Physiological correlates of cancer-related fatigue in advanced non-small cell lung cancer (NSCLC) patients
Bibliographic record
Abstract
8525 Background: Fatigue is a debilitating consequence of lung cancer and its treatments. The etiology of fatigue is unclear, and our current knowledge does not point to logical interventions. In this study, global fatigue score was assessed using the Brief Fatigue Inventory (BFI). A symptom questionnaire, as well as muscular and cardiorespiratory function, were assessed as potential contributors to the global fatigue score. Methods: Participants were evaluated by a physical therapist within the McGill Cancer Nutrition and Rehabilitation Program. Performance-based measures of physical function [upper limb strength and endurance (Jamar dynamometry), lower limb strength (30sec chair rise), cardiorespiratory function (2 minute walk -2MW)] and a symptom questionnaire [Edmonton Symptom Assessment Scale (ESAS)] were conducted at one point in time. Results: Eighty patients (43M:37F, mean age 68 ± 12 ) participated in the study. Forty-seven percent were actively receiving treatment at the time of assessment. On the BFI, 56% had moderate or severe fatigue and 88% indicated fatigue had interfered with their functioning during the past 24 hours. Global fatigue scores were unrelated to hand grip strength or endurance measurements but were significantly correlated with chair rise performance (R= -0.31, p<0.05), 2MW (R= -0.31, p<0.05), ESAS rating of pain (R=0.47, p<0.01), overall ESAS rating of breathlessness (R= 0.59, p<0.01), and ESAS rating of strength (R=0.58, p<0.01). Multivariate regression analysis suggested the best model for global fatigue scores incorporates chair rise performance, 2MW performance, ESAS rating of strength and ESAS rating of shortness of breath (adjusted R sq = 0.68, p<0.01). Conclusions: Fatigue is prevalent and impacts on the function of advanced NSCLC patients. Several key factors contribute to this fatigue, with muscular and cardiorespiratory restrictions playing an important role. Such findings may have clinical implications in the recommendations of rest and exercise to best manage fatigue. No significant financial relationships to disclose.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".