High-intensity interval training or resistance training versus usual care in men with prostate cancer on active surveillance: a 3-arm feasibility randomized controlled trial
Bibliographic record
Abstract
This study assessed the feasibility of a phase II randomized controlled trial of high-intensity interval training (HIIT), resistance training (RT), and usual care (UC) in men with prostate cancer (PCa) on active surveillance and evaluated changes in clinically relevant outcomes. Eighteen men undergoing active surveillance for PCa were randomized to HIIT (n = 5), RT (n = 7), or UC (n = 6). Exercise participants attended 2 supervised sessions weekly and were instructed to complete 1 home-based session weekly for 8 weeks. UC participants were provided with physical activity guidelines. Feasibility was met for attendance, compliance, and retention, but not recruitment. HIIT increased leg press (mean: +8.2 kg, 95% CI 1.1 to 15.3) from baseline to 8 weeks. RT increased seated row (mean: +11.7 kg, 95% CI 6.1 to 17.3), chest press (mean: +10.4 kg, 95% CI 5.3 to 15.5), leg press (mean: +13.1 kg, 95% CI 5.9 to 20.3), serum insulin-like binding protein-3 (IGFBP-3) (mean: +400.0 ng/mL, 95% CI 94.5 to 705.5), and decreased interferon-γ (mean: −3.1 pg/mL, 95% CI −5.7 to −0.4). No changes were observed in the UC group. HIIT and RT may be effective strategies for improving muscle strength; however, only RT may increase serum IGFBP-3. Strategies that can enhance recruitment in men on active surveillance are important prior to conducting a phase II trial. Trial registration number: ClinicalTrials.gov number NCT04266262. Novelty: High-intensity interval training or resistance training are feasible during active surveillance for prostate cancer. Resistance training may suppress the tumour-promoting effects of insulin-like growth factor-I (IGF-I) via increased expression of IGFBP-3.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".