Evidence map›Paper›PMID 35348771›Full record

ArticleThe oncologist2022

COVID-19 Outcomes Among Patients With Cancer: Observations From the University of California Cancer Consortium COVID-19 Project Outcomes Registry.

Hala T Borno, Mi-Ok Kim, Julian C Hong, Sasha Yousefi, Amy Lin, Irina Tolstykh, Sylvia Zhang, Rana R McKay, Olivier Harismendy, Pelin Cinar and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The oncologist, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

16 authors.

Hala T BornoDivision of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0002-4357-9759
Mi-Ok KimHelen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA.
Julian C HongHelen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA.
Sasha YousefiDepartment of Radiation Oncology, University of California, San Francisco, San Francisco, CA, USA.
Amy LinDivision of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
Irina TolstykhDepartment of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
Sylvia ZhangHelen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA.
Rana R McKayDepartment of Medicine, University of California, San Diego, San Diego, CA, USA.
Olivier HarismendyMoores Cancer Center, University of California, San Diego, San Diego, CA, USA.
Pelin CinarDivision of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
Hope RugoDivision of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0001-6710-4814
Vadim S KoshkinDivision of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
Maya RabowCollege of Science, Northeastern University, Boston, MA, USA.
Christine WangSan Diego State University, San Diego, CA, USA.
Adina BaileyDivision of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
Eric J SmallDivision of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe risks associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its associated illness, coronavirus disease 2019 (COVID-19), among patients with a cancer diagnosis have not been fully characterized. This study leverages data from a multi-institutional cohort study, the University of California Cancer COVID Consortium, to evaluate outcomes associated with SARS-CoV-2 infection among patients with cancer.

methodsClinical data were collected from March to November 2020 and included patient demographics, cancer history and treatment, SARS-CoV-2 exposure and testing, and COVID-19 clinical management and outcomes. Multivariate ordinal logistic regression permitting unequal slopes was used to evaluate the impact of demographic, disease, and treatment factors on SARS-CoV-2 related hospitalization, intensive care unit (ICU) admission, and mortality.

findingsAmong all evaluated patients (n = 303), 147 (48%) were male, 118 (29%) were older adults (≥65 years old), and 104 (34%) were non-Hispanic white. A subset (n = 63, 21%) had hematologic malignancies and the remaining had solid tumors. Patients were hospitalized for acute care (n = 79, 26%), ICU-level care (n = 28, 9%), or died (n = 21, 7%) due to COVID-19. Patients with ≥2 comorbidities were more likely to require acute care (odds ratio [OR] 2.09 [95% confidence interval (CI), 1.23-3.55]). Cough was identified as a significant predictor of ICU hospitalization (OR 2.16 [95% CI, 1.03-4.57]). Importantly, mortality was associated with an active cancer diagnosis (OR 3.64 [95% CI, 1.40-9.5]) or advanced age (OR 3.86 [95% CI, 1.2-12.44]).

interpretationThis study observed that patients with active cancer or advanced age are at an increased risk of death from COVID-19. These study observations can inform risk counseling related to COVID-19 for patients with a cancer diagnosis.

Indexed as

COVID-19NeoplasmsAgedCohort StudiesComorbidityFemaleHospitalizationHumansMaleRegistriesRisk FactorsSARS-CoV-2cancerCOVID-19mortality

Identifiers

PMID35348771
PMCPMC9074994

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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.