Manoharan Sivananthan, Ying Ying Lee
Molecular Pathology Unit, Cancer Research Centre, Institute for Medical Research, National Institutes of Health, Ministry of Health Malaysia, Shah Alam, Selangor 40170, Malaysia.
Department of Biomedical Sciences, Asia Metropolitan University, Johor Bahru, Johor 81750, Malaysia.
Biol Methods Protoc. 2024 Jan 23;9(1):bpae002. doi: 10.1093/biomethods/bpae002. eCollection 2024.
Due to high heterogeneity and risk of bias (RoB) found in previously published meta-analysis (MA), a concrete conclusion on the efficacy of baricitinib in reducing mortality in coronavirus disease 2019 (COVID-19) patients was unable to form. Hence, this systematic review and MA were conducted to analyse whether RoB, heterogeneity, and optimal sample size from placebo-controlled randomized controlled trials (RCTs) are still the problems to derive a concrete conclusion. Search engines PubMed/MEDLINE, ScienceDirect, and other sources like preprints and reference lists were searched with appropriate keywords. The RoB and MA were conducted using RevMan 5.4. The grading of the articles was conducted using the GRADEPro Guideline Development Tool. Ten RCTs were included in the current systematic review. Only five low RoB articles are Phase III placebo-controlled RCTs with a high certainty level based on the GRADE grading system. For the MA, based on five low RoB articles, baricitinib statistically significantly reduced mortality where the risk ratio (RR) = 0.68 [95% confidence interval (95% CI) 0.56-0.82; <0.0001; = 0%; =0.85]. The absolute mortality effect (95% CI) based on the grading system was 35 fewer mortalities per 1000 COVID-19 patients, whereas in the baricitinib and control groups, the mortality was 7.4% and 10.9%, respectively. With the presence of an optimal sample size of 3944 from five low RoB-placebo-controlled RCTs, which represent a minimum of 300 million population of people and with the presence of 0% heterogeneity from MA, the effectiveness of baricitinib in reducing the mortality in COVID-19 patients is concretely proven.
由于在先前发表的荟萃分析(MA)中发现高度异质性和偏倚风险(RoB),因此无法就巴瑞替尼降低2019冠状病毒病(COVID-19)患者死亡率的疗效得出具体结论。因此,进行了这项系统评价和MA,以分析来自安慰剂对照随机对照试验(RCT)的RoB、异质性和最佳样本量是否仍然是得出具体结论的问题。使用适当的关键词搜索了搜索引擎PubMed/MEDLINE、ScienceDirect以及预印本和参考文献列表等其他来源。使用RevMan 5.4进行RoB和MA。使用GRADEPro指南制定工具对文章进行分级。本系统评价纳入了10项RCT。根据GRADE分级系统,只有5篇低RoB文章是具有高确定性水平的III期安慰剂对照RCT。对于MA,基于5篇低RoB文章,巴瑞替尼在统计学上显著降低了死亡率,风险比(RR)=0.68[95%置信区间(95%CI)0.56 - 0.82;<0.0001;I² = 0%;Tau² = 0.85]。基于分级系统的绝对死亡率效应(95%CI)为每1000例COVID-19患者中死亡人数减少35例,而在巴瑞替尼组和对照组中,死亡率分别为7.%.和10.9%。来自5项低RoB安慰剂对照RCT的最佳样本量为3944,代表至少3亿人群,且MA的异质性为0%,这具体证明了巴瑞替尼在降低COVID-19患者死亡率方面的有效性。