Discrimination of Nonalcoholic Steatohepatitis Using Transient Elastography in Patients with Nonalcoholic Fatty Liver Disease.
Discrimination of Nonalcoholic Steatohepatitis Using Transient Elastography in Patients with Nonalcoholic Fatty Liver Disease.
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DOI：
10.1371/journal.pone.0157358
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Han KH
中科院分区：
文献类型：
--
作者：
Lee HW;Park SY;Kim SU;Jang JY;Park H;Kim JK;Lee CK;Chon YE;Han KH
非侵入性标记物鉴别非酒精性脂肪性肝炎(NASH)的准确性并不令人满意。我们研究了瞬时弹性成像(TE)能否将NASH患者与非酒精性脂肪性肝病(NAFLD)患者区分开来。这些疑似NAFLD的患者在2011年11月至2013年12月期间从五个三级中心招募，他们接受了肝脏活检和伴随TE。研究人群(n=183)的平均年龄为40.6岁，男性占优势(n=111，60.7%)。在研究参与者中，89人(48.6%)患有非NASH，94人(51.4%)患有NASH。受控衰减参数(CAP)和肝脏硬度(LS)分别与脂肪变性程度(r=0.656，P&t；0.001)和肝纤维化程度(r=0.714，P<；0.001)显著相关。脂肪变性的最佳临界值为：S1为247dB/m，S2为280dB/m，S3为300dB/m。基于多变量分析得到的独立预测因子[P=0.044，优势比(OR)4.133，95%可信区间(CI)1.037~16.470；P=0.013，OR 3.399，95%CI 1.295~8.291；P<；0.001，OR 7.557，95%CI 2.997~19.059(丙氨酸氨基转移酶)；60IU/L]，我们建立了一个新的鉴别NASH患者的CLA模型。CLA模型具有良好的判别能力，其受试者工作特征曲线下面积为0.812(95%可信区间0.724~0.880)。为了评估判别能力，Bootstrap方法确定的AUROC在迭代之间基本保持不变，平均值为0.833(95%CI 0.740-0.893)。这一新的基于TE的CLA模型在区分NASH和单纯性脂肪变性方面显示出可接受的准确性。然而，还需要进一步的研究来进行外部验证。
The accuracy of noninvasive markers to discriminate nonalcoholic steatohepatitis (NASH) is unsatisfactory. We investigated whether transient elastography (TE) could discriminate patients with NASH from those with nonalcoholic fatty liver disease (NAFLD). The patients suspected of NAFLD who underwent liver biopsy and concomitant TE were recruited from five tertiary centers between November 2011 and December 2013. The study population (n = 183) exhibited a mean age of 40.6 years and male predominance (n = 111, 60.7%). Of the study participants, 89 (48.6%) had non-NASH and 94 (51.4%) had NASH. The controlled attenuation parameter (CAP) and liver stiffness (LS) were significantly correlated with the degrees of steatosis (r = 0.656, P<0.001) and fibrosis (r = 0.714, P<0.001), respectively. The optimal cut-off values for steatosis were 247 dB/m for S1, 280 dB/m for S2, and 300 dB/m for S3. Based on the independent predictors derived from multivariate analysis [P = 0.044, odds ratio (OR) 4.133, 95% confidence interval (CI) 1.037–16.470 for CAP>250 dB/m; P = 0.013, OR 3.399, 95% CI 1.295–8.291 for LS>7.0 kPa; and P<0.001, OR 7.557, 95% CI 2.997–19.059 for Alanine aminotransferase>60 IU/L], we developed a novel CLA model for discriminating patients with NASH. The CLA model showed good discriminatory capability, with an area under the receiver operating characteristic curve (AUROC) of 0.812 (95% CI 0.724–0.880). To assess discriminatory power, the AUROCs, as determined by the bootstrap method, remained largely unchanged between iterations, with an average value of 0.833 (95% CI 0.740–0.893). This novel TE-based CLA model showed acceptable accuracy in discriminating NASH from simple steatosis. However, further studies are required for external validation.