Dataset Information

Clinical efficacy and safety of remdesivir in patients with COVID-19: a systematic review and network meta-analysis of randomized controlled trials.

ABSTRACT:

Objectives

We performed a systematic review and network meta-analysis of randomized controlled trials (RCTs) to provide updated information regarding the clinical efficacy of remdesivir in treating coronavirus disease 2019 (COVID-19).

Methods

PubMed, Embase, Cochrane Library, clinical trial registries of ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform were searched for relevant articles published up to 18 November 2020.

Results

Five RCTs, including 13 544 patients, were included in this meta-analysis. Among them, 3839 and 391 patients were assigned to the 10 day and 5 day remdesivir regimens, respectively. Patients receiving 5 day remdesivir therapy presented greater clinical improvement than those in the control group [OR = 1.68 (95% CI 1.18-2.40)], with no significant difference observed between the 10 day and placebo groups [OR = 1.23 (95% CI 0.90-1.68)]. Patients receiving remdesivir revealed a greater likelihood of discharge [10 day remdesivir versus control: OR = 1.32 (95% CI 1.09-1.60); 5 day remdesivir versus control: OR = 1.73 (95% CI 1.28-2.35)] and recovery [10 day remdesivir versus control: OR = 1.29 (95% CI 1.03-1.60); 5 day remdesivir versus control: OR = 1.80 (95% CI 1.31-2.48)] than those in the control group. In contrast, no mortality benefit was observed following remdesivir therapy. Furthermore, no significant association was observed between remdesivir treatment and an increased risk of adverse events.

Conclusions

Remdesivir can help improve the clinical outcome of hospitalized patients with COVID-19 and a 5 day regimen, instead of a 10 day regimen, may be sufficient for treatment. Moreover, remdesivir appears as tolerable as other comparators or placebo.

SUBMITTER: Lai CC

PROVIDER: S-EPMC8083728 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

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.

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:BackgroundDespite global containment measures to fight the coronavirus disease 2019 (COVID-19), the pandemic continued to rise, rapidly spread across the world, and resulting in 2.6 million confirmed cases and 185 061 deaths worldwide as of 23 April 2020. Yet, there are no approved vaccines or drugs to make the disease less deadly, while efforts are underway. Remdesivir, a nucleotide-analogue antiviral drug developed for Ebola, is determined to prevent and stop infections with COVID-19, while results are yet controversial. Here, we aim to conduct a systematic review and meta-analysis of randomised controlled trials (RCTs) to evaluate the efficacy of remdesivir in patients with COVID-19.Method and analysisWe will search MEDLINE-PubMed, Embase, Cochrane Library, ClinicalTrials.gov and Google scholar databases for articles published as of 30 June 2020 and we will complete the study on 30 August 2020. We will follow the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) 2015 guidelines for the design and reporting of the results. We will include RCTs that assessed the efficacy of remdesivir versus placebo or standard of care. The primary endpoint will be time to clinical recovery. The secondary endpoints will be proportion of participants relieved from clinical symptoms defined at the time (in hours) from initiation of the study treatment, all-cause mortality, discharged date, frequency of respiratory progression and treatment-emergent adverse events. RevMan V.5.3 software will be used for statistical analysis. Random effects model will be carried out to calculate mean differences for continuous outcome data and risk ratio for dichotomous outcome data between remdesivir and placebo or standard of care.Ethics and disseminationThere are no ethical considerations associated with this study as we will use publicly available data from previously published studies. We plan to publish results in open-access peer-reviewed journals and present at international and national conferences.Prospero registration numberCRD42020177953.