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Efficacy of BCG Vaccination against COVID-19: Systematic Review and Meta-Analysis of Randomized Controlled Trials

ABSTRACT: Beneficial off-target effects of the Bacillus Calmette-Guérin (BCG) vaccination might offer general protection from respiratory tract infections. We conducted a systematic review and meta-analysis of published randomized controlled trials (RCTs) to ascertain BCG vaccination effectiveness against COVID-19. We looked up English RCTs from 1 January 2019 to 15 November 2022 in Embase, the Cochrane Library, and the Web of Science in this systematic review and meta-analysis. Nine RCTs, including 7963 participants, were included. The infection rate of COVID-19 was not decreased in people who were vaccinated with BCG (OR, 0.96; 95% CI, 0.82–1.13; I2 = 4%), and the BCG vaccination group did not have decreased COVID-19 related-hospitalization (OR, 0.66; 95% CI, 0.37–1.18; I2 = 42%), admission to the ICU (OR, 0.25; 95% CI, 0.05–1.18; I2 = 0%), and mortality (OR, 0.64; 95% CI, 0.17–2.44; I2 = 0%) compared with the control group. There is not sufficient evidence to support the use of BCG vaccination in the prevention of COVID-19 infection and severe COVID-19 and avoid overstating the role of BCG vaccination leading to its misuse.

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PROVIDER: S-EPMC9917948 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Project description:Background: We provided a comprehensive evaluation of efficacy of available treatments for coronavirus disease 2019 (COVID-19). Methods: We searched for candidate COVID-19 studies in WHO COVID-19 Global Research Database up to August 19, 2021. Randomized controlled trials for suspected or confirmed COVID-19 patients published on peer-reviewed journals were included, regardless of demographic characteristics. Outcome measures included mortality, mechanical ventilation, hospital discharge and viral clearance. Bayesian network meta-analysis with fixed effects was conducted to estimate the effect sizes using posterior means and 95% equal-tailed credible intervals (CrIs). Odds ratio (OR) was used as the summary measure for treatment effect. Bayesian hierarchical models were used to estimate effect sizes of treatments grouped by the treatment classifications. Results: We identified 222 eligible studies with a total of 102,950 patients. Compared with the standard of care, imatinib, intravenous immunoglobulin and tocilizumab led to lower risk of death; baricitinib plus remdesivir, colchicine, dexamethasone, recombinant human granulocyte colony stimulating factor and tocilizumab indicated lower occurrence of mechanical ventilation; tofacitinib, sarilumab, remdesivir, tocilizumab and baricitinib plus remdesivir increased the hospital discharge rate; convalescent plasma, ivermectin, ivermectin plus doxycycline, hydroxychloroquine, nitazoxanide and proxalutamide resulted in better viral clearance. From the treatment class level, we found that the use of antineoplastic agents was associated with fewer mortality cases, immunostimulants could reduce the risk of mechanical ventilation and immunosuppressants led to higher discharge rates. Conclusions: This network meta-analysis identified superiority of several COVID-19 treatments over the standard of care in terms of mortality, mechanical ventilation, hospital discharge and viral clearance. Tocilizumab showed its superiority compared with SOC on preventing severe outcomes such as death and mechanical ventilation as well as increasing the discharge rate, which might be an appropriate treatment for patients with severe or mild/moderate illness. We also found the clinical efficacy of antineoplastic agents, immunostimulants and immunosuppressants with respect to the endpoints of mortality, mechanical ventilation and discharge, which provides valuable information for the discovery of potential COVID-19 treatments.

Project description:Several vaccines have been approved for the prevention of COVID-19. However, no head-to-head trials comparing their clinical efficacy have been performed. This network meta-analysis aims to identify those, among the competing existing vaccines, conferring the maximum protection against COVID-19. A literature search was done in Medline (via PubMed), Embase and Cochrane Library databases for phase 3 randomized controlled trials evaluating the efficacy of different COVID-19 vaccines. Search results were screened and eligible studies were included to perform a network meta-analysis in software 'R' version 4.1.2 using a random effect model. Cochrane's 'Risk of Bias tool (RoB2)' was used for quality assessment. Raw data from the included studies was used for network meta-analysis. Assessment of inconsistency was not possible as no study compared two or more vaccines directly. A forest plot for indirect comparison of various COVID-19 vaccines was obtained. Rankogram and 'P' scores were obtained to rank the vaccines based on the indirect evidence of their comparative efficacy. A total of 17 randomized controlled trials evaluating the efficacy of 16 COVID-19 vaccines, were included in the network meta-analysis. A total of 361,386 participants was included in this network meta-analysis. Overall risk of bias among included studies was of 'some concern'. All the COVID-19 vaccines had a statistically significant reduction of risk for contracting symptomatic SARS-CoV-2 in comparison to the placebo, however, the maximum protection (RR 0.05) was with BNT126b2. The indirect comparison also revealed BNT126b2 vaccine confers the highest protection against symptomatic SARS-CoV-2 infection in comparison to all others included, with a 'P' score of 0.9771 followed by mRNA-1273, rAD26 & rAD5 and NVX-CoV2373. The evidence generated from this network meta-analysis indicates the good efficacy of all the included vaccines in preventing symptomatic COVID-19 as compared to placebo. The BNT126b2 vaccine was found to provide the highest protection against symptomatic SARS-CoV-2 among all included followed by mRNA-1273, rAD26 & rAD5, NVX-CoV2373 and others.

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Efficacy of BCG Vaccination against COVID-19: Systematic Review and Meta-Analysis of Randomized Controlled Trials

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