Cited by 143Nutrition and Health in AgingLung Cancer Diagnosis and TreatmentBody Composition Measurement Techniques

Skeletal muscle radiodensity is prognostic for survival in patients with advanced non-small cell lung cancer

Sjøblom, Bjørg, Grønberg, Bjørn H., Wentzel-Larsen, Tore, Baracos, Vickie E., Hjermstad, Marianne J., Aass, Nina, Bremnes, Roy M., Fløtten, Øystein +2 more·2016·Clinical Nutrition

Abstract

Background & aims Recent research indicates that severe muscular depletion (sarcopenia) is frequent in cancer patients and linked to cachexia and poor survival. Our aim was to investigate if measures of skeletal muscle hold prognostic information in advanced non-small cell lung cancer (NSCLC).Methods We included NSCLC patients with disease stage IIIB/IV, performance status 0-2, enrolled in three randomised trials of first-line chemotherapy (n = 1305). Computed tomography (CT) images obtained before start of treatment were used for body composition analyses at the level of the third lumbar vertebra (L3). Skeletal muscle mass was assessed by measures of the cross sectional muscle area, from which the skeletal muscle index (SMI) was obtained. Skeletal muscle radiodensity (SMD) was measured as the mean Hounsfield unit (HU) of the measured muscle area. A high level of mean HU indicates a high SMD.Results Complete data were available for 734 patients, mean age 65 years. Both skeletal muscle index (SMI) and muscle radiodensity (SMD) varied largely. Mean SMI and SMD were 47.7 cm 2/m 2 and 37.4 HU in men (n = 420), 39.6 cm 2/m 2 and 37.0 HU in women (n = 314). Multivariable Cox regression analyses, adjusted for established prognostic factors, showed that SMD was independently prognostic for survival (Hazard ratio (HR) 0.98, 95% CI 0.97-0.99, p = 0.001), whereas SMI was not (HR 0.99, 95% CI 0.98-1.01, p = 0.329).Conclusion Low SMD is associated with poorer survival in advanced NSCLC. Further research is warranted to establish whether muscle measures should be integrated into routine practice to improve prognostic accuracy.

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Crossref · 10.1016/j.clnu.2016.03.010

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Authors
Sjøblom, B., Grønberg, B. H., Wentzel-Larsen, T., Baracos, V. E., Hjermstad, M. J., Aass, N., Bremnes, R. M., Fløtten, Ø., Bye, A., & Jordhøy, M.
Affiliations
  • Oslo University Hospital (NO)
  • Norwegian University of Science and Technology (NO)
  • University of Alberta (CA)
  • University Hospital of North Norway (NO)
  • Haukeland University Hospital (NO)
  • University of Oslo (NO)
Corresponding author
Sjøblom, Bjørg
Venue
Clinical Nutrition
Publisher
Elsevier BV
Published
2016-12
Volume
35
Issue
6
Pages
1386-1393
ISSN
0261-5614 (ISSN-L)
OpenAlex
W2332389425
Cited by
143
References
38
Citations by year
2026: 4 · 2025: 15 · 2024: 8 · 2023: 10 · 2022: 13 · 2021: 19 · 2020: 15 · 2019: 17 · 2018: 23 · 2017: 18 · 2016: 1
FWCI
15.84
Type
journal article
Language
en
Open access
closed
Locations
  • Clinical Nutrition (publishedVersion)
  • PubMed (publishedVersion)
Funders
Canadian Institutes of Health Research
Topics
  • Health Sciences › Medicine › Physiology › Nutrition and Health in Aging
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
  • Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
Keywords
skeletal muscle radiodensity, non-small cell lung cancer, sarcopenia, skeletal muscle index, survival prediction, body composition, Hounsfield units, muscle cross-sectional area, first-line chemotherapy, advanced cancer
MeSH terms
Aged, Cachexia, Carcinoma, Non-Small-Cell Lung, Female, Humans, Image Processing, Computer-Assisted, Lung Neoplasms, Male, Middle Aged, Prognosis, Tomography, X-Ray Computed, Body Mass Index, Muscle, Skeletal, Sarcopenia

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