Effects of strength training on body composition, physical functioning, and quality of life in prostate cancer patients during androgen deprivation therapy
Bibliographic record
Abstract
BACKGROUND: Androgen deprivation therapy (ADT) increases survival rates in prostate cancer (PCa) patients with locally advanced disease, but is associated with side effects that may impair daily function. Strength training may counteract several side effects of ADT, such as changes in body composition and physical functioning, which in turn may affect health-related quality of life (HRQOL). However, additional randomised controlled trials are needed to expand this knowledge. MATERIAL AND METHODS: Fifty-eight PCa patients on ADT were randomised to either 16 weeks of high-load strength training (n = 28) or usual care (n = 30). The primary outcome was change in total lean body mass (LBM) assessed by dual x-ray absorptiometry (DXA). Secondary outcomes were changes in regional LBM, fat mass, and areal bone mineral density (aBMD) measured by DXA; physical functioning assessed by 1-repetition maximum (1RM) tests, sit-to-stand test, stair climbing test and Shuttle walk test; and HRQOL as measured by the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30. RESULTS AND CONCLUSION: No statistically significant effect of high-load strength training was demonstrated on total LBM (p = 0.16), but significant effects were found on LBM in the lower and upper extremities (0.49 kg, p < 0.01 and 0.15 kg, p < 0.05, respectively). Compared to usual care, high-load strength training showed no effect on fat mass, aBMD or HRQOL, but beneficial effects were observed in all 1RM tests, sit-to-stand test and stair climbing tests. Adherence to the training program was 88% for lower body exercises and 84% for upper body exercises. In summary, high-load strength training improved LBM in extremities and physical functioning, but had no effect on fat mass, aBMD, or HRQOL in PCa patients on ADT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".