基于简单无创模型预测慢性乙型肝炎患者的肝坏死性炎症活动度。

Prediction of hepatic necroinflammatory activity in patients with chronic hepatitis B by a simple noninvasive model.

机构信息

Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Research and Therapy Center for Liver Diseases, Zhengxing Hospital, Zhangzhou, Fujian Province, China.

出版信息

J Transl Med. 2018 Jun 18;16(1):166. doi: 10.1186/s12967-018-1538-z.

DOI:10.1186/s12967-018-1538-z

PMID:29914513

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6006738/

Abstract

BACKGROUND

A model was constructed using clinical and serum variables to discriminate between chronic hepatitis B (CHB) patients with and without significant necroinflammatory activity (score 4-18 vs. score 0-3).

METHODS

Consecutive CHB patients who underwent liver biopsy were divided into two sequential groups: a training group (n = 401) and a validation group (n = 401). Multivariate analysis identified alanine aminotransferase, γ-glutamyltransferase, prothrombin time and albumin as independent predictors of necroinflammatory activity.

RESULTS

The area under the receiver operating characteristic curve was 0.826 for the training group and 0.847 for the validation group. Using a cut-off score of H ≤ 0.375, significant necroinflammatory activity (score 4-18) was excluded with high accuracy [78.2% negative predictive value (NPV), 72% positive predictive value (PPV), and 90.8% sensitivity] in 238 (59.4%) of 401 patients in the training group and with the same certainty (88.1% NPV, 61.2% PPV, and 95.1% sensitivity) among 204 (50.9%) of 401 patients in the validation group. Similarly, applying a cut-off score of H > 0.720, significant necroinflammatory activity was correctly identified with high accuracy (90.8% PPV, 57.7% NPV, and 92.0% specificity) in 150 (37.4%) of 401 patients in the training group and with the same certainty (91.8% PPV, 64.6% NPV, and 95.4% specificity) in 188 (46.9%) of 401 patients in the validation group.

CONCLUSIONS

A predictive model based on easily accessible variables identified CHB patients with and without significant necroinflammatory activity with a high degree of accuracy. This model may decrease the need for liver biopsy for necroinflammatory activity grading in 72.1% of CHB patients.

摘要

背景

建立了一个模型，用于区分慢性乙型肝炎（CHB）患者是否具有显著的坏死性炎症活动（评分 4-18 与评分 0-3），该模型使用临床和血清变量。

方法

对接受肝活检的连续 CHB 患者进行分组，分为两个连续组：训练组（n=401）和验证组（n=401）。多变量分析确定丙氨酸氨基转移酶、γ-谷氨酰转移酶、凝血酶原时间和白蛋白为坏死性炎症活动的独立预测因子。

结果

训练组的受试者工作特征曲线下面积为 0.826，验证组为 0.847。使用 H≤0.375 的截断值，在训练组的 401 名患者中有 238 名（78.2%阴性预测值（NPV）、72%阳性预测值（PPV）和 90.8%敏感性），在验证组的 401 名患者中有 204 名（88.1%NPV、61.2%PPV 和 95.1%敏感性）能够以高准确率排除显著的坏死性炎症活动（评分 4-18）。同样，应用 H>0.720 的截断值，在训练组的 401 名患者中有 150 名（90.8%PPV、57.7%NPV 和 92.0%特异性），在验证组的 401 名患者中有 188 名（91.8%PPV、64.6%NPV 和 95.4%特异性）能够以高准确率正确识别显著的坏死性炎症活动。