Persistence at 24 months with denosumab among postmenopausal women with osteoporosis: results of a prospective cohort study
Bibliographic record
Abstract
Persistence with prescribed medications for chronic diseases is important; however, persistence with osteoporosis treatments is historically poor. In this prospective cohort study of postmenopausal women treated for osteoporosis in real-world clinical practice settings in the USA and Canada, 24-month persistence with denosumab was 58%. PURPOSE: Patients who persist with their prescribed osteoporosis treatment have increased bone mineral density (BMD) and reduced risk of fracture. Twelve-month persistence with denosumab in routine clinical practice is as high as 95%, but there are limited data on longer-term persistence with denosumab in this setting. METHODS: This single-arm, prospective, cohort study evaluated 24-month persistence with denosumab administered every 6 months in postmenopausal women receiving treatment for osteoporosis in real-world clinical practice in the USA and Canada. Endpoints and analyses included the percentage of patients who persist with denosumab at 24 months (greater than or equal to four injections with a gap between injections of no more than 6 months plus 8 weeks), the total number of injections received by each patient, changes in BMD in persistent patients, and the incidence of serious adverse events (SAEs) and fractures. RESULTS: Among 935 enrolled patients, 24-month persistence was 58% (50% in US patients and 75% in Canadian patients). A majority of patients received at least four injections over the observation period (62% of US patients and 81% of Canadian patients). Among patients who were persistent at 24 months and who had a baseline, 12-month, and 24-month DXA scan, mean BMD increased from baseline to 24 months by 7.8% at the lumbar spine and 2.1% at the femoral neck. SAEs and fractures were reported for 122 (13.0%) patients and 54 (5.8%) patients, respectively. CONCLUSIONS: Persistence with denosumab for 24 months yields improvement in BMD among postmenopausal women with osteoporosis treated in routine clinical practice in the USA and Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".