Meta-Analysis Open Access
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Meta-Anal. Apr 18, 2023; 11(4): 125-133
Published online Apr 18, 2023. doi: 10.13105/wjma.v11.i4.125
Role of baricitinib in COVID-19 patients: A systematic review and meta-analysis
Manisha Thakur, Ashok Kumar Datusalia, Department of Regulatory Toxicology, National Institute of Pharmaceutical Education and Research, Raebareli, Raebareli 226002, India
Akhil Babu, Gopal Lal Khatik, Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research, Raebareli, Raebareli 226002, India
Ramchander Khatri, Department of Pharmacognosy, Delhi Pharmaceutical Sciences and Research University, New Delhi 110017, India
Anoop Kumar, Department of Pharmacology and Clinical Research, Delhi Pharmaceutical Sciences and Research University, New Delhi 110017, Delhi, India
ORCID number: Anoop Kumar (0000-0002-7806-9986).
Author contributions: Thakur M and Babu A contributed to searching and selection of studies, extraction of data; Khatik GL, Datusalia AK, and Khatri R contributed to cross verification of data; Khatik GL contributed to first draft of the manuscript; Datusalia AK and Khatri R contributed to revision; Kumar A contributed to design, analysis and final rthe evision of manuscript; All authors have read and approved the final manuscript.
Conflict-of-interest statement: All the authors declare that they have no conflict of interest.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Anoop Kumar, PhD, Assistant Professor, Department of Pharmacology and Clinical Research, Delhi Pharmaceutical Sciences and Research University, New Delhi 110017, Delhi, India. abitmesra@gmail.com
Received: October 31, 2022
Peer-review started: October 31, 2022
First decision: January 17, 2023
Revised: January 27, 2023
Accepted: March 29, 2023
Article in press: March 29, 2023
Published online: April 18, 2023
Processing time: 179 Days and 7.3 Hours

Abstract
BACKGROUND

Recent studies have indicated the use of baricitinib in coronavirus disease 2019 (COVID-19) patients. However, the use of baricitinib in COVID-19 patients is unclear so far.

AIM

To determine the precise role of baricitinib in the mortality of COVID-19 patients.

METHODS

The relevant studies were searched in PubMed, Google scholar, and Clinical trials registries till July 13, 2021 and sorted out based on inclusion and exclusion criteria. The quality of studies was assessed using Newcastle-Ottawa Scale. A random-effect model was used, and the pooled estimate was calculated as the odds ratio with a 95% confidence interval using Rev Man 5.

RESULTS

A total of 11 studies (4 observational and 7 clinical trials) were found relevant for analysis. The overall estimate measure in terms of odds ratio for observational studies was 0.42 [0.11, 1.67], whereas for clinical trials it was 0.37 [0.09, 1.46], indicating a non-significant reduction in COVID-19 patient deaths in the baricitinib group versus the non-baricitinib group.

CONCLUSION

More studies are required to confirm the role of baricitinib in the deaths of COVID-19 patients.

Key Words: Janus kinase inhibitors; Baricitinib; COVID-19; Mortality; Systematic Review; Meta-analysis

Core Tip: Emerging reports have indicated the use of baricitinib in hospitalized coronavirus disease 2019 (COVID-19) patients. However, the use of baricitinib in COVID-19 patients is unclear so far. Current study aimed to find out the exact association of baricitinib in the mortality of COVID-19 patients.



INTRODUCTION

According to the World Health Organization (WHO), multiple pneumonia episodes of unknown cause were reported in the central Metropolitan area of Wuhan in December 2019 in China. The causal infection was later identified as a novel coronavirus, tentatively termed coronavirus disease 2019 (COVID-19). This virus has been causing havoc on public health across the world since its outbreak in December 2019. More than 2000 incidents of COVID-19 infection were reported as of January 26, 2020, the majority of which were individuals living in or traveling Wuhan. The WHO claimed the COVID-19 pandemic was a Public Health Emergency of International Concern on January 30, 2020[1]. The cases of infection were highly associated with the seafood market in Wuhan[2]. Chinese officials announced 2835 confirmed cases in 2020, with 81 deaths. The causal agent has been identified as a novel coronavirus, COVID-19, a pathogen linked to severe acute respiratory syndrome (SARS), was quickly identified as the cause (SARS-CoV) by Chinese officials[3,4]. Coronaviruses (CoV) belongs to the family “coronaviridae”. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is thought to be spread directly from bats to humans or by a single or several host species[3,5]. The treatment is based on the symptoms of the patients. Various classes of drugs are repurposed and are being used in the management of this infection.

