Convalescent Plasma in treatment of COVID-19: A review of evidence for a living systematic benefit-risk assessment

  1. Miranda Davies
  2. Samantha Lane
  3. Alison Evans
  4. Jacqueline Denyer
  5. Sandeep Dhanda
  6. Debabrata Roy
  7. Vicki Osborne
  8. Saad Shakir

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Abstract

Objectives

We aimed to review the evidence for a living systematic benefit risk assessment for convalescent plasma use amongst patients with severe COVID-19 disease, based on currently available data.

Methods

The assessment used the Benefit-Risk Action Team (BRAT) framework. Convalescent plasma treatment in severe COVID-19 was compared to standard of care, placebo or other treatments. A literature search was conducted to identify published papers from January 1 st , 2019 until July 8 th , 2020. A value tree was constructed which included ranked key benefits and risks.

Results

We screened 396 papers from PubMed and 127 papers from Embase. Four studies were eligible for inclusion as they contained comparative data. Results from a randomised controlled trial revealed a non-statistically significant shortening of time to clinical improvement of 2.15 days (95% CI, −5.28 to 0.99 days) in the intervention group compared with the control group, with a possible signal of increased efficacy amongst a small subset of patients with severe disease (but not life threatening disease), however this study may have been underpowered. Interpretation of findings amongst the three controlled non-randomised studies were limited by small patient numbers, lack of randomisation, and confounding by co-administration of other treatments. Limited data availability at the current time precluded construction of a data summary table and further quantitative analysis.

Conclusions

There was insufficient evidence from controlled studies to complete a data summary table for a systematic benefit-risk assessment of the use of CP for severe COVID-19 disease at the current time, and as such a benefit-risk conclusion could not be made. Whilst uncontrolled case series have suggested positive findings with CP, results from these studies are very difficult to interpret. We provide a framework which can be updated when further data that have an impact on the benefit-risk become available.

Article Summary

Strengths and limitations of this study

  • provides a living systematic benefit risk assessment based on currently available data for the use of convalescent plasma in patients with severe COVID-19 disease

  • establishes a framework inclusive of ranked key benefits and risks for convalescent plasma in severe COVID-19 disease, into which additional data can be added as this becomes available facilitating re-assessment of the benefit risk profile

  • uses a transparent framework (BRAT framework) which can be applied to other potential treatment options in this disease context

  • insufficient data available at the current time from comparative studies to form a benefit risk conclusion

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.08.24.20180729: (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
    BRAT uses a six-step iterative process to support the decision and communication of a benefit-risk assessment: define decision context, identify outcomes, identify data sources, customise framework, assess outcome importance, and display and interpret key Benefit-Risk metrics [15].
    BRAT
    suggested: (BRAT, RRID:SCR_013159)

    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:
    Whilst uncontrolled case series have suggested positive findings with CP, results from these studies are very difficult to interpret, given the limitations previously discussed. We identified only four controlled studies, inclusive of one RCT and three controlled non-randomised studies. In the RCT, findings for the primary outcome of time to clinical improvement amongst the 103 patients included were not statistically significant, however it is acknowledged that the study may have been underpowered due to its early termination. It is of note that a statistically significant result for this outcome was obtained when the intervention group was restricted to patients with severe disease only (but not life-threatening disease) compared to the control group. This may reflect the administration of this therapy earlier in the disease process, when it is considered that antibody-based therapies work best [36, 37]. Nevertheless, the overall median time between onset of symptoms and randomisation was 30 days, and the authors state that it is unclear whether earlier treatment would have resulted in greater benefit [24]. The question of whether earlier treatment may have resulted in greater benefit also applies to study findings by Zeng et al, in which the median days to treatment was 21.5 days [26]. In the study by Hegerova et al, the median time from hospitalization to CP was earlier at 2 days (IQR 1-4.3), however the study does not report on the median time from onset of symptoms [25]...

    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 10.1101/2020.08.24.20180729v1 on medRxiv