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Article Abstract
Introduction: The purpose of this study was to evaluate the association between body composition, overall survival, odds of receiving treatment, and patient-reported outcomes (PROs) in individuals living with metastatic non-small-cell lung cancer (mNSCLC).
Methods: This retrospective analysis was conducted in newly diagnosed patients with mNSCLC who had computed-tomography (CT) scans and completed PRO questionnaires close to metastatic diagnosis date. Cox proportional hazard models and logistic regression evaluated overall survival and odds of receiving treatment, respectively. Hazard ratios (HR) and odds ratios (OR) were evaluated as the interquartile range for body composition compartments. Multiple linear regression evaluated the association between PROs and body composition. Models were adjusted for gender, age at diagnosis, smoking history, and mutation status. The survival model also included adjustment for tumor histology.
Results: Our sample (n = 69) included men (52%) and women (48%), with a median age of 67.4-years, history of smoking (67%), wild-type genotype (75.4%), and a tumor histology of adenocarcinoma (68%). Greater skeletal muscle area was associated with higher physical function scores. Larger intermuscular adipose tissue area was associated with higher mortality risk (HR 2.03, 95% CI 1.32, 3.11), lower odds of receiving treatment (OR 0.76, 95% CI 0.61, 0.93), and higher fatigue. Larger subcutaneous adipose tissue area was associated with lower mortality risk (HR 0.42, 95% CI 0.22, 0.82) and higher odds of receiving treatment (OR 1.03, 95% CI 1.01, 1.06). Larger total adipose tissue area was linked with improved survival (HR 0.59, 95% CI 0.36, 0.96).
Conclusion: Findings support an association between different body composition compartments at mNSCLC diagnosis and survival, decisions to treat, and PROs. This work supports the use of data collected in routine CT scans and PROs to inform treatment decisions and supportive care options.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11705441 | PMC |
| http://dx.doi.org/10.1002/cam4.70534 | DOI Listing |
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