Diminishing Value from Multiple Serial Bone Densitometry in Women Receiving Antiresorptive Medication for Osteoporosis
Bibliographic record
Abstract
CONTEXT: The value of serial bone mineral density (BMD) monitoring while on osteoporosis therapy is controversial. OBJECTIVE: We determined the percentage of women classified as suboptimal responders to therapy with antiresorptive medications according to 2 definitions of serial BMD change. METHODS: This was a cohort study using administrative databases at a single-payer government health system in Manitoba, Canada. Participants were postmenopausal women aged 40 years or older receiving antiresorptive medications and having 3 sequential BMD measures. Women stopping or switching therapies were excluded. The percentage of women whose spine or hip BMD decreased significantly during the first or second interval of monitoring by BMD was determined. Suboptimal responder status was defined as BMD decrease during both monitoring intervals or BMD decreased from baseline to final BMD. RESULTS: There were 1369 women in the analytic cohort. Mean BMD monitoring intervals were 3.0 (0.8) and 3.2 (0.8) years. In the first interval, 3.2% and 6.5% of women had a decrease in spine or hip BMD; 8.0% and 16.9% had decreases in the second monitoring interval; but only 1.4% showed repeated losses in both intervals. Considering the entire treatment interval, only 3.2% and 7.4% showed BMD loss at spine or hip. Results may not apply to situations of poor adherence to antiresorptive medication or anabolic therapy use. CONCLUSION: Among women highly adherent to antiresorptive therapy for osteoporosis, a very small percentage sustained BMD losses on repeated measures. The value of multiple serial BMD monitoring to detect persistent suboptimal responders should be questioned.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".