The Efficacy and Safety of Janus Kinase Inhibitors for Patients With COVID-19: A Living Systematic Review and Meta-Analysis

Abstract

BackgroundCytokine storm observed in patients with severe Coronavirus Disease 2019 (COVID-19) contributes to poor clinical outcomes and increased mortality. Janus kinases (JAKs) are important mediators in the cytokine storm. Therefore, we conduct a living systematic review and meta-analysis of the literature investigating efficacy and safety of JAK inhibitors for patients with COVID-19.MethodsDatabases were searched up to December 1, 2021 for interventional and observational studies comparing JAK inhibitor treatment with concurrent control in patients with COVID-19. Efficacy and safety outcomes were evaluated by pooled risk ratio (RR).ResultsOf 3,170 records retrieved, 15 studies were eligible and 13 were evaluated in the meta-analysis (n = 3,977). Based on data from three randomized controlled trials (RCTs), baricitinib treatment significantly decreased mortality by day 28 in hospitalized patients with COVID-19 (RR = 0.64, 95% CI 0.51–0.80) without increasing the incidence of adverse outcomes. In subgroup analysis, patients who required supplemental oxygen (RR = 0.62, 95% CI 0.41–0.95) or high-flow oxygen/non-invasive ventilation (RR = 0.59, 95% CI 0.42–0.85) at baseline benefited most. Pooled analysis of all eligible studies for JAK inhibitors (baricitinib, ruxolitinib, tofacitinib, and nezulcitinib) demonstrated a significant decrease in mortality (RR = 0.62, 95% CI 0.49–0.78) with no increase in the risk of adverse events.ConclusionBaricitinib probably decreases mortality in hospitalized adult patients with COVID-19, especially for patients who required supplemental oxygen or high-flow oxygen/non-invasive ventilation at baseline. The efficacy and safety of other JAK inhibitors, such as ruxolitinib, tofacitinib, and nezulcitinib, await more evidence.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021261414, identifier: CRD42021261414.

Characteristics of Living Systematic Review for COVID-19

“… 16–21 , 23–44 , 46–51 , 53–57 , 59–69 , 73–79 The impact factor published in SCI journals ranged from 1.04 to 39.89, with an average of 11.72 and a standard deviation of 11.30. The impact factor of 64.1% studies was >5, 16–20 , 23 , 26 , 27 , 30 , 32 , 33 , 36 , 37 , 39–44 , 46 , 47 , 49–51 , 54–57 , 60–64 , 67–69 , 73–76 , 79 the impact factor of 17.2% studies was >15. 16 , 17 , 23 , 42 , 43 , 51 , 62–64 , 74 , 76 LSRs were published in journals with high impact factor, which indicated COVID-19 related studies have attracted much attention from readers ( Table 1 ).…”

“…The topic most studied (40.6%) was the treatment of COVID-19. 20 , 22 , 25 , 32 , 37 , 39 , 43 , 46 , 47 , 49 , 51 , 55 , 56 , 58 , 62–64 , 67–74 , 79 The population most studied (76.6%) was general COVID-19 patients, 18–23 , 26 , 27 , 29 , 31–34 , 36 , 37 , 39 , 42–44 , 46 , 47 , 49–65 , 67–76 , 79 but there were fewer (6.3%) studies concerning pregnant women 16 , 17 , 30 , 78 and children 28 , 30 , 77 , 78 with COVID-19, even no study concerning the elderly with COVID-19. ( Table 1 , Supplementary Material Table 1 )…”

“…In the production phase of LSR, most of the LSRs registered 16–22 , 25 , 26 , 28–33 , 35 , 37 , 39–42 , 45–62 , 65–67 , 69–73 , 76–79 (81.2%) and wrote the protocol 16–35 , 37 , 39–43 , 45–67 , 69–73 , 76–79 (92.2%) before the study started. Less than one third of the LSRs searched the Chinese database 16–18 , 23 , 25 , 34 , 35 , 43 , 46 , 48 , 57 , 62–64 , 70 , 79 (25%), and less than half of the LSRs searched the preprint database 16 , 20 , 21 , 23–26 , 28 , 37 , 39 , 40 , 43 , 45 , 46 , 48 , 51 , 53 , 57 , 62–64 , 67 , 68 , 73 , 76 , 77 , 79 (42.2%), and two-thirds of the LSRs searched 12 COVID-19 databases 16 , 17 , 20–23 , 27 , 30 , 32 , 33 , 37–42 , 44–46 , 48 , 49 ...…”

“…Less than one third of the LSRs searched the Chinese database 16–18 , 23 , 25 , 34 , 35 , 43 , 46 , 48 , 57 , 62–64 , 70 , 79 (25%), and less than half of the LSRs searched the preprint database 16 , 20 , 21 , 23–26 , 28 , 37 , 39 , 40 , 43 , 45 , 46 , 48 , 51 , 53 , 57 , 62–64 , 67 , 68 , 73 , 76 , 77 , 79 (42.2%), and two-thirds of the LSRs searched 12 COVID-19 databases 16 , 17 , 20–23 , 27 , 30 , 32 , 33 , 37–42 , 44–46 , 48 , 49 , 51 , 54–56 , 58–64 , 67 , 69–77 , 79 (67.2%)( Supplementary Material Table 2 ). More than half (51.6%) of LSRs used the same frequency to search different databases regularly, 16–18 , 20 , 24–26 , 30 , 32 , 35–37 , 39 , 40 , 43–46 , ...…”

Application of Machine Learning in Hospitalized Patients with Severe COVID-19 Treated with Tocilizumab

“…Currently available treatment focuses on modulating immune responses, and obtaining antiviral, antithrombotic or anticoagulant effects [ 3 ]. The drugs with the most accumulating evidence for CRS blockade are IL-1 (anakinra) or IL-6 (tocilizumab or sarilumab) inhibitors, janus kinase inhibitors [JAKi] (e.g., baricitinib), as well as corticosteroids [ 4 , 33 , 34 ]. Increasing evidence supports the incremental efficacy of corticosteroids alone or in combination with tocilizumab/JAKi in moderate to severe and critical COVID-19 [ 4 , 35 , 36 ].…”