Outcomes Evaluated in Controlled Clinical Trials on the Management of COVID-19: A Methodological Systematic Review

  1. Alexander G. Mathioudakis
  2. Markus Fally
  3. Rola Hashad
  4. Ahmed Kouta
  5. Ali Sina Hadi
  6. Sean Blandin Knight
  7. Nawar Diar Bakerly
  8. Dave Singh
  9. Paula R. Williamson
  10. Tim Felton
  11. Jørgen Vestbo

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Abstract

It is crucial that randomized controlled trials (RCTs) on the management of coronavirus disease 2019 (COVID-19) evaluate the outcomes that are critical to patients and clinicians, to facilitate relevance, interpretability, and comparability. This methodological systematic review describes the outcomes evaluated in 415 RCTs on the management of COVID-19, that were registered with ClinicalTrials.gov, by 5 May 2020, and the instruments used to measure these outcomes. Significant heterogeneity was observed in the selection of outcomes and instruments. Mortality, adverse events and treatment success or failure are only evaluated in 64.4%, 48.4% and 43% of the included studies, respectively, while other outcomes are selected less often. Studies focusing on more severe presentations (hospitalized patients or requiring intensive care) most frequently evaluate mortality (72.5%) and adverse events (55.6%), while hospital admission (50.8%) and viral detection/load (55.6%) are most frequently assessed in the community setting. Outcome measurement instruments are poorly reported and heterogeneous. Follow-up does not exceed one month in 64.3% of these earlier trials, and long-term COVID-19 burden is rarely assessed. The methodological issues identified could delay the introduction of potentially life-saving treatments in clinical practice. Our findings demonstrate the need for greater consistency, to enable decision makers to compare and contrast studies.

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  1. ScreenIT

    SciScore for 10.1101/2020.10.26.20218370: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Finally, the generic outcomes were further classified according to the COMET taxonomy17.
    COMET
    suggested: (CoMet, RRID:SCR_011925)

    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 study only included clinical trials that were registered until May 2020 and this may be a limitation as trial designs and endpoints may have evolved since then, in view of the emerging knowledge on the nature and outcomes of COVID-19 infection, and the published core outcome sets. Moreover, we only evaluated studies registered with the U.S. National Library of Medicine clinical trials register (ClinicalTrials.gov). However, our extensive, globally representative sample of 415 ongoing RCTs was a major strength of our methodological survey and we strongly believe it was sufficient to capture all relevant outcomes and measurement instruments. Characteristically, after extracting data from approximately 25% of the included trials, it became clear that we reached saturation with regards to the outcome categories, while by the time we extracted approximately 70% of the trials, we also reached saturation with regards to the outcome measurement instruments. Therefore, we are confident that we have not missed important outcomes, although we anticipate that newer outcomes may be introduced in newer trials, in response to our expanding knowledge on COVID-19 natural history and outcomes. Future studies will need to assess the impact of the emerging evidence on the natural history and outcomes of COVID-19 and of the four published core outcome sets and the meta-COS on the selection of outcomes in more recently registered trials. Another limitation of our study is the lack of a prospec...

    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 10.3390/life10120350
  3. Version published to 10.1101/2020.10.26.20218370v1 on medRxiv