Evidence map›Paper›PMID 32986528›Full record

ArticleJournal of clinical oncology : official journal of the American Society of Clinical Oncology2020

COVID-19 Severity and Outcomes in Patients With Cancer: A Matched Cohort Study.

Gagandeep Brar, Laura C Pinheiro, Michael Shusterman, Brandon Swed, Evgeniya Reshetnyak, Orysya Soroka, Frank Chen, Samuel Yamshon, John Vaughn, Peter Martin and 3 more

Abstract read
In one paragraph

Article in Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 9 pooled it
–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

82 citing papers in PubMed, 9 syntheses or guidelines pooled it.

  1. Pooled it
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22 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Gagandeep BrarDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.ORCID 0000-0002-3174-311X
Laura C PinheiroDivision of General Internal Medicine, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.ORCID 0000-0002-6920-8526
Michael ShustermanDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.ORCID 0000-0003-2899-7714
Brandon SwedDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.
Evgeniya ReshetnyakDivision of General Internal Medicine, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.ORCID 0000-0001-9478-4405
Orysya SorokaDivision of General Internal Medicine, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.ORCID 0000-0003-3282-2378
Frank ChenDivision of General Internal Medicine, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.
Samuel YamshonDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.
John VaughnDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.ORCID 0000-0001-8122-3852
Peter MartinDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.
Doru PaulDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.
Manuel HidalgoDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.ORCID 0000-0002-3765-3318
Manish A ShahDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine/New York-Presbyterian, New York, NY.ORCID 0000-0002-6913-9655

Funding

Disparities in COVID Disease Severity and Outcomes in New York CityUL1TR002384 · NCATS · WEILL MEDICAL COLL OF CORNELL UNIV · PI JULIANNE L IMPERATO-MCGINLEY · 2017 to 2026
$86.2M
Clinical and Translational Science CenterUL1TR000457 · NCATS · WEILL MEDICAL COLL OF CORNELL UNIV · PI IMPERATO-MCGINLEY, JULIANNE L · 2012 to 2016
$46.0M
NCATS NIH HHS UL1 TR000457NCATS NIH HHS UL1 TR002384
6 · The paper itself

Abstract

purposeSARS-CoV-2 (COVID-19) is a systemic infection. Patients with cancer are immunocompromised and may be vulnerable to COVID-related morbidity and mortality. The objectives of this study were to determine if patients with cancer have worse outcomes compared with patients without cancer and to identify demographic and clinical predictors of morbidity and mortality among patients with cancer.

methodsWe used data from adult patients who tested positive for COVID-19 and were admitted to two New York-Presbyterian hospitals between March 3 and May 15, 2020. Patients with cancer were matched 1:4 to controls without cancer in terms of age, sex, and number of comorbidities. Using Kaplan-Meier curves and the log-rank test, we compared morbidity (intensive care unit admission and intubation) and mortality outcomes between patients with cancer and controls. Among those with cancer, we identified demographic and clinical predictors of worse outcomes using Cox proportional hazard models.

resultsWe included 585 patients who were COVID-19 positive, of whom 117 had active malignancy, defined as those receiving cancer-directed therapy or under active surveillance within 6 months of admission. Presenting symptoms and in-hospital complications were similar between the cancer and noncancer groups. Nearly one half of patients with cancer were receiving therapy, and 45% of patients received cytotoxic or immunosuppressive treatment within 90 days of admission. There were no statistically significant differences in morbidity or mortality (

conclusionWe observed that patients with COVID-19 and cancer had similar outcomes compared with matched patients without cancer. This finding suggests that a diagnosis of active cancer alone and recent anticancer therapy do not predict worse COVID-19 outcomes and therefore, recommendations to limit cancer-directed therapy must be considered carefully in relation to cancer-specific outcomes and death.

Indexed as

AgedAntineoplastic AgentsCohort StudiesComorbidityCOVID-19FemaleHospitalizationHumansIntensive Care UnitsKaplan-Meier EstimateMaleMiddle AgedNeoplasmsNew YorkOutcome Assessment, Health CarePandemicsAntineoplastic Agents

Identifiers

PMID32986528
PMCPMC7676890

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.