosis, a score <0.5 was 81% specific and 95% sensitive for advanced fibrosis, and a score <0.84 was 84% specific and 71% sensitive for cirrhosis. Among the validation set, the AUC for significant fibrosis, advanced fibrosis, and cirrhosis were 0.82, 0.90, and 0.89, respectively. A score > or = 0.5 provided a specificity and sensitivity of 89% and 63% for significant fibrosis, whereas scores <0.5 had 74% specificity and 88% sensitivity for advanced fibrosis.

CONCLUSIONS

A model of 4 serum markers plus age and sex provides clinically useful information regarding different fibrosis stages among hepatitis C patients.

摘要

背景

通过肝活检对肝纤维化进行分期可指导丙型肝炎的预后和治疗，但该方法具有侵入性且费用高昂。我们试图创建一种血清标志物算法，以准确可靠地预测丙型肝炎患者的肝纤维化分期。

方法

在117例未经治疗的丙型肝炎患者（训练集）进行肝活检时测量了10种生化标志物。采用多变量逻辑回归和ROC曲线分析来创建显著纤维化（METAVIR F2、F3和F4）、重度纤维化（F3和F4）以及肝硬化（F4）的预测模型。该模型在来自其他机构的104例患者中进行了验证。

结果

由胆红素、γ-谷氨酰转移酶、透明质酸、α2-巨球蛋白、年龄和性别组成的模型（Hepascore）对于显著纤维化、重度纤维化和肝硬化的ROC曲线下面积（AUC）分别为0.85、0.96和0.94。在训练集中，评分≥0.5（范围为0.0 - 1.0）对显著纤维化的特异性为92%，敏感性为67%；评分<0.5对重度纤维化的特异性为81%，敏感性为95%；评分<0.84对肝硬化的特异性为84%，敏感性为71%。在验证集中，显著纤维化、重度纤维化和肝硬化的AUC分别为0.82、0.90和0.89。评分≥0.5对显著纤维化的特异性和敏感性分别为89%和63%，而评分<0.5对重度纤维化的特异性为74%，敏感性为88%。