Cell-based therapies for COVID-19: A living, systematic review

  1. Gabriel Rada
  2. Javiera Corbalán
  3. Patricio Rojas

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Abstract

Objective This living, systematic review aims to provide a timely, rigorous, and continuously updated summary of the available evidence on the role of cell-based therapies in the treatment of patients with COVID-19. Data sources We conducted searches in PubMed/Medline, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), grey literature, and in a centralized repository in L·OVE (Living OVerview of Evidence). L·OVE is a platform that maps PICO questions to evidence from the Epistemonikos database. In response to the COVID-19 emergency, L·OVE was adapted to expand the range of evidence it covers and customized to group all COVID-19 evidence in one place. All the searches covered the period until 23 April 2020 (one day before submission). Eligibility criteria for selecting studies and methods We adapted an already published standard protocol for multiple parallel systematic reviews to the specificities of this question. We searched for randomized trials evaluating the effectiveness and safety of cell-based therapies versus placebo or no treatment in patients with COVID-19. Anticipating the lack of randomized trials directly addressing this question, we also searched for trials evaluating other coronavirus infections, such as MERS-CoV and SARS-CoV, and nonrandomized studies in COVID-19. Two reviewers independently screened each study for eligibility. A living, web-based version of this review will be openly available during the COVID-19 pandemic. We will resubmit this review to a peer-reviewed journal every time the conclusions change or whenever there are substantial updates. Results We screened 1 043 records, but no study was considered eligible. We identified 61 ongoing studies, including 39 randomized trials evaluating different types of cell-based therapies in COVID-19. Conclusions We did not find any studies that met our inclusion criteria, and hence there is no evidence to support or refute the use of cell-based therapies for treating patients with COVID-19. A substantial number of ongoing studies should provide valuable evidence to inform researchers and decision-makers in the near future. PROSPERO Registration number CRD42020179711

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  1. Version published to 10.5867/medwave.2020.11.8078
  2. ScreenIT

    SciScore for 10.1101/2020.04.24.20078667: (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
    The additional searches are uploaded to the screening software Collaboratron™[25].
    Collaboratron™
    suggested: None
    Strategy for data synthesis: If we include more than one trial, we conduct meta-analysis for studies clinically homogeneous using RevMan 5 [29], using the inverse variance method with random effects model.
    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: We detected the following sentences addressing limitations in the study:
    However, the traditional model for conducting reviews has several limitations, including high demand for time and resources [34] and a rapid obsolescence [35]. Amidst the COVID-19 crisis, researchers should make their best effort to answer the urgent needs of health decision makers yet without giving up scientific accuracy. Information is being produced at a vertiginous speed [36], so alternative models are needed. One potential solution to these shortfalls are rapid reviews, reviews that omit some of the steps of a traditional systematic review in order to move faster. Unfortunately, in these reviews rapidity comes at the cost of quality [37]. Furthermore, they do not solve the issue of obsolescence. Living systematic reviews do address that issue [38]. They are continually updated by incorporating relevant new evidence as it becomes available, at a substantial effort. So, an approach combining these two models might prove more successful in providing the scientific community and other interested parties with evidence that is actionable, rapidly and efficiently produced, up to date, and of the highest quality [39]. This review is part of a larger project set up to put such an approach into practice. The project aims to produce multiple parallel living systematic reviews relevant to COVID-19 following the higher standards of quality in evidence synthesis production [19]. We believe our methods are well suited to handle the abundance of evidence that is to come, including evid...

    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.

  3. Version published to 10.1101/2020.04.24.20078667v1 on medRxiv