Efficacy of remdesivir in patients with COVID-19: a protocol for systematic review and meta-analysis of randomised controlled trials

  1. Desye Gebrie
  2. Desalegn Getnet
  3. Tsegahun Manyazewal

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Abstract

Despite 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 analysis

We 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 dissemination

There 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 number

CRD42020177953.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.09.20059196: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationWe will include randomized controlled trials that assessed the effectiveness of remdesivir versus placebo for patients with COIVID-19 without restriction on year of publication, but published in English language.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data sources and searches: We will search MEDLINE/PubMed (http://www.ncbi.nlm.nih.gov/pubmed/), Embase (http://www.embase.com/), The Cochrane Library (http://www.cochranelibrary.com/), ClinicaTtrials.gov (https://www.clinicaltrials.gov/), and google scholar (https://scholar.google.com/) databases for completed studies that reported the efficacy of remdesivir versus placebo for patients with COVID-19.
    Embase
    suggested: (EMBASE, RRID:SCR_001650)
    Cochrane Library
    suggested: (Cochrane Library, RRID:SCR_013000)
    google scholar
    suggested: (Google Scholar, RRID:SCR_008878)
    The Medical Subject Headings (MeSH) and keywords we will used in different combinations using balloon operators will be 2019 novel coronavirus, 2019-nCov, coronavirus disease 2019, COVID-19, SARS-cov-2, remdesivir
    MeSH
    suggested: (MeSH, RRID:SCR_004750)
    Statistical analysis: Meta-analysis will be carried out using the computer software packages RevMan 5.3 [26]
    RevMan
    suggested: (RevMan, RRID:SCR_003581)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1136/bmjopen-2020-039159
  3. Version published to 10.1101/2020.04.09.20059196v1 on medRxiv