Efficacy of Tocilizumab in Covid 19: A metanalysis of case series studies

  1. Shalam Mohamed Hussain
  2. Ayesha Farhana Syeda
  3. Osama Al-Wutayd
  4. Abdullah Al Nafeesah
  5. Mohammad Alshammari
  6. Sulaiman Alnasser
  7. Nandakumar Krishnadas

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Abstract

Background

characteristic feature of COVID-19 during its progression in severity is the cytokine storm (via interleukin-6, IL-6) which is responsible for secondary acute respiratory distress syndrome (ARDS) [4]. Tocilizumab has an antagonist effect on the IL-6 receptor. With present review and metanalysis, we intend to update the current status on the clinical efficacy of tocilizumab in the treatment of Covid 19 infections in the published literature of case series.

MATERIALS AND METHODS

The following inclusion criteria were used: (i) case series studies (number of reported patients in each study equal to or greater than ten (ii) use of tocilizumab alone or in combination with standard of care therapy (iii) Covid 19 adult patients (iv) the studies with endpoints on all-cause mortality, need for mechanical ventilation, clinical improvements.

Data synthesis and statistical analysis

Meta-analysis was performed using a random effects model and the DerSimonian and Laird method.

RESULTS

18 were selected for the quantitative analysis (meta-analysis). 14 studies were retrospective and 4 were prospective

Meta-analysis

The mortality rate of COVID-19 patients with tocilizumab was 21% (251/1212) Asymmetric funnel plot in the cylindrical form due to publication bias

In conclusion

the present synthesis provide us useful insights with the other available evidence to refine our strategy and equip ourselves effectively with tocilizumab to defeat COVID 19 to save humanity.

Limitations

The included studies utilized varied doses of tocilizumab (single or double), and duration drug availability issues emerged in some centers, which may have influenced both sample sizes and study designs.

Clinical implications

Incorporated studies without control groups into systematic reviews and quantitative synthesis especially when there are no other studies to consider can provide information for formulating effective treatment strategies for management of COVID 19 infections through the use of tocilizumab.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.12.20173682: (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

    Antibodies
    SentencesResources
    In Google scholar text word search of titles and abstracts was conducted using the following search terms ‘Tocilizumab,’ ‘anti-interleukin-6 antibody,’ and ‘COVID-19’ or ‘coronavirus 2019’ in various combinations.
    ‘anti-interleukin-6
    suggested: None
    Software and Algorithms
    SentencesResources
    A literature search was conducted on PubMed, Google Scholar and repositories of preprints (MedRxiv) for articles published until July, 2020 using keywords such as “COVID-19,” “tocilizumab,” “interleukin 6 antagonist,” or “IL-6 blocker”, or “human monoclonal antibody,” “cytokine storm treatment”).
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)

    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:
    Limitations: The included studies utilized varied doses of tocilizumab (single or double), and duration drug availability issues emerged in some centers, which may have influenced both sample sizes and study designs. The treatment allocations in these observational studies were based solely upon physician judgement rather than random assignment thereby leading to chances of risk of bias without accounting for risk factors. As the case series consists of studies with low sample sizes might likely cause over estimation of the overall effect size.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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 10.1101/2020.08.12.20173682v1 on medRxiv