Janus Kinase Inhibitors (JAKi) are also one of the repurposed drugs which are being used in the management of hospitalized COVID-19 patients due to their anti-inflammatory (inhibition of IL-6) and anti-viral effects (inhibit the entry of virus)[6]. Baricitinib is one of the JAKi approved for the treatment of rheumatoid arthritis. It has been observed that most SARS-CoV-2 infected patients were died due to cytokine storms, specifically the excess release of IL-6. Thus, baricitinib might be useful in the reduction of deaths of COVID-19 patients[7,8]. Meta-analysis is one of the quantitative analyses that help in clinical decision-making. The results of the individual studies are pooled and integrated using suitable statistical procedures[9-11]. In the current study, we performed a systematic review of clinical studies to determine the role of baricitinib in the deaths of COVID-19 hospitalised patients.

MATERIALS AND METHODS

The study was conducted in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines (Figure 1). The study is registered with the International prospective register of systematic reviews (PROSPERO, Registration number: CRD42021281366).

Figure 1
Figure 1 Selection of studies as per the PRISMA guidelines.
Search strategy

A search was conducted in PubMed, Google scholar, and Clinical trial registry for observational, randomized, and non-randomized controlled studies, cohort studies, and comparative cross-sectional studies with the following search strategies: “baricitinib”, OR “immunosuppressants”, OR “anti-rheumatoid”, OR “Janus kinase inhibitor” OR “Disease-modifying antirheumatic drug” AND “COVID-19” OR “Coronavirus” OR “Acute respiratory distress syndrome” OR “SARS-CoV-2”. The references of included studies were screened to boost the search.

Study selection

Two reviewers (MT and AB) separately screened all the titles and abstracts as per the inclusion and exclusion criteria. The studies were included if participants were on baricitinib therapy, with all age groups, and all sexes. The case reports, case series, narrative review, systematic review, meta-analysis, studies of poor quality as per standard scale were excluded. The reviewers (MT and AB) separately screened the full-text studies for final inclusion. In the case of conflicts over the inclusion, the third reviewer (AK) was consulted.

Quality assessment

The quality assessment of eligible observational studies was done using Newcastle-Ottawa Scale whereas quality assessment of clinical trials was done using NIH quality assessment scale for quality assessment of controlled intervention studies. The assessment was done by two reviewers (MT and AB) separately. The disagreement among authors was resolved after a discussion with four reviewers (GLK, AKD, RK, and AK). The studies were categorized into three categories, i.e., good, fair, and poor quality.

Data extraction

The data was extracted from studies by two reviewers (MT and AB) in an excel sheet. The information includes the name of the first author with publication year, the country where the study has been conducted, gender, study design, the total number of subjects, number of subjects, and deaths in baricitinib, non-baricitinib group.

Sensitivity analysis

The sensitivity analysis was done to check the effect of high or low sample size on the outcome to address the degree of heterogeneity.

Statistical analysis

RevMan 5 was used for all of the analyses. Using a random-effect model, the overall estimate was calculated as an odds ratio with 95% confidence intervals. Cochrane Q and I square statistics were used to calculate study heterogeneity.

RESULTS
Search results and study characteristics

We found 865 articles after the initial search. After primarily screening of titles, 21 relevant articles were found. Further, based on the screening of abstracts, 16 were retrieved, out of which 05 articles were excluded due to insufficient information. Finally, 11 articles[11-22] were included for qualitative and quantitative analysis. Figure 1 depicts the selection of articles. The full-text or secondary screening with bibliography searches yielded no additional articles for inclusion. Out of the 11 studies, 4 were observational studies whereas the remaining 7 studies were clinical trials. The four studies were conducted in Italy, two in Spain, one in Italy and Spain, and one each at, Omaha, Bangladesh, Germany, Wuhan. The characteristics of included observational studies were compiled in Table 1 whereas the characteristics of included clinical trials were compiled in Table 2.

Table 1 Characteristics of included observational studies.
Ref.CountryStudy designSample sizeSex
Baricitinib group
Non-baricitinib group
Male
Female
Number of patients
Death
Number of patients
Death
Hasan et al[14], 2021BangladeshCohort study2381597912241167
Stebbing et al[15], 2021Italy, SpainObservational 79043835237114247
Rodriguez-Garcia et al[16], 2020SpainCohort study1127834625502
Rosas et al[19], 2020SpainCase control study29209122176
Table 2 Characteristics of included clinical trials.
Ref.CountryStudy designSample sizeSex
Baricitinib group
Non-baricitinib group
Male
Female
Number of patients
Death
Number of patients
Death
Bronte et al[13], 2020ItalyClinical trial7638382015625
Kalil et al[12], 2020OmahaClinical trial10336523815153251852
Cantini et al[17], 2020GermanyClinical trial24204120120
Cantini et al[18], 2020ItalyClinical trial191119721130787
Cao et al[20],2020WuhanClinical trial412417200213
D'Alessio et al[21],2021ItalyClinical trial755223323430
Giudice et al[22], 2020ItalyClinical trial1713471101
Quality assessment

All observational studies on the Newcastle-Ottawa Scale were found to be of good to fair quality based on their scores in the selection, comparability, and outcome subscales. Three of the four studies were of high quality, while the fourth was of fair quality (Table 3). According to the NIH quality assessment scale, 5 studies were of good quality, while the remaining two were of fair quality (Table 4).

Table 3 Quality assessment of observational studies using new castle Ottawa scale.
Ref.
Selection
Comparability
Exposure
Total score
Quality of the study
Hasan et al[14], 2021*********9Good
Stebbing et al[15], 2021*******7Good
Rodriguez-Garcia et al[16], 2020********8Good
Rosas et al[19], 2020*******7Fair
Table 4 Quality assessment of clinical trials using NIH scale.
No.
Ref.
Type of study
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
Q10
Q11
Q12
Q13
Q14
Quality of the study
1Bronte et al[13], 2020Clinical trialYes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Good
2Kalil et al[12], 2020Clinical trialYes Yes Yes Yes Yes Yes Yes Yes NRYes Yes Yes Yes Yes Good
3Cantini et al[17], 2020Clinical trialYes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Good
4Cantini et al[18], 2020Clinical trialNoNo Yes Yes Yes Yes Yes Yes Yes Yes Yes NOYes Yes Fair
5Cao et al[20], 2020Clinical trialYes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Good
6D'Alessio et al[21], 2021Clinical trialNo NoYes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Fair
7Giudice et al[22], 2020Clinical trialYes Yes Yes Yes Yes Yes Yes Yes NOYes Yes NOYes NRGood
Analysis of observational studies

A total of 558 patients were found in selected 4 observational studies. 233 of the 558 coronavirus disease 2019 (COVID-19) cases were taking baricitinib, while the remaining 325 were not. The overall estimate was 0.42 [0.11, 1.67], indicating that the baricitinib group had a non-significant reduction in COVID-19 patient deaths compared to the non-baricitinib group (Figure 2).

Figure 2
Figure 2 Forest Plot showing overall estimate measure of observational studies as odds ratio using random-effect model.
Analysis of clinical trials

In total, 1457 patients were found in 7 clinical trials. 719 of the 1457 COVID-19 cases were taking baricitinib, while the remaining 738 were not. The overall estimate was 0.37 [0.09, 1.46], indicating that the baricitinib group had a non-significant reduction in COVID-19 patient deaths compared to the non-baricitinib group (Figure 3).

Figure 3
Figure 3 Forest Plot showing overall estimate measure of clinical trials as odds ratio using random-effect model.
Heterogeneity

The I2 (90%) and chi2 statics have shown high heterogeneity among studies.

Sensitivity analysis

We have analyzed the forest plots of both observational and clinical trials and found that there is a study with high and low sample sizes, particularly in clinical trials. Therefore, analysis was also done again to check the effect of these studies on the outcome. The studies with a high and low sample sizes i.e., Kalil et al[12] and Giudice et al[22], were excluded, and analysis was done again. The overall estimate was 0.23 [0.02, 2.37], indicating a non-significant reduction in COVID-19 patient deaths in the baricitinib group versus the non-baricitinib group (Figure 4). Overall, results were not affected by the studies with high and low sample sizes.

Figure 4
Figure 4 Forest Plot showing overall estimate measure of clinical trials as odds ratio after exclusion of studies with high (Kalil et al[12], 2020) and low sample size (Giudice et al[22], 2020) using random-effect model.
DISCUSSION

The current analysis was done to find out the role of baricitinib in the reduction of deaths of COVID-19 hospitalized patients. To the best of our knowledge, very few meta-analyses have been done so far on the use of baricitinib in COVID-19 treatment. Recently, Chen et al[23], have performed a meta-analysis of 11 studies and reported the safety and efficacy of JAK-inhibitors including baricitinib in COVID-19 patients. Another JAK inhibitor i.e., ruxolitinib is also used in hospitalized patients. The meta-analysis results of Wijaya et al[24], have demonstrated a significant clinical improvement and decrease in the risk of mortality of COVID-19 patients. The potential of baricitinib in the reduction of deaths of hospitalized COVID 19 patients is also indicated by a meta-analysis conducted by Walz et al[25]. Recently, Putman et al[26], have also performed a meta-analysis to find out the efficacy of anti-rheumatoid therapy, including baricitinib and steroids for the treatment of COVID-19. However, number of available studies regarding the use of baricitinib in COVID-19 patients at that time was very less. The already published meta-analysis have also analyzed different design of studies together which make less valid conclusion. In the current meta-analysis, we have analyzed observational and clinical trials separately. However, the results of both observational and clinical trials have shown the non-significant deaths of COVID-19 hospitalized patients in the baricitinib group as compared to non-baricitinib group. Further, the sensitivity analysis results have also shown no effect of outliers on the outcome.

CONCLUSION

In conclusion, more research is needed to draw a valid conclusion about the use of baricitinib in the reduction of COVID-19 patient deaths.

ARTICLE HIGHLIGHTS
Research background

More research is needed to draw a valid conclusion about the use of baricitinib in the reduction of coronavirus disease 2019 (COVID-19) patient deaths.

Research motivation

More research is needed to confirm the role of baricitinib in COVID-19 patient deaths.

Research objectives

A total of 11 studies (4 observational and 7 clinical trials) were found relevant for analysis. The overall estimate measure in terms of odds ratio for observational studies was 0.42 [0.11, 1.67], whereas for clinical trials it was 0.37 [0.09, 1.46], indicating a non-significant reduction in COVID-19 patient deaths in the baricitinib group versus the non-baricitinib group. The degree of heterogeneity among studies was also discovered to be high.

Research methods

The study was conducted as per the PRISMA guideline using RevMan 5 software.

Research results

To investigate the role of baricitininb in the reduction of COVID-19 patient deaths.

Research conclusions

Can baricitinib reduce the deaths of COVID-19 patients?

Research perspectives

Emerging reports have indicated the use of baricitinib in hospitalized COVID-19 patients. However, the use of baricitinib in COVID-19 patients is unclear so far.

ACKNOWLEDGEMENTS

The authors are thankful to Vice-Chancellor, Prof. R.K. Goyal, Delhi Pharmaceutical Sciences & Research University, New Delhi, and Director, National Institute of Pharmaceutical Education and Research, Raebareli, India for their constant encouragement, motivation, and provision of the necessary resources to carry out this work.

Footnotes

Provenance and peer review: Unsolicited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Pharmacology and pharmacy

Country/Territory of origin: India

Peer-review report’s scientific quality classification

Grade A (Excellent): 0

Grade B (Very good): B

Grade C (Good): 0

Grade D (Fair): D

Grade E (Poor): 0

P-Reviewer: Badri M, Iran; Mohammadi M, Iran S-Editor: Liu JH L-Editor: A P-Editor: Yu HG

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