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药物干预在非酒精性脂肪性肝病中的有效性:一项网状Meta分析。

Effectiveness of drug interventions in nonalcoholic fatty liver disease: A network meta-analysis.

作者信息

Huang Yi-Zhou, Yang Gang-Yi, Wang Cong, Chen Xing-Yu, Zhang Li-Li

机构信息

Department of Endocrinology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing 404100, China.

出版信息

World J Diabetes. 2021 Sep 15;12(9):1576-1586. doi: 10.4239/wjd.v12.i9.1576.

DOI:10.4239/wjd.v12.i9.1576
PMID:34630909
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8472495/
Abstract

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is a major chronic liver disorder worldwide, and there is no established treatment for this disease. We conducted a network meta-analysis (NMA) to compare existing treatments, which include four classes of antidiabetic drugs, and examined the optimum treatments for NAFLD.

AIM

To compare the effectiveness of different treatments for NAFLD.

METHODS

An NMA was conducted using Stata 14.0 (Corporation LLC, College Station, United States) and R (X64 3.6.3 version) in this study. Eligible randomized controlled trials (RCTs) were searched in the PubMed, Cochrane Library, Embase, Medline and Web of Science databases from database inception to April 2021. Two researchers independently screened the available studies in strict accordance with inclusion and exclusion criteria. The Cochrane Risk of Bias tool was used to evaluate the risk of bias of the included studies. The variables with and without dimensional differences were calculated as the standardized mean difference and weighted mean difference, respectively. An inconsistency model and "node-splitting" technique were used to test for inconsistency. Funnel plots were used to evaluate publication bias.

RESULTS

Twenty-two eligible RCTs involving 1377 participants were eventually included in our analysis. Data were pooled using a random-effects model. Our NMA results revealed that glucagon-like peptide-1 receptor agonists (GLP-1RAs) were the most effective treatment, yielding improvements in hepatic fat content (HFC), alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum γ-glutamyl transferase (GGT) and body weight [surface under the cumulative ranking curve (SUCRA) = 99.6%, 92.6%, 82.8%, 92.3% and 99.6%, respectively], while thiazolidinediones (TZDs) were the best intervention for reducing the NAFLD activity score (NAS; SUCRA = 98.9%). In addition, moderate performance was observed for the sodium glucose cotransporter-2 inhibitors groups (SUCRA = 25.1%, 66.2%, 63.5%, 58.2% and 71.9% for HFC, ALT, AST, GGT and body weight, respectively). However, metformin performed poorly according to most indicators (SUCRA = 54.5%, 0.3%, 19.5%, 33.7%, 57.7% and 44.3% for HFC, NAS, ALT, AST, GGT and body weight, respectively).

CONCLUSION

GLP-1RAs may be the optimum choice for most patients with NAFLD. However, TZDs are considered the most effective therapies in NAFLD patients with histological disease activity.

摘要

背景

非酒精性脂肪性肝病(NAFLD)是全球主要的慢性肝脏疾病,目前尚无针对该疾病的确立疗法。我们进行了一项网状Meta分析(NMA)以比较现有治疗方法,其中包括四类抗糖尿病药物,并研究了NAFLD的最佳治疗方法。

目的

比较NAFLD不同治疗方法的有效性。

方法

本研究使用Stata 14.0(美国大学城LLC公司)和R(X64 3.6.3版本)进行NMA。从数据库建立至2021年4月,在PubMed、Cochrane图书馆、Embase、Medline和科学网数据库中检索符合条件的随机对照试验(RCT)。两名研究人员严格按照纳入和排除标准独立筛选现有研究。使用Cochrane偏倚风险工具评估纳入研究的偏倚风险。具有和不具有维度差异的变量分别计算为标准化均数差和加权均数差。使用不一致模型和“节点拆分”技术检验不一致性。漏斗图用于评估发表偏倚。

结果

最终,我们的分析纳入了22项符合条件的RCT,涉及1377名参与者。数据采用随机效应模型进行汇总。我们的NMA结果显示,胰高血糖素样肽-1受体激动剂(GLP-1RAs)是最有效的治疗方法,可改善肝脂肪含量(HFC)、丙氨酸氨基转移酶(ALT)、天冬氨酸氨基转移酶(AST)、血清γ-谷氨酰转移酶(GGT)和体重[累积排序曲线下面积(SUCRA)分别为99.6%、92.6%、82.8%、92.3%和99.6%],而噻唑烷二酮类(TZDs)是降低NAFLD活动评分(NAS;SUCRA = 98.9%)的最佳干预措施。此外,钠-葡萄糖协同转运蛋白-2抑制剂组表现中等(HFC、ALT、AST、GGT和体重的SUCRA分别为25.1%、66.2%、63.5%、58.2%和71.9%)。然而,根据大多数指标,二甲双胍表现不佳(HFC、NAS、ALT、AST、GGT和体重的SUCRA分别为54.5%、0.3%、19.5%、33.7%、57.7%和44.3%)。

结论

GLP-1RAs可能是大多数NAFLD患者的最佳选择。然而,TZDs被认为是组织学疾病活动的NAFLD患者中最有效的治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f81/8472495/38c1bfa6cbc8/WJD-12-1576-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f81/8472495/1cb7be83aa22/WJD-12-1576-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f81/8472495/4c2aea0547ee/WJD-12-1576-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f81/8472495/38c1bfa6cbc8/WJD-12-1576-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f81/8472495/1cb7be83aa22/WJD-12-1576-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f81/8472495/4c2aea0547ee/WJD-12-1576-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f81/8472495/38c1bfa6cbc8/WJD-12-1576-g003.jpg

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