Associations of fat and muscle mass with overall survival in men with prostate cancer: a systematic review with meta-analysis
Bibliographic record
Abstract
BACKGROUND: To systematically review and analyse the associations between fat and muscle mass measures with overall survival in men with prostate cancer. METHODS: A systematic search was conducted in CINAHL, Cochrane Library, EMBASE, PubMed, and Web of Science databases from inception to December 2020, while abstracts from the American Society of Clinical Oncology (ASCO), Clinical Oncology Society of Australia (COSA), and the American College of Sports Medicine (ACSM) conferences were searched from 2014 to 2020. Eligible articles examined the association of body composition measures, such as fat mass (e.g., fat mass, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and VAT/SAT) and muscle mass measures, with overall survival in prostate cancer patients at any treatment stage. The primary endpoint was overall survival. Random-effect meta-analysis was conducted for studies reporting multivariable or univariable analysis assessing the associations of fat mass measures (i.e., fat mass, VAT, SAT, VAT/SAT) and muscle mass measures with overall survival. RESULTS: Sixteen cohort studies that comprised 4807 men with prostate cancer were included. Total adiposity (hazard ratio (HR) 0.98, 95% CI: 0.75-1.28, p = 0.888) and VAT (HR 1.03, 95% CI: 0.74-1.43, p = 0.873) were not significantly associated with overall survival, while higher subcutaneous adipose tissue levels were associated with higher survival (HR 0.68, 95% CI: 0.54-0.84, p = 0.001). Greater mortality risk was found in patients with localised (HR 1.91, 95% CI: 1.40-2.62, p < 0.001) and advanced disease (HR 1.43, 95% CI: 1.07-1.92, p = 0.020) presenting with low levels of muscle mass compared to those presenting with high levels. DISCUSSION: These results indicate that although overall adiposity should be cautiously interpreted in regards to survival, high muscle mass and SAT, and low VAT/SAT ratio values are associated with overall survival in men with prostate cancer.
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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 | 0.011 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.027 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".