Management of decreased bone mineral density in men starting androgen‐deprivation therapy for prostate cancer
Bibliographic record
Abstract
OBJECTIVE: To determine whether clinicians discuss bone-specific side-effects with patients on androgen-deprivation therapy (ADT) for prostate cancer, or prescribe lifestyle and pharmacological interventions for low bone mineral density (BMD), as decreased BMD is a common side-effect of ADT, leading to increased risk of fracture. PATIENTS AND METHODS: Sixty-six men (mean age 70.6 years) with non-metastatic prostate cancer and starting continuous ADT were enrolled in a prospective longitudinal study. BMD was determined by dual X-ray absorptiometry (DXA) at baseline. Patients were interviewed to obtain their medical histories, and charts were reviewed to determine whether clinicians documented potential bone side-effects in clinic notes, and made lifestyle and/or medication recommendations. Both were done at the start of ADT, and 3 and 6 months later. Patients were classified based on DXA T-score as having normal BMD, as osteopenic, or osteoporotic. RESULTS: At baseline, 53% of patients had osteopenia and 5% had osteoporosis. Within 6 months of starting ADT, general side-effects and bone-specific side-effects of ADT were documented as being discussed with 26% and 15%, respectively. Clinicians recommended lifestyle interventions to 11% of patients. Pharmacological interventions (calcium, vitamin D, and/or bisphosphonates) were recommended to 18% of all patients within 6 months of starting ADT, and to 26% and 67% of osteopenic and osteoporotic patients, respectively. CONCLUSIONS: A minority of patients is being informed of bone-specific side-effects of ADT. Lifestyle and drug interventions to prevent declines in BMD were recommended uncommonly. Practices around bone health for men starting ADT are suboptimal.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".