Comparative efficacy and safety of current drugs against COVID-19: A systematic review and network meta-analysis

  1. Yi Li
  2. Wei He

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Abstract

The rapid spread of coronavirus disease (COVID-19) has greatly disrupted the livelihood of many people around the world. To date, more than 35.16 million COVID-19 cases with 1.037million total deaths have been reported worldwide. Compared with China, where the disease was first reported, cases of COVID-19, the number of confirmed cases for the disease in the rest of the world have been incredibly high. Even though several dugs have been suggested to be used against the disease, the said interventions should be backed by empirical clinical evidence. Therefore, this paper provides a systematic review and a meta-analysis of efficacy and safety of different COVID-19 drugs.

Research in context

Evidence before this study

Currently, Covid-19 is one of the most urgent and significant health challenge, globally. However, so far there is no specific and effective treatment strategy against the disease. Nonetheless, there are numerous debates over the effectiveness and potential adverse effects of different COVID-19 antivirals. In general, there is invaluable need to continually report on new advances and successes against COVID-19, apparently to aid in managing the pandemic.

Added value of this study

This study provides a comprehensive, evidence-based guide on the management of multiple COVID-19 symptoms. In particular, we provide a review of 14 drugs, placebos and standard treatments against COVID 19. Meanwhile, we also performed a meta-analysis based on four clinical outcome indicators, to measure and compare the efficacy and safety of current interventions.

Implications of all the available evidence

Findings of this research will guide clinical decision in COVID-19 patients. It will also provide a basis for predicting clinical outcomes such as efficacy, mortality and safety of interventions against the disease.

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  1. ScreenIT

    SciScore for 10.1101/2020.11.16.20232884: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindinggeneration of random sequence, (2). blindlessness of the trails, (3.)concealment and (4).
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Search strategy and selection criteria: The systematic review and network meta-analysis was performed on numerous reports in the Cochrane Central Register of Controlled Trials, PubMed, Embase and Web of Science.
    Cochrane Central Register of Controlled Trials
    suggested: (Cochrane Central Register of Controlled Trials, RRID:SCR_006576)
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Embase
    suggested: (EMBASE, RRID:SCR_001650)
    The search terms were “severe acute respiratory syndrome coronavirus 2*” (MeSH) OR “2019nCoV*” OR “SARSCoV2*” OR “2019 novel coronavirus*” OR “COVID19 virus disease” OR “COVID19 virus infection”, combined with a list of all included drugs.
    MeSH
    suggested: (MeSH, RRID:SCR_004750)
    Duplicates were first excluded using EndNote (version 9.3.3).
    EndNote
    suggested: (EndNote, RRID:SCR_014001)
    Bayesian network model analysis was performed using ADDIS software10, whereas the diagrams were plotted using Stata V. 14.24.
    ADDIS
    suggested: None

    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:
    Our findings notwithstanding, this report has several limitations. First, the study focused on hospitalized patients, thus it may have suffered a possible selection bias. Therefore, it is not clear how asymptomatic individuals with a positive nucleic acid test result or mild COVID 19 symptoms would respond to the proposed drugs. Second, given we included trials from the whole world, the majority of studies involved in this meta-analysis were basically on Chinese population, thus further universal studies should be reviewed. Meanwhile, the heterogeneity between studies included in this report is critical. Sources of heterogeneity included broad inclusion criteria, differences in clinical trial design, patient cooperation and measurement of outcome. Additionally, differences in individual samples with regard to severity of the disease, intervention time, age and gender composition may have contributed to heterogeneity. Thus given the significant heterogeneity between studies related to COVID-19, our findings should be interpreted with caution, random effect model notwithstanding13. Despite these limitations, this network meta-analysis provides preliminary understanding on current COVID-19 treatment. In this report, we first conducted a comprehensive search in five databases including Cochrane, EmBase, PubMed and Web of Science, incorperating a relative a large sample of COVID 19 patients across the world. Although the reports on several drugs such as colchicine are limited, fin...

    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 10.1101/2020.11.16.20232884v1 on medRxiv