Association of Bone Density Monitoring in Routine Clinical Practice With Anti-Osteoporosis Medication Use and Incident Fractures: A Matched Cohort Study
Bibliographic record
Abstract
Routine bone mineral density (BMD) monitoring of individuals during the initial 5 years of anti-osteoporosis treatment is controversial. Using a registry-based cohort from the Province of Manitoba, Canada, we compared anti-osteoporosis medication use and fracture outcomes in women with versus without BMD monitoring receiving anti-osteoporosis medication. We identified 4559 women aged 40 years and older receiving anti-osteoporosis therapy with serial BMD testing (monitoring) within 5 years (mean interval 3.2 years) and 4559 propensity score-matched women without BMD monitoring. We assessed anti-osteoporosis medication use over 5 years from a population-based retail pharmacy database. Incident fractures to 10 years from health services data. During median 10 years observation, 1225 (13.4%) women developed major osteoporotic fracture, including 382 (4.2%) with hip fractures. Monitored women had significantly better fracture-free survival for major osteoporotic fracture (p = 0.040; 10-year cumulative risk 1.9% lower, 95% confidence interval [CI] 0.3-3.6%) and hip fracture ( p = 0.001; 10-year cumulative risk 1.8% lower, 95% CI 0.7-2.8%) compared with women who were not monitored. Hazard ratios (HRs) were significantly lower in monitored versus not monitored women for major osteoporotic fracture (HR = 0.89, 95% CI 0.80-0.98) and hip fracture (HR = 0.74, 95% CI 0.63-0.87). Days of medication use, medication persistence ratio, and treatment switching over 5 years were greater in monitored versus not monitored women. At the end of 5 years, more women in the monitored group persisted on treatment and more switched treatment, with switching behavior associated with an observed interval reduction in BMD. In conclusion, our findings suggest a possible role for BMD monitoring after initiating anti-osteoporosis therapy in the routine clinical practice setting. © 2019 American Society for Bone and Mineral Research.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".