Long-term impact of adherence to oral bisphosphonates on osteoporotic fracture incidence
Bibliographic record
Abstract
Adherence to osteoporosis treatments is a critical parameter resulting in suboptimal effectiveness in real-life practice. The long-term effect of adherence on fracture risk has not been assessed. This was a retrospective study using provincial health insurance claims databases to assess the association between adherence to oral bisphosphonates (OBP) and incidence of osteoporotic fractures in all Ontario patients with osteoporosis between April 1996 and December 2009. Multivariate logistic regression models were used to assess the association between OBP adherence and fracture risk. Treatment duration was classified into 2-year intervals. Compliance was estimated with the medication possession ratio (MPR), and persistence was defined as the length of continuous therapy without a gap in refills >30 days. The study cohort was composed of 636,114 patients, among whom 36.1% were prescribed OBPs for 0 to 2 years, 19.7% for 2 to 4 years, 15.1% for 4 to 6 years, 12% for 6 to 8 years, 9.1% for 8 to 10 years, 6.1% for 10 to 12 years, and 1.9% for 12 to 14 years. Overall, the mean (SD) compliance for the cohort was 0.72 (0.30) with 53.5% of the patients having compliance >80% and 24.6% being persistent with treatment during the 14-year follow-up period. Significant associations between high adherence and reduced fracture risk over the entire 14-year period were observed; the overall odds ratio for categorical compliance (MPR >80% or MPR ≤80%), continuous compliance, and persistence were 0.909 (95% confidence interval [CI] 0.893-0.925), 0.918 (95% CI 0.893-0.944), and 0.804 (95% CI 0.787-0.821), respectively. In conclusion, adherence to OBP in osteoporosis management is suboptimal in a real-life setting. A significant positive association exists between poor adherence and increased risk of osteoporotic fractures, which becomes augmented with longer treatment duration.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".