AUTHOR=Niu Jianyi , Lin Zhiwei , He Zhenfeng , Yang Xiaojing , Qin Lijie , Feng Shengchuan , Guan Lili , Zhou Luqian , Chen Rongchang 

TITLE=Janus kinases inhibitors for coronavirus disease-2019: A pairwise and Bayesian network meta-analysis

JOURNAL=Frontiers in Medicine

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2022.973688

DOI=10.3389/fmed.2022.973688

ISSN=2296-858X

ABSTRACT=Background JAK (Janus kinases) inhibitors have been proposed as a promising treatment option for the coronavirus disease-2019 (COVID-19). However, the benefits of JAK inhibitors and the optimum JAK inhibitors for COVID-19 have not been adequately defined.
Methods Databases were searched from their inception to 17 June 2022. Eligible studies included randomized controlled trials and observational studies. Extracted data were analyzed by pairwise and network meta-analysis. The primary outcome was the coefficient of mortality.
Results Twenty-eight studies of 8206 patients were included and assessed qualitatively (modified Jadad and Newcastle–Ottawa Scale scores). A pairwise meta-analysis revealed that JAK inhibitors effectively improved the mortality (OR = 0.54; 95% CI: 0.46 – 0.63; P < 0.00001; I2 = 32%) and did not increase the risk of adverse events (OR = 1.02; 95% CI: 0.88–1.18; P = 0.79; I2 = 12%). In a network meta-analysis, clinical efficacy benefits were seen among different types of JAK inhibitors (baricitinib, ruxolitinib and tofacitinib), but reduced incidence of adverse events were not observed among them. The assessment of rank probabilities indicated that ruxolitinib presented the greatest likelihood of benefit regarding mortality and adverse events.
Conclusion JAK inhibitors appear to be a promising treatment for COVID-19 with respect to reducing mortality, and they do not increase the risk of adverse events versus standard of care. A network meta-analysis suggests that mortality benefits are associated with specific JAK inhibitors, and among these, ruxolitinib presents the greatest likelihood of having benefits for mortality and adverse events.