The Outcome of Gynecologic Cancer Patients With Covid-19 Infection: A Systematic Review And Meta-Analysis

  1. I Gde Sastra Winata
  2. Januar Simatupang
  3. Arie A Polim
  4. Yakob Togar
  5. Advenny Elisabeth Tondang

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Abstract

Objective

Cancer is a comorbidity that leads to progressive worsening of Covid-19 with increased mortality. This is a systematic review and meta-analysis to yield evidence of adverse outcomes of Covid-19 in gynecologic cancer.

Methods

Searches through PubMed, Google Scholar, ScienceDirect, and medRxiv to find articles on the outcome of gynecologic cancer with Covid-19 (24 July 2021-19 February 2022). Newcastle-Ottawa Scale tool is used to evaluate the quality of included studies. Pooled odds ratio (OR), 95% confidence interval (CI), random-effects model were presented. This study was registered to PROSPERO (CRD42021256557).

Results

We accepted 51 studies (1991 gynecologic cancer with Covid-19). Covid-19 infection was lower in gynecologic cancer vs hematologic cancer (OR 0.71, CI 0.56-0.90, p 0.005). Severe Covid and death were lower in gynecologic cancer vs lung and hematologic cancer (OR 0.36, CI 0.16-0.80, p 0.01), (OR 0.52, CI 0.44-0.62, p <0.0001), (OR 0.26, CI 0.10-0.67 p 0.005), (OR 0.63, CI 0.47-0.83, p 0.001) respectively. Increased Covid death is seen in gynecologic cancer vs breast, non-covid cancer, and non-cancer covid (OR 1.50, CI 1.20-1.88, p 0.0004), (OR 11.83, CI 8.20-17.07, p <0.0001), (OR 2.98, CI 2.23-3.98, p <0.0001) respectively.

Conclusion

Gynecologic cancer has higher Covid-19 adverse outcomes compared to non-cancer, breast cancer, non-metastatic, and Covid-19 negative population. Gynecologic cancer has fewer Covid-19 adverse outcomes compared to other cancer types, lung cancer, and hematologic cancer. These findings may aid health policies and services during the ongoing global pandemic.

Article activity feed

  1. Version published to 10.1101/2022.03.20.22272676v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2022.03.20.22272676: (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.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Boolean operators technique used for Pubmed/Medline search with (“COVID-19” or “2019-nCoV” or “SARS-CoV” or SARSCOV2 or 2019-nCov or “2019 coronavirus” or covid19) AND (gynecology or gynaecology) AND (tumor or malignancy or cancer) AND (outcomes or outcome) AND (gyn* tum* or gyn *malign* or gyn* cancer) AND (cancer surgery or oncolog* surger*) AND (brachytherapy or radiotherapy).
    Pubmed/Medline
    suggested: None
    We used “Gynecologic cancer AND Covid-19” with Google Scholar, Science Direct, and medRxiv.
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)
    Findings were accumulated and stored in Mendeley and Zotero for management and automated duplicate identification.
    Mendeley
    suggested: (Mendeley Data, RRID:SCR_002750)
    Data Extraction and Quality Assessment: Two authors (YT & AET) extracted data independently and stored them in The Microsoft Excel spreadsheet.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    Data Analysis & Synthesis: We performed data analysis mainly using Review Manager 5.4.1 (RevMan 5.4.1) by Cochrane collaboration.
    Review Manager
    suggested: None
    RevMan
    suggested: (RevMan, RRID:SCR_003581)
    Cochrane
    suggested: (Cochrane Library, RRID:SCR_013000)

    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.

    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 10.1101/2022.03.20.22272676v1 on medRxiv