Abaloparatide in Postmenopausal Women With Osteoporosis and Type 2 Diabetes: A Post Hoc Analysis of the ACTIVE Study
Bibliographic record
Abstract
ABSTRACT Type 2 diabetes mellitus (T2DM) increases fracture risk despite normal or increased BMD. Abaloparatide reduces fracture risk in patients with postmenopausal osteoporosis (PMO); however, its efficacy in women with T2DM is unknown. This post hoc analysis evaluated the efficacy and safety of abaloparatide in patients with T2DM. The analysis included patients with T2DM from the Abaloparatide Comparator Trial In Vertebral Endpoints (ACTIVE), a phase 3, double‐blind, randomized, placebo‐ and active‐controlled trial. In ACTIVE, participants were randomized 1:1:1 to daily s.c. injections of placebo, abaloparatide (80 μg), or open‐label teriparatide (20 μg) for 18 months. A total of 198 women with PMO and T2DM from 21 centers in 10 countries were identified from ACTIVE through review of their medical records. The main outcomes measured included effect of abaloparatide versus placebo on BMD and trabecular bone score (TBS), with secondary outcomes of fracture risk and safety, in patients from ACTIVE with T2DM. Significant (p < 0.001) improvements in BMD at total hip (mean change 3.0% versus −0.4%), femoral neck (2.6% versus −0.2%), and lumbar spine (8.9% versus 1.3%) and TBS at lumbar spine (3.72% versus −0.56%) were observed with abaloparatide versus placebo at 18 months. Fracture events were fewer with abaloparatide treatment in patients with T2DM, and differences were not significant between groups except nonvertebral fractures in the abaloparatide versus placebo groups (p = 0.04). Safety was consistent with the ACTIVE population. In conclusion, in women with PMO and T2DM, abaloparatide treatment resulted in significant improvements in BMD and TBS versus placebo, consistent with the overall ACTIVE population © 2020 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of 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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".