Effects Of Exercise Training On Body Composition And Sarcopenia In People With Advanced Lung Cancer
Bibliographic record
Abstract
Sarcopenia is characterized by progressive skeletal muscle loss and has been associated with increased morbidity and mortality in patients with advanced lung cancer. Exercise interventions have demonstrated significant clinical benefits for patients with advanced cancer. PURPOSE: This study assessed the effect of a virtual exercise intervention for patients with advanced lung cancer on body composition, including skeletal muscle mass. METHODS: 27 participants with advanced lung cancer (median age = 66 years) undergoing systemic therapy in British Columbia, Canada participated in a 12-week supervised group exercise program delivered twice a week via Zoom. The 30-second sit-to-stand (30s STS) and 8-foot timed up and go (TUG) test were assessed at baseline and post-intervention. Changes in body composition were measured using pre- and post-intervention abdominal computed tomography (CT) scans. Height-adjusted muscle quantity was measured as skeletal muscle index (SMI), and muscle quality was measured as skeletal muscle density (SMD) and skeletal muscle gauge (SMG), which is SMI multiplied by SMD. Quantities of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and intermuscular adipose tissue (IMAT) were also measured. CT-derived sarcopenia was defined using body mass index (BMI) and sex-specific SMI cutoff points. Performance-derived sarcopenia was defined using sex-specific TUG and 30s STS cutoff points. Finally, combination-derived sarcopenia was defined using sex-specific cutoff points of the 30s STS, SMI, and SMD. Paired t-tests were used to assess pre- and post-intervention changes in body composition scores. RESULTS: SMI increased from 43.1cm2/m2 to 44.0cm2/m2 (p = 0.033). There were no significant changes in SMD, SMG, SAT, VAT, or IMAT. The percentage of participants that met the criteria for sarcopenia decreased from 73% at baseline to 64% post-intervention for CT-derived sarcopenia, 91% to 82% for physical performance-derived sarcopenia, and remained constant at 82% for combination-derived sarcopenia. CONCLUSION: A 12-week virtually supervised exercise program for patients with advanced lung cancer improved the quantity of skeletal muscle and decreased the proportion of participants categorized as sarcopenic, using body composition and physical performance. Supported by: This work was supported by BC Lung [UBC Number F21-00722] and the BC Cancer Foundation (UBC Number F23-05978). R. A. Fujita was supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES PrInt, grant 30/2022, process #88887.695669/ 2022-00).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".