Evidence map›Paper›PMID 40479498›Full record

ArticleCancer2025

Racial and ethnic variation in body composition and prognosis of nonmetastatic breast cancer.

Ijeamaka A Fumagalli, Erica T Warner, Adana A M Llanos, Charles P Quesenberry, Wendy Y Chen, Bette J Caan, Elizabeth M Cespedes Feliciano

Abstract read
In one paragraph

Article in Cancer, 2025. 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. Future of CT body composition research: Methodological discrepancies and advances.Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition · 2026
    Review
  2. Review
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

7 authors.

Ijeamaka A FumagalliDivision of Research, Kaiser Permanente Northern California, Pleasanton, California, USA.
Erica T WarnerClinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-2671-0313
Adana A M LlanosDepartment of Epidemiology, Mailman School of Public Health, Columbia University Irving Medical Center, New York, New York, USA.ORCID https://orcid.org/0000-0001-9954-9121
Charles P QuesenberryDivision of Research, Kaiser Permanente Northern California, Pleasanton, California, USA.
Wendy Y ChenDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
Bette J CaanDivision of Research, Kaiser Permanente Northern California, Pleasanton, California, USA.ORCID https://orcid.org/0000-0002-5803-310X
Elizabeth M Cespedes FelicianoDivision of Research, Kaiser Permanente Northern California, Pleasanton, California, USA.ORCID https://orcid.org/0000-0003-1192-4017

Funding

Body composition and breast cancer survival: immune and metabolic biomarkers in breast tumors - Disparities SupplementR01CA251589 · NCI · KAISER FOUNDATION RESEARCH INSTITUTE · PI FELICIANO, ELIZABETH MARJORIE CESPEDES · 2020 to 2025
$3.5M
Understanding the role of adiposity and adipokine-related RNA expression in the tumor microenvironment on breast cancer outcomes in a racially and ethnically diverse sampleR01CA277862 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Elizabeth Marjorie Cespedes Feliciano, Adana A. M. Llanos · 2023 to 2026
$2.1M
NCI NIH HHS R01 CA251589NCI NIH HHS R01CA251589NCI NIH HHS R01CA251589-04S1NCI NIH HHS R01 CA277862NCI NIH HHS R01CA277862
6 · The paper itself

Abstract

backgroundThe disproportionate burden of obesity among Black women may contribute to disparities in breast cancer survival; yet, associations of body mass index (BMI), a proxy for total adiposity, are inconsistent.

methodsTo examine racial/ethnic differences in body composition and evaluate associations with breast cancer-specific and all-cause mortality, this study identified 3898 women 18 to <90 years old, diagnosed in 2005-2019 with stage II-III breast cancer at Kaiser Permanente Northern California. The authors measured subcutaneous, visceral, and intermuscular adipose tissue area from computed tomography scans.

resultsBody composition differed by race: compared to other race/ethnicity groups, Black women had higher skeletal muscle and subcutaneous adipose, but lower visceral adipose tissues, whereas Asian/Pacific Islander women had lower intermuscular and subcutaneous adipose tissue. BMI was not significantly associated with mortality in any group. Among Black women, higher subcutaneous adipose tissue was associated with breast cancer-specific mortality (hazard ratio [HR], 1.24; 95% confidence interval [CI], 1.02-1.52) and all adipose tissue measures were associated with increased all-cause mortality (intermuscular HR, 1.26; 95% CI, 1.09-1.46; subcutaneous HR, 1.25; 95% CI, 1.05-1.48; and visceral HR, 1.32; 95% CI, 1.03-1.68, respectively). By contrast, only increased intermuscular adipose tissue was associated with all-cause mortality among White women (HR, 1.08; 95% CI, 1.00-1.16), with null associations for Hispanic and Asian/Pacific Islander women.

conclusionsBMI obscures variation in body composition, particularly for Black women, who have more subcutaneous adipose and skeletal muscle but less visceral adipose tissue at higher BMIs. These findings from routine imaging highlight opportunities for tailored lifestyle interventions to improve survivorship and mitigate disparities.

Indexed as

Body CompositionBreast NeoplasmsObesityAdiposityAdolescentAdultAgedAged, 80 and overBlack or African AmericanBody Mass IndexCaliforniaEthnicityFemaleHumansIntra-Abdominal FatMiddle Agedadipositybody compositionbody mass indexbreast cancerdisparities

Identifiers

PMID40479498
PMCPMC12453017

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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.