LBA83 Outcomes of the 2019 novel coronavirus in patients with or without a history of cancer: A multi-centre North London experience

  1. N. Nalinie Joharatnam-Hogan
  2. D. Daniel Hochhauser
  3. K-K. Shiu
  4. H. Rush
  5. V. Crolley
  6. E. Butcher
  7. A. Sharma
  8. A. Muhammad
  9. N. Vasdev
  10. M. Anwar
  11. G. Kantser
  12. A. Saha
  13. F. Raja
  14. J. Bridgewater
  15. K.H. Khan

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Abstract

No abstract available

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  1. Version published to 10.1016/j.annonc.2020.08.2324
  2. ScreenIT

    SciScore for 10.1101/2020.04.16.20061127: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    BlindingInvestigators from the different hospitals provided data of consecutive COVID-19 positive patients for cohort B at their sites and were blinded to the data from other hospitals.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistics: Patient demographics and clinical characteristics were explored descriptively using STATA v15.1
    STATA
    suggested: (Stata, RRID:SCR_012763)
    (StataCorp. 2017).
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    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:
    We acknowledge the limitations to this study, including the retrospective sample collection and small sample size. Amongst the patients with cancer, there was significant heterogeneity between tumour types, including variability in stage and other clinico-pathological factors. Patients were selected consecutively, rather than choosing matched samples between cohorts, leading to possible confounding. Patient data was obtained from 4 different London hospitals, in which treatment may vary, and this therefore may have an impact on prognostic factors. However, selecting admitted patients in a consecutive manner helped to reduce selection bias. Selection bias was further reduced by selecting data from the primary institute only in the non-cancer ‘control’ arm. Data were date matched; however not age or gender matched. Given the limited sample size with a pre-defined severe event, analysis of the effects of multiple prognostic risk factors on mortality could not be carried out, due to the likely effect of other confounding variables, and this would be a useful analysis to undertake in a larger series of patients. We acknowledge the above limitations. Given the urgent timeline of an evolving and rapidly progressing pandemic, we elected not to wait for a larger sample-size, as we prioritise the early release of data to assist global physicians and oncologists to make real-time decisions. In the UK, the government has closed all non-essential places of work, limiting travel to key-wor...

    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.

  3. Version published to 10.1101/2020.04.16.20061127v1 on medRxiv