Evidence map›Paper›PMID 35406618›Full record

ArticleCancers2022

Associations of Computed Tomography Image-Assessed Adiposity and Skeletal Muscles with Triple-Negative Breast Cancer.

Livingstone Aduse-Poku, Jiang Bian, Dheeraj R Gopireddy, Mauricio Hernandez, Chandana Lall, Sara M Falzarano, Shahla Masood, Ara Jo, Ting-Yuan David Cheng

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

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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 at 1 institution in 1 country.

Livingstone Aduse-PokuDepartment of Epidemiology, College of Public Health & Health Professions & College of Medicine, University of Florida, Gainesville, FL 32603, USA.ORCID 0000-0001-9787-1731
Jiang BianDepartment of Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0002-2238-5429
Dheeraj R GopireddyDepartment of Radiology, College of Medicine-Jacksonville, University of Florida, Jacksonville, FL 32209, USA.
Mauricio HernandezDepartment of Radiology, College of Medicine-Jacksonville, University of Florida, Jacksonville, FL 32209, USA.
Chandana LallDepartment of Radiology, College of Medicine-Jacksonville, University of Florida, Jacksonville, FL 32209, USA.
Sara M FalzaranoDepartment of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL 32610, USA.
Shahla MasoodDepartment of Pathology and Laboratory Medicine, College of Medicine-Jacksonville, University of Florida, Jacksonville, FL 32210, USA.
Ara JoDepartment of Health Services Research, Management & Policy, College of Public Health & Health Professions, University of Florida, Gainesville, FL 32609, USA.ORCID 0000-0002-3428-7471
Ting-Yuan David ChengDepartment of Epidemiology, College of Public Health & Health Professions & College of Medicine, University of Florida, Gainesville, FL 32603, USA.ORCID 0000-0002-4105-828X
University of Florida · US

Funding

Using social networks to map and evaluate team science across CTSA hubsUL1TR001427 · NCATS · UNIVERSITY OF FLORIDA · PI MITCHELL, DUANE A. · 2015 to 2024
$37.2M
Energy Balance, mTOR pathway signaling, and breast cancer prognosisR37CA248371 · NCI · UNIVERSITY OF FLORIDA · PI Ting-Yuan Cheng · 2021 to 2026
$4.2M
mTOR pathway in breast cancer subtypes by race: A molecular pathological studyK07CA201334 · NCI · UNIVERSITY OF FLORIDA · PI CHENG, TING-YUAN · 2016 to 2020
$693k
NCATS NIH HHS UL1 TR001427NCI NIH HHS K07 CA201334NCI NIH HHS K07CA201334NCI NIH HHS R37 CA248371NIH HHS UL1 TR001427
6 · The paper itself

Abstract

Obesity measured by anthropometrics is associated with increased risk of triple-negative breast cancer (TNBC). It is unclear to what extent specific adipose tissue components, aside from muscle, are associated with TNBC. This retrospective study included 350 breast cancer patients who received treatment between October 2011 and April 2020 with archived abdominal or pelvic computed tomography (CT) images. We measured the areas of adipose tissue and five-density levels of skeletal muscle on patients' third lumbar vertebra (L3) image. Logistic regression was performed to examine the associations of specific adiposity and skeletal muscles components and a four-category body composition phenotype with the TNBC subtype. Results showed that higher vs. lower areas (3rd vs. 1st tertiles) of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were associated with increased odds of TNBC vs. non-TNBC after adjusting for age, race, stage, tumor grade, tumor size, and skeletal muscle areas (adjusted odds ratio [AOR], 11.25 [95% CI = 3.46-36.52]) and (AOR, 10.34 [95% CI = 2.90-36.90]) respectively. Higher areas of low density muscle was also associated with increased odds of TNBC (AOR, 3.15 [95% CI = 1.05-10.98]). Compared to normal body composition (low adipose tissue/high muscle), high adiposity/high muscle was associated with higher odds of TNBC (AOR, 5.54 [95% CI = 2.12-14.7]). These associations were mainly in premenopausal women and among patients with the CT performed after breast cancer surgery. Specific adipose tissue and low-density muscle can be associated with the TNBC subtype in breast cancer patients. The direction of association warrants confirmation by prospective studies.

Indexed as

adipose tissuesbody compositioncomputed tomographyskeletal musclestriple-negative breast cancer

Identifiers

PMID35406618
PMCPMC8997963
OpenAlexW4223518132

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.