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Prognostic impact of skeletal muscle volume derived from cross-sectional computed tomography images in breast cancer
- Source :
- Breast Cancer Research and Treatment. 172:425-436
- Publication Year :
- 2018
- Publisher :
- Springer Science and Business Media LLC, 2018.
-
Abstract
- This study aimed to determine whether the prognosis of breast cancer is affected by muscle or fat volume as measured from computed tomography (CT) images. We identified 1460 patients with chest CT who were diagnosed as having breast cancer at the National Cancer Center, Korea, between January 2001 and December 2009. Using CT images of 10-mm slices, we measured the cross-sectional areas of skeletal muscle and adipose tissue at the 3rd lumbar vertebrae, and derived their volumes. The skeletal muscle volume, fat volume, and muscle-to-fat ratio were evaluated for association with overall survival (OS) and recurrence-free survival (RFS). The median skeletal muscle and fat volumes among the patients were 93.3 cc (range 39.6–236.9) and 420.1 cc (range 19.5–1392.3), respectively. Patients with higher muscle volume had better prognosis than those with lower muscle volume [hazard ratio (HR) 0.56, 95% confidence interval (CI) 0.34–0.92, P = 0.022 for OS; HR 0.72, 95% CI 0.52–0.99, P = 0.046 for RFS]. However, body mass index (BMI) and fat volume were not associated with prognosis. In addition, muscle volume was a significant prognosticator for OS, regardless of BMI (HR 0.55, 95% CI 0.32–0.93, P = 0.034 in BMI
- Subjects :
- Adult
0301 basic medicine
Cancer Research
medicine.medical_specialty
Urology
Adipose tissue
Breast Neoplasms
Lumbar vertebrae
Disease-Free Survival
Body Mass Index
03 medical and health sciences
0302 clinical medicine
Breast cancer
Republic of Korea
medicine
Humans
Muscle, Skeletal
Aged
Retrospective Studies
business.industry
Hazard ratio
Cancer
Skeletal muscle
Middle Aged
Prognosis
medicine.disease
Confidence interval
030104 developmental biology
medicine.anatomical_structure
Adipose Tissue
Oncology
030220 oncology & carcinogenesis
Female
Tomography, X-Ray Computed
business
Body mass index
Subjects
Details
- ISSN :
- 15737217 and 01676806
- Volume :
- 172
- Database :
- OpenAIRE
- Journal :
- Breast Cancer Research and Treatment
- Accession number :
- edsair.doi.dedup.....3ecda0febe62349519928c5a7cb2e2fe
- Full Text :
- https://doi.org/10.1007/s10549-018-4915-7