The Effectiveness and Safety of Romosozumab and Teriparatide in Postmenopausal Women With Osteoporosis
Bibliographic record
Abstract
PURPOSE: The purpose of this observational study was to investigate the effectiveness and safety of romosozumab (ROMO) and teriparatide (TPTD) in a clinical setting. METHODS: A total of 315 postmenopausal women were included based on the reimbursement criteria for ROMO and TPTD at the Department of Endocrinology at Aarhus University Hospital. Criteria for ROMO were bone mineral density (BMD) T-score < -2.5 (femoral neck [FN], total hip [TH], or lumbar spine [LS]) + a fragility fracture (hip, spine, pