Time to SARS‐CoV‐2 clearance among patients with cancer and COVID‐19

  1. Wenxin Xu
  2. Andrew J. Piper‐Vallillo
  3. Poorva Bindal
  4. Jonathan Wischhusen
  5. Jaymin M. Patel
  6. Daniel B. Costa
  7. Mary Linton B. Peters

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Abstract

Background

For cancer patients, coronavirus disease 19 (COVID‐19) infection can lead to delays in cancer therapy both due to the infection itself and due to the need to minimize exposure to other patients and to staff. Clearance guidelines have been proposed, but expected time to clearance has not been established.

Methods

We identified all patients at a tertiary care hospital cancer center between 25 March 2020 and 6 June 2020 with a positive nasopharyngeal reverse transcriptase polymerase chain reaction (RT‐PCR) test for the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), a cancer‐related visit within 3 years, and at least one follow‐up assay. We determined the time to clearance using American Society of Clinical Oncology (ASCO), the UK National Institute for Health and Care Excellence (UK‐NICE), and Centers for Disease Control and Prevention (CDC) criteria. A matched non‐cancer comparison cohort was also identified.

Results

Thirty‐two cancer patients were identified. Nineteen were cleared by ASCO criteria, with estimated median time to clearance of 50 days. Fourteen patients resumed chemotherapy prior to clearance. Using UK‐NICE criteria, median time to clearance would have been 31 days, and using CDC criteria, it would have been 13 days. The matched non‐cancer cohort had similar clearance time, but with less frequent testing.

Conclusion

SARS‐CoV‐2 clearance times differ substantially depending on the criteria used and may be prolonged in cancer patients. This could lead to a delay in cancer care, increased use of clearance testing, and extension of infection control precautions.

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  1. Version published to 10.1002/cam4.3708
  2. ScreenIT

    SciScore for 10.1101/2020.07.23.20161000: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Data collection was performed as part of an institutional COVID-19 registry project and approved by the institutional review board.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    SARS-CoV-2 RT-PCR testing was performed using the Abbott Laboratories m2000 platform in conjunction with either the Aldatu Biosciences PANDAA qDxTM SARS-CoV-2 or Abbott RealTime SARS-CoV-2 assays.
    Abbott Laboratories
    suggested: None
    Abbott
    suggested: (Abbott, RRID:SCR_010477)

    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 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.

  3. Version published to 10.1101/2020.07.23.20161000v1 on medRxiv