Influence of clinical characteristics and anti-cancer therapy on outcomes from SARS-CoV-2 infection: a systematic review and meta-analysis of 5,678 cancer patients

  1. Ik Shin Chin
  2. Sara Galavotti
  3. Kay Por Yip
  4. Helen Curley
  5. Roland Arnold
  6. Archana Sharma-Oates
  7. Laura Chegwidden
  8. Siang Ing Lee
  9. Lennard YW Lee
  10. David J. Pinato
  11. Gino M. Dettorre
  12. Claire Palles

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Abstract

Background

The COVID-19 pandemic started a healthcare crisis and heavily impacted cancer services.

Methods

Data from cohort studies of COVID-19 cancer patients published up until October 23rd 2020 from PubMed, PubMed Central, medRxiv and Google Scholar were reviewed. Meta-analyses using the random effects model was performed to assess the risk of death in cancer patients with COVID-19.

Results

Our meta-analyses including up to 5,678 patients from 13 studies showed that the following were all statistically significant risk factors for death following SARS-CoV-2 infection in cancer patients: age of 65 and above, presence of co-morbidities, cardiovascular disease, chronic lung disease, diabetes and hypertension. There was no evidence that patients who had received cancer treatment within 60 days of their COVID-19 diagnosis were at a higher risk of death, including patients who had recent chemotherapy.

Conclusions

Cancer patients are susceptible to severe COVID-19, especially older patients and patients with co-morbidities who will require close monitoring. Our findings support the continued administration of anti-cancer therapy during the pandemic. The analysis of chemotherapy was powered at 70% to detect an effect size of 1.2 but all other anti-cancer treatments had lower power. Further studies are required to better estimate their impact on the outcome of cancer patients.

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  1. ScreenIT

    SciScore for 10.1101/2020.12.15.20248195: (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
    PubMed and PubMed Central (PMC) were searched for articles published in the last year up to 23rd October 2020 using the following keywords: coronavirus, COVID-19, SARS-CoV-2 AND cancer, malignancy and oncology.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    The same keywords were also used to identify relevant articles using medRxiv and Google Scholar.
    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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 10.1101/2020.12.15.20248195v1 on medRxiv