Efficacy of covid-19 vaccines in immunocompromised patients: systematic review and meta-analysis

  1. Ainsley Ryan Yan Bin Lee
  2. Shi Yin Wong
  3. Louis Yi Ann Chai
  4. Soo Chin Lee
  5. Matilda Xinwei Lee
  6. Mark Dhinesh Muthiah
  7. Sen Hee Tay
  8. Chong Boon Teo
  9. Benjamin Kye Jyn Tan
  10. Yiong Huak Chan
  11. Raghav Sundar
  12. Yu Yang Soon

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Abstract

Objective

To compare the efficacy of covid-19 vaccines between immunocompromised and immunocompetent people.

Design

Systematic review and meta-analysis.

Data sources

PubMed, Embase, Central Register of Controlled Trials, COVID-19 Open Research Dataset Challenge (CORD-19), and WHO covid-19 databases for studies published between 1 December 2020 and 5 November 2021. ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform were searched in November 2021 to identify registered but as yet unpublished or ongoing studies.

Study selection

Prospective observational studies comparing the efficacy of covid-19 vaccination in immunocompromised and immunocompetent participants.

Methods

A frequentist random effects meta-analysis was used to separately pool relative and absolute risks of seroconversion after the first and second doses of a covid-19 vaccine. Systematic review without meta-analysis of SARS-CoV-2 antibody titre levels was performed after first, second, and third vaccine doses and the seroconversion rate after a third dose. Risk of bias and certainty of evidence were assessed.

Results

82 studies were included in the meta-analysis. Of these studies, 77 (94%) used mRNA vaccines, 16 (20%) viral vector vaccines, and 4 (5%) inactivated whole virus vaccines. 63 studies were assessed to be at low risk of bias and 19 at moderate risk of bias. After one vaccine dose, seroconversion was about half as likely in patients with haematological cancers (risk ratio 0.40, 95% confidence interval 0.32 to 0.50, I 2 =80%; absolute risk 0.29, 95% confidence interval 0.20 to 0.40, I 2 =89%), immune mediated inflammatory disorders (0.53, 0.39 to 0.71, I 2 =89%; 0.29, 0.11 to 0.58, I 2 =97%), and solid cancers (0.55, 0.46 to 0.65, I 2 =78%; 0.44, 0.36 to 0.53, I 2 =84%) compared with immunocompetent controls, whereas organ transplant recipients were 16 times less likely to seroconvert (0.06, 0.04 to 0.09, I 2 =0%; 0.06, 0.04 to 0.08, I 2 =0%). After a second dose, seroconversion remained least likely in transplant recipients (0.39, 0.32 to 0.46, I 2 =92%; 0.35, 0.26 to 0.46), with only a third achieving seroconversion. Seroconversion was increasingly likely in patients with haematological cancers (0.63, 0.57 to 0.69, I 2 =88%; 0.62, 0.54 to 0.70, I 2 =90%), immune mediated inflammatory disorders (0.75, 0.69 to 0.82, I 2 =92%; 0.77, 0.66 to 0.85, I 2 =93%), and solid cancers (0.90, 0.88 to 0.93, I 2 =51%; 0.89, 0.86 to 0.91, I 2 =49%). Seroconversion was similar between people with HIV and immunocompetent controls (1.00, 0.98 to 1.01, I 2 =0%; 0.97, 0.83 to 1.00, I 2 =89%). Systematic review of 11 studies showed that a third dose of a covid-19 mRNA vaccine was associated with seroconversion among vaccine non-responders with solid cancers, haematological cancers, and immune mediated inflammatory disorders, although response was variable in transplant recipients and inadequately studied in people with HIV and those receiving non-mRNA vaccines.

Conclusion

Seroconversion rates after covid-19 vaccination were significantly lower in immunocompromised patients, especially organ transplant recipients. A second dose was associated with consistently improved seroconversion across all patient groups, albeit at a lower magnitude for organ transplant recipients. Targeted interventions for immunocompromised patients, including a third (booster) dose, should be performed.

Systematic review registration

PROSPERO CRD42021272088.

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  1. Version published to 10.1136/bmj-2021-068632
  2. ScreenIT

    SciScore for 10.1101/2021.09.28.21264126: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomization(18) The Cochrane Risk of Bias 2.0 tool was planned to be used for experimental studies which assesses 5 domains: bias arising from 1) the randomisation process, 2) deviations from intended interventions, 3) missing outcome data, 4) measurement of the outcome and 5) bias in selection of the reported result.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Search strategy: Searches of databases MEDLINE via PubMed, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), CORD-19, WHO COVID-19 Research Database, ClinicalTrials.gov and WHO international clinical trials registry platform were conducted per protocol in September 2021 for articles published from 1 December 2020 to 3 September 2021.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    EMBASE
    suggested: (EMBASE, RRID:SCR_001650)
    Cochrane Central Register of Controlled Trials
    suggested: (Cochrane Central Register of Controlled Trials, RRID:SCR_006576)
    Additionally, studies were excluded if they: Data extraction: Data was extracted according to a pre-determined proforma in Microsoft Excel Version 16.45 by two researchers.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    (18) The Cochrane Risk of Bias 2.0 tool was planned to be used for experimental studies which assesses 5 domains: bias arising from 1) the randomisation process, 2) deviations from intended interventions, 3) missing outcome data, 4) measurement of the outcome and 5) bias in selection of the reported result.
    Cochrane Risk of Bias
    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:
    Limitations: Firstly, the studies included in this paper are observational studies. Factors that may influence the immune response to the vaccine, such as comorbidities and age, may not be controlled between both the immunocompromised populations and healthy controls. To address this limitation, we performed subgroup analyses which showed no significant effect modification between studies with different median age. Secondly, there was heterogeneity in the definition of immunocompromised state. To address this limitation, we have pre-specified the definition of immunocompromised and performed subgroup analyses accordingly to assess the difference in seroconversion rates in different groups of immunocompromised patients which revealed stark differences between solid cancer, haematological cancer, IMID and transplant patients. Next, while seroconversion rates is an indication of the immune response to the vaccine, it is only a proxy for the different impact that the vaccine has on the infection rates and severity of COVID. Lastly, the definition of seroconversion and immunoassay used are not standardised across the studies. To address this limitation, we have performed subgroup analyses to determine if there is effect modification between studies that used different brands of immunoassays. Interestingly, significant effect modification was shown in dose 1 but not dose 2. Furthermore, vaccination type may influence the seroconversion rates of individuals after their COVID-19 vacc...

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.09.28.21264126v1 on medRxiv