A Systematic Review and Network Meta-Analysis for COVID-19 Treatments

  1. Chenyang Zhang
  2. Huaqing Jin
  3. Yifeng Wen
  4. Guosheng Yin

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

Numerous interventions for coronavirus disease 2019 (COVID-19) have been investigated by randomized controlled trials (RCTs). This systematic review and Bayesian network meta-analysis (NMA) aim to provide a comprehensive evaluation of efficacy of available treatments for COVID-19.

Methods

We searched for candidate COVID-19 studies in WHO COVID-19 Global Research Database, PubMed, PubMed Central, LitCovid, Proquest Central and Ovid up to December 19, 2020. RCTs for suspected or confirmed COVID-19 patients were included, regardless of publication status or demographic characteristics. Bayesian NMA with fixed effects was conducted to estimate the effect sizes using posterior means and 95% equal-tailed credible intervals (CrIs), while that with random effects was carried out as well for sensitivity analysis. Bayesian hierarchical models were used to estimate effect sizes of treatments grouped by their drug classifications.

Results

We identified 96 eligible RCTs with a total of 51187 patients. Compared with the standard of care (SOC), this NMA showed that dexamethasone led to lower risk of mortality with an odds ratio (OR) of 0.85 (95% CrI [0.76, 0.95]; moderate certainty) and lower risk of mechanical ventilation (MV) with an OR of 0.68 (95% CrI [0.56, 0.83]; low certainty). For hospital discharge, remdesivir (OR 1.37, 95% CrI [1.15, 1.64]; moderate certainty), dexamethasone (OR 1.20, 95% CrI [1.08, 1.34]; low certainty), interferon beta (OR 2.15, 95% CrI [1.26, 3.74]; moderate certainty), tocilizumab (OR 1.40, 95% CrI [1.05, 1.89]; moderate certainty) and baricitinib plus remdesivir (OR 1.75, 95% CrI [1.28, 2.39]; moderate certainty) could all increase the discharge rate respectively. Recombinant human granulocyte colony-stimulating factor indicated lower risk of MV (OR 0.20, 95% CrI [0.10, 0.40]; moderate certainty); and patients receiving convalescent plasma resulted in better viral clearance (OR 2.28, 95% CrI [1.57, 3.34]; low certainty). About two-thirds of the studies included in this NMA were rated as high risk of bias, and the certainty of evidence was either low or very low for most of the comparisons.

Conclusion

The Bayesian NMA identified superiority of several COVID-19 treatments over SOC in terms of mortality, requirement of MV, hospital discharge and viral clearance. These results provide a comprehensive comparison of current COVID-19 treatments and shed new light on further research and discovery of potential COVID-19 treatments.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.12.21.20248621: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    , PubMed, PubMed Central, LitCovid
    PubMed
    suggested: (PubMed, RRID:SCR_004846)

    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: We detected the following sentences addressing limitations in the study:
    Strength and limitations: Not only was this NMA timely conducted, but it also included a wide range of RCTs, which contained not only common drugs but also interferons, blood products, mineral and vitamin supplementations without restrictions on publication status. Risk of bias for individual studies and rating of certainty for NMA estimates were carefully conducted and detailed information and reasons for corresponding assessments are given in Supplementary Materials. Treatment effects for multiple treatments were evaluated in a network at both the individual drug and class levels. This study has several limitations. The primary one is the low or very low certainty of evidence for most NMA estimates. For each outcome of interest, about two-thirds of trials were graded as high risk and the major reason was lack of blinding in the trials, leading to potential bias in the NMA. At the early stage of COVID-19 pandemic, with limited clinical resources and urgent need to obtain trial results, many RCTs were conducted with simplified procedures, e.g., no placebo prepared, including the large RECOVERY and SOLIDARITY trials. As time goes on, such situation has changed and recently many double-blind RCTs have been conducted and published. Moreover, networks of treatments were sparse because most of the included studies evaluated interventions versus SOC and there were few direct comparisons between interventions. As we considered COVID-19 RCTs regardless of baseline patient characteris...

    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 10.1101/2020.12.21.20248621v1 on medRxiv