Estimated impact of the COVID-19 pandemic on cancer services and excess 1-year mortality in people with cancer and multimorbidity: near real-time data on cancer care, cancer deaths and a population-based cohort study

  1. Alvina G Lai
  2. Laura Pasea
  3. Amitava Banerjee
  4. Geoff Hall
  5. Spiros Denaxas
  6. Wai Hoong Chang
  7. Michail Katsoulis
  8. Bryan Williams
  9. Deenan Pillay
  10. Mahdad Noursadeghi
  11. David Linch
  12. Derralynn Hughes
  13. Martin D Forster
  14. Clare Turnbull
  15. Natalie K Fitzpatrick
  16. Kathryn Boyd
  17. Graham R Foster
  18. Tariq Enver
  19. Vahe Nafilyan
  20. Ben Humberstone
  21. Richard D Neal
  22. Matt Cooper
  23. Monica Jones
  24. Kathy Pritchard-Jones
  25. Richard Sullivan
  26. Charlie Davie
  27. Mark Lawler
  28. Harry Hemingway

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Abstract

To estimate the impact of the COVID-19 pandemic on cancer care services and overall (direct and indirect) excess deaths in people with cancer.

Methods

We employed near real-time weekly data on cancer care to determine the adverse effect of the pandemic on cancer services. We also used these data, together with national death registrations until June 2020 to model deaths, in excess of background (pre-COVID-19) mortality, in people with cancer. Background mortality risks for 24 cancers with and without COVID-19-relevant comorbidities were obtained from population-based primary care cohort (Clinical Practice Research Datalink) on 3 862 012 adults in England.

Results

Declines in urgent referrals (median=−70.4%) and chemotherapy attendances (median=−41.5%) to a nadir (lowest point) in the pandemic were observed. By 31 May, these declines have only partially recovered; urgent referrals (median=−44.5%) and chemotherapy attendances (median=−31.2%). There were short-term excess death registrations for cancer (without COVID-19), with peak relative risk (RR) of 1.17 at week ending on 3 April. The peak RR for all-cause deaths was 2.1 from week ending on 17 April. Based on these findings and recent literature, we modelled 40% and 80% of cancer patients being affected by the pandemic in the long-term. At 40% affected, we estimated 1-year total (direct and indirect) excess deaths in people with cancer as between 7165 and 17 910, using RRs of 1.2 and 1.5, respectively, where 78% of excess deaths occured in patients with ≥1 comorbidity.

Conclusions

Dramatic reductions were detected in the demand for, and supply of, cancer services which have not fully recovered with lockdown easing. These may contribute, over a 1-year time horizon, to substantial excess mortality among people with cancer and multimorbidity. It is urgent to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks.

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  1. Version published to 10.1136/bmjopen-2020-043828
  2. ScreenIT

    SciScore for 10.1101/2020.05.27.20083287: (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

    No key resources detected.

    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: This study has important limitations. First, there is a lack of near real-time clinical data in multiple digitally-mature hospitals with large numbers of COVID-19 infected patients. Second, the health records we used may have missed cases of cancer and underestimated incidence(36); if so, our estimates of excess deaths may be conservative. The National Health Service has national linked hospital admissions and cancer registration data with information on stage and details of surgical, chemotherapeutic and radiotherapy treatment of cancer. However, information governance for such data can take months to secure, making data-enabled research and time-sensitive responsive service improvement difficult. Third, we did not have access to multimorbidity data for the US. Fourth, we did not have access to data on children.

    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

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  3. Version published to 10.1101/2020.05.27.20083287v1 on medRxiv