Centre de Recherche sur l'Inflammation, UMR 1149 Inserm, Université Paris Diderot, Clichy, France; Service d'Hépatologie, AP-HP Hôpital Beaujon, Clichy, France.
Centre de Recherche sur l'Inflammation, UMR 1149 Inserm, Université Paris Diderot, Clichy, France; Service d'Hépatologie, AP-HP Hôpital Beaujon, Clichy, France.
Clin Gastroenterol Hepatol. 2015 Aug;13(8):1532-9.e1. doi: 10.1016/j.cgh.2014.12.017. Epub 2014 Dec 24.
BACKGROUND & AIMS: Noninvasive techniques are needed to assess hepatic fibrosis in patients with chronic hepatitis B. We developed a scoring system to determine the degree of fibrosis in patients with genotype B or genotype C hepatitis B virus (HBV) infection and positive for the hepatitis B e antigen.
We performed a retrospective study to identify baseline variables associated with the severity of fibrosis (METAVIR scores, F0-F4) in a large phase 3 clinical trial of predominantly Asian patients (n = 710), using multivariate logistic regression analyses. Significant variables were used to construct predictive models using optimal cut-off values. The final model was validated in similar patients from a large phase 4 clinical trial (n = 465).
We developed 2 prediction scoring systems (PSs). PS1 analyzed data on HBV genotype (B vs. C), patient age (<30 vs. ≥30 y), level of hepatitis B surface antigen (≤17,500 vs. >17,500 IU/mL), and level of alanine aminotransferase (≤3-fold vs. >3-fold the upper limit of normal). PS2 analyzed data on only age and level of hepatitis B surface antigen. PS1 identified patients with F0 to F1 vs. F2 to F4 fibrosis with more than 87% specificity and a positive predictive value greater than 75; it identified patients with F0 to F2 vs. F2 to F4 fibrosis with approximately 95% specificity and a positive predictive value (PPV) of approximately 97%. PS2 identified patients with F0 to F1 fibrosis with less accuracy than PS1, but identified patients with F0 to F2 fibrosis with an almost identical level of sensitivity and PPV.
We developed a simple scoring system to determine the severity of fibrosis in patients with genotypes B or C HBV infection who are hepatitis B e antigen positive. Our system differentiated patients with no or mild fibrosis (F0-F1) from those with marked or severe (F2-F4) fibrosis with a high PPV. The high level of specificity for the identification of nonsevere fibrosis (F0-F2) limits the risk of overlooking patients with severe fibrosis (F3-F4).
需要非侵入性技术来评估慢性乙型肝炎患者的肝纤维化程度。我们开发了一种评分系统，用于确定乙型肝炎病毒（HBV）基因型 B 或 C 感染且乙型肝炎 e 抗原阳性患者的纤维化程度。
我们进行了一项回顾性研究，以确定主要为亚洲患者的大型 3 期临床试验（n=710）中与纤维化严重程度（METAVIR 评分，F0-F4）相关的基线变量，使用多元逻辑回归分析。使用最佳截断值构建预测模型。使用来自大型 4 期临床试验的相似患者（n=465）对最终模型进行验证。
我们开发了 2 种预测评分系统（PS）。PS1 分析了 HBV 基因型（B 型与 C 型）、患者年龄（<30 岁与≥30 岁）、乙型肝炎表面抗原水平（≤17,500 与>17,500 IU/mL）和丙氨酸氨基转移酶水平（≤3 倍与>3 倍正常值上限）的数据。PS2 仅分析了年龄和乙型肝炎表面抗原水平的数据。PS1 可将 F0 至 F1 与 F2 至 F4 纤维化的患者识别出来，特异性超过 87%，阳性预测值大于 75%；将 F0 至 F2 与 F2 至 F4 纤维化的患者识别出来，特异性约为 95%，阳性预测值（PPV）约为 97%。PS2 识别 F0 至 F1 纤维化的准确性低于 PS1，但识别 F0 至 F2 纤维化的敏感性和 PPV 几乎相同。
我们开发了一种简单的评分系统，用于确定乙型肝炎病毒基因型 B 或 C 感染且乙型肝炎 e 抗原阳性患者的纤维化严重程度。我们的系统具有较高的阳性预测值，可将无或轻度纤维化（F0-F1）患者与明显或严重纤维化（F2-F4）患者区分开来。对非严重纤维化（F0-F2）的高特异性识别限制了漏诊严重纤维化（F3-F4）患者的风险。
