Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 565

The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.

Association of Muscle and Adiposity Measured by Computed Tomography With Survival in Patients With Nonmetastatic Breast Cancer

Open access
Caan, Bette J., Cespedes Feliciano, Elizabeth M., Prado, Carla M., Alexeeff, Stacey, Kroenke, Candyce H., Bradshaw, Patrick, Quesenberry, Charles P., Weltzien, Erin K., Castillo, Adrienne L., Olobatuyi, Taiwo A., Chen, Wendy Y.·2018·JAMA Oncology

Abstract

Importance: Sarcopenia (low muscle mass), poor muscle quality (low muscle radiodensity), and excess adiposity derived from computed tomography (CT) has been related to higher mortality in patients with metastatic breast cancer, but the association with prognosis in patients with nonmetastatic breast cancer is unknown. Objective: To evaluate associations of all 3 body composition measures, derived from clinically acquired CT at diagnosis, with overall mortality in nonmetastatic breast cancer. Design, Setting, and Participants: This observational study included 3241 women from Kaiser Permanente of Northern California and Dana Farber Cancer Institute diagnosed from January 2000 to December 2013 with stages II or III breast cancer. We calculated hazard ratios (HRs) to evaluate the associations of all-cause mortality with sarcopenia, low muscle radiodensity, and total adipose tissue (TAT). Models were adjusted for sociodemographics, tumor characteristics, treatment, body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), and other body composition measures. We also evaluated the cross-classification of categories of sarcopenia (yes/no) and tertiles of TAT, with outcomes. Main Outcomes and Measures: Overall survival time and all-cause mortality. Results: Median (range) age of 3241 women included in this study was 54 (18-80) years, and median follow-up was 6.0 years; 1086 patients (34%) presented with sarcopenia, and 1199 patients (37%) had low muscle radiodensity. Among patients with nonmetastatic breast cancer, those with sarcopenia showed higher overall mortality (HR, 1.41; 95% CI, 1.18-1.69) compared with those without sarcopenia. Patients in the highest tertile of TAT also showed higher overall mortality (HR, 1.35; 95% CI, 1.08-1.69) compared with those in the lowest tertile. Low radiodensity was not associated with survival. In analyses of sarcopenia and TAT, highest mortality was seen in patients with sarcopenia and high TAT (HR, 1.89; 95% CI, 1.30-2.73); BMI alone was not significantly related to overall mortality and did not appropriately identify patients at risk of death owing to their body composition. Conclusions and Relevance: Sarcopenia is underrecognized in nonmetastatic breast cancer and occurs in over one-third of newly diagnosed patients. Measures of both sarcopenia and adiposity from clinically acquired CT scans in nonmetastatic patients provide significant prognostic information that outperform BMI and will help to guide interventions to optimize survival outcomes.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1001/jamaoncol.2018.0137

Cites

20 of 20 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 20 references

Cited by

See all 565

Metadata

Authors
Caan, B. J., Cespedes Feliciano, E. M., Prado, C. M., Alexeeff, S., Kroenke, C. H., Bradshaw, P., Quesenberry, C. P., Weltzien, E. K., Castillo, A. L., Olobatuyi, T. A., & Chen, W. Y.
Venue
JAMA Oncology
Published
2018-06-01
Volume
4
Issue
6
Pages
798
ISSN
2374-2437 (ISSN-L)
OpenAlex
W2796428104
Cited by
565
References
20
FWCI
31.92
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Association of Muscle and Adiposity Measured by Computed Tomography With Survival in Patients With Nonmetastatic Breast Cancer. https://app.cochat.ai/papers/10.1001/jamaoncol.2018.0137
The paper
Caan, B. J., Cespedes Feliciano, E. M., Prado, C. M., Alexeeff, S., Kroenke, C. H., Bradshaw, P., Quesenberry, C. P., Weltzien, E. K., Castillo, A. L., Olobatuyi, T. A., & Chen, W. Y. (2018). Association of Muscle and Adiposity Measured by Computed Tomography With Survival in Patients With Nonmetastatic Breast Cancer. JAMA Oncology. https://doi.org/10.1001/jamaoncol.2018.0137

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.