The Effect of Abaloparatide-SC on Fracture Risk Is Independent of Baseline FRAX Fracture Probability: A Post Hoc Analysis of the ACTIVE Study
Bibliographic record
Abstract
Daily subcutaneous (SC) injections of the investigational drug abaloparatide-SC (80 mcg) for 18 months significantly decrease the risk of vertebral and nonvertebral fracture compared with placebo in postmenopausal women. We examined the efficacy of abaloparatide-SC as a function of baseline fracture risk, assessed using the FRAX tool. Baseline clinical risk factors (age, body mass index [BMI], prior fracture, glucocorticoid use, rheumatoid arthritis, and smoking) were entered into country-specific FRAX models to calculate the 10-year probability of major osteoporotic fractures, with or without femoral neck bone mineral density (BMD). The interaction between probability of a major osteoporotic fracture and treatment efficacy was examined by a Poisson regression. A total of 821 women randomized to placebo and 824 women to abaloparatide-SC, mean age 69 years in both groups, were followed for up to 2 years. At baseline, the 10-year probability of major osteoporotic fractures (with BMD) ranged from 2.3% to 57.5% (mean 13.2%). Treatment with abaloparatide-SC was associated with a 69% (95% confidence interval [CI] 38-85%) decrease in major osteoporotic fracture (MOF) and a 43% (95% CI 9-64%) decrease in any clinical fracture compared with placebo. For all outcomes, hazard ratios tended to decrease (ie, greater efficacy) with increasing fracture probability. Whereas the interaction approached significance for the outcome of any fracture (p = 0.11), there was no statistically significant interaction for any of the fracture outcomes. Similar results were noted when FRAX probability was computed without BMD. Efficacy of abaloparatide-SC to decrease the risk of major osteoporotic fracture or any clinical fracture in postmenopausal women with low BMD and/or prior fracture appears independent of baseline fracture probability. © 2017 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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".