Effects of Structured Exercise Programs on Self-Reported Health-Related Quality of Life in Patients with Advanced Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
Current treatments for metastatic non-small cell lung cancer (NSCLC) have improved survival but remain non-curative, primarily aiming to control disease and to extend life. Structured exercise has demonstrated clinical and quality-of-life benefits in early-stage NSCLC. This systematic review assesses the impact of adjunctive exercise programs on health-related quality of life (HRQoL) in advanced NSCLC patients, with safety as a secondary outcome. Of 1168 studies screened, 13 met the inclusion criteria. All eligible studies were included in the systematic review, and three underwent meta-analysis. Using Synthesis Without Meta-analysis (SWiM), the findings were heterogeneous: four studies showed positive outcomes, two had mixed results, and seven showed negative outcomes. Meta-analysis of studies utilizing the EORTC-C30 tool demonstrated a positive mean difference of 1.57 (95% CI: 0 to 3.14), indicating a trend toward HRQoL improvement. Safety analyses largely revealed no major adverse events related to exercise interventions. Future studies must therefore be designed to account for confounders intrinsic to the underlying disease of study participants to better determine both the efficacy and the safety of structured, adjunctive exercise programs in this patient population.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.024 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".