Bone health and body composition in prostate cancer: Meet-URO and AIOM consensus about prevention and management strategies
Bibliographic record
Abstract
BACKGROUND: Prostate cancer (PCa) treatments are associated with a detrimental impact on bone health (BH) and body composition. However, the evidence on these issues is limited and contradictory. This consensus, based on the Delphi method, provides further guidance on BH management in PCa. MATERIALS AND METHODS: In May 2023, a survey made up of 37 questions and 74 statements was developed by a group of oncologists and endocrinologists with expertise in PCa and BH. In June 2023, 67 selected Italian experts, belonging to the Italian scientific societies Italian Association of Medical Oncology and Italian Network for Research in Urologic-Oncology (Meet-URO), were invited by e-mail to complete it, rating their strength of agreement with each statement on a 5-point scale. An agreement ≥75% defined the statement as accepted. RESULTS: In non-metastatic hormone-sensitive PCa, the panel agreed that androgen deprivation therapy (ADT) alone implies sufficient fracture risk to warrant antifracture therapy with bone-targeting agents (BTAs) for cancer treatment-induced bone loss (CTIBL) prevention (79%). Therefore, no consensus was reached (48%) for the treatment with BTAs of patients receiving short-term ADT (<6 months). All patients receiving active treatment for metastatic hormone-sensitive PCa (75%), non-metastatic castration-resistant PCa (89%) and metastatic castration-resistant PCa (mCRPC) without bone metastases (84%) should be treated with BTAs at the doses and schedule for CTIBL prevention. All mCRPC patients with bone metastasis should be treated with BTAs to reduce skeletal-related events (94%). In all settings, the panel analyzed the type and timing of treatments and examinations to carry out for BH monitoring. The panel agreed on the higher risk of sarcopenic obesity of these patients and its correlation with bone fragility. CONCLUSIONS: This consensus highlights areas lacking major agreement, like non-metastatic hormone-sensitive prostate cancer patients undergoing short-term ADT. Evaluation of these issues in prospective clinical trials and identification of early biomarkers of bone loss are particularly urgent.
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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 | 0.104 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.007 | 0.005 |
| 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".