Evidence map›Paper›PMID 38617523›Full record

ArticleTranslational cancer research2024

Predictors of mortality in hospitalized African American COVID-19 patients with cancer.

Suryanarayana Reddy Challa, Gholamreza Oskrochi, Gagan Paul Singh, Lakshmi G Chirumamilla, Nader Shayegh, Vaisakh K Nair, Megan Littleton, Danae T Byer, Nicole A Morrison, Brittany L Grossi and 6 more

Open access · diamondAbstract read
In one paragraph

Article in Translational cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 31% of its field
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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 2 institutions in 2 countries.

Suryanarayana Reddy ChallaDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Gholamreza OskrochiCollege of Engineering and Technology, American University of the Middle East, Egalia, Kuwait.
Gagan Paul SinghDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Lakshmi G ChirumamillaDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Nader ShayeghDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Vaisakh K NairDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Megan LittletonDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Danae T ByerDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Nicole A MorrisonDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Brittany L GrossiDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Barclay AshannaDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Shahnoza DusmatovaDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Trae ThompsonDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Dideolu O DawoduDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Hassan BrimDepartment of Pathology and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Hassan AshktorabDepartment of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.ORCID https://orcid.org/0000-0002-4048-4666
American University of the Middle East · KWHoward University · US

Funding

PROTEOMICS CORE FACILITYG12MD007597 · NIMHD · HOWARD UNIVERSITY · PI SOUTHERLAND, WILLIAM M. · 2012 to 2018
$14.8M
Inactivation of MSH3 in Colorectal Cancer and RaceR01CA258519 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ASHKTORAB, HASSAN, CARETHERS, JOHN M · 2021 to 2025
$2.9M
NCI NIH HHS R01 CA258519NIMHD NIH HHS G12 MD007597
6 · The paper itself

Abstract

Background: Coronavirus disease 2019 (COVID-19) manifest differently depending on patients' background and pre-existing conditions. It remains unclear how African Americans with cancer have been affected in comparison to those without. In this study, we aim to identify demographic, clinical, and laboratory markers associated with mortality in COVID-19 patients with cancer. Methods: We reviewed all COVID-19 hospitalized patients' records from Dec. 2019 to Oct. 2021 at Howard University Hospital. Patients having a history of, or active, cancer were reviewed. Clinical, treatment, lab test values, and pathological data were extracted. Univariable and multivariable analyses were conducted on the entire cohort as well as on cases and controls separately, using SPSS software. Results: Out of 512 COVID-19 infected patients, 49 had cancer, either active or history of cancer (cases) and 463 COVID-19 were cancer-free (controls), allowing for comparison. African American race was predominant in both cases and controls, 83.7% and 66.7% respectively. Cancer patients were older than non-cancer patients (mean age: 70.6 Conclusions: Albumin level has an inverse relationship with clinical outcomes among all COVID-19 infected cancer patients. Reduction in albumin level during the hospital stay, particularly in COVID-19 cancer patients should be considered as a predictor of mortality. Further research with a large cohort size is needed to verify and identify other predictors of outcomes in COVID-19 patients with cancer.

Indexed as

African Americanscancerscoronavirus disease 2019 (COVID-19)mortalitypredictors

Identifiers

PMID38617523
PMCPMC11009794
OpenAlexW4393281324

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.