Evidence map›Paper›PMID 33980502›Full record

ArticleBMJ health & care informatics2021

Comparison and impact of COVID-19 for patients with cancer: a survival analysis of fatality rate controlling for age, sex and cancer type.

Haiquan Li, Edwin Baldwin, Xiang Zhang, Colleen Kenost, Wenting Luo, Elizabeth A Calhoun, Lingling An, Charles L Bennett, Yves A Lussier

Abstract read
In one paragraph

Article in BMJ health & care informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Forging ahead: CANO/ACIO's Strategic Plan for 2022-2024.Canadian oncology nursing journal = Revue canadienne de nursing oncologique · 2022
    Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Haiquan Li *Department of Biosystems Engineering, The University of Arizona, Tucson, Arizona, USA haiquan@arizona.edu Yves.Lussier@utah.edu bennettc@cop.sc.edu.ORCID http://orcid.org/0000-0002-8049-0278
Edwin Baldwin *Department of Biosystems Engineering, The University of Arizona, Tucson, Arizona, USA.
Xiang ZhangDepartment of Biosystems Engineering, The University of Arizona, Tucson, Arizona, USA.
Colleen KenostDepartment of Biomedical Informatics, The University of Utah School of Medicine, Salt Lake City, Utah, USA.
Wenting LuoDepartment of Biosystems Engineering, The University of Arizona, Tucson, Arizona, USA.
Elizabeth A CalhounDepartment of Population Health, University of Kansas Medical Center, Kansas City, Kansas, USA.
Lingling AnDepartment of Biosystems Engineering, The University of Arizona, Tucson, Arizona, USA.
Charles L BennettDepartment of Clinical Pharmacy and Outcomes Sciences, University of South Carolina, Columbia, South Carolina, USA haiquan@arizona.edu Yves.Lussier@utah.edu bennettc@cop.sc.edu.
Yves A LussierDepartment of Biomedical Informatics, The University of Utah School of Medicine, Salt Lake City, Utah, USA haiquan@arizona.edu Yves.Lussier@utah.edu bennettc@cop.sc.edu.ORCID http://orcid.org/0000-0001-9854-1005

Funding

Utah Center for Clinical and Translational ScienceUL1TR002538 · NCATS · UNIVERSITY OF UTAH · PI HESS, RACHEL, MAJERSIK, JENNIFER JUHL · 2018 to 2022
$26.0M
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NCATS NIH HHS UL1 TR002538
6 · The paper itself

Abstract

objectivesPrior research has reported an increased risk of fatality for patients with cancer, but most studies investigated the risk by comparing cancer to non-cancer patients among COVID-19 infections, where cancer might have contributed to the increased risk. This study is to understand COVID-19's imposed HR of fatality while controlling for covariates, such as age, sex, metastasis status and cancer type.

methodsWe conducted survival analyses of 4606 cancer patients with COVID-19 test results from 16 March to 11 October 2020 in UK Biobank and estimated the overall HR of fatality with and without COVID-19 infection. We also examined the HRs of 13 specific cancer types with at least 100 patients using a stratified analysis.

resultsCOVID-19 resulted in an overall HR of 7.76 (95% CI 5.78 to 10.40, p<10 DISCUSSION: The results confirmed prior reports for the increased risk of fatality for patients with COVID-19 plus hematological malignancies and demonstrated similar findings of COVID-19 on melanoma, uterine, and kidney cancers.

conclusionThe results highlight the heightened risk that COVID-19 imposes on localised and haematological cancer patients and the necessity to vaccinate uninfected patients with cancer promptly, particularly for the cancer types most influenced by COVID-19. Results also suggest the importance of timely care for patients with localised cancer, whether they are infected by COVID-19 or not.

Indexed as

Health StatusPublic Health SurveillanceAdultAgedAged, 80 and overCOVID-19FemaleHumansMaleNeoplasmsRisk AssessmentRisk FactorsSurvival AnalysisYoung AdultBMJ health informaticsCOVID-19medical informatics

Identifiers

PMID33980502
PMCPMC8117441

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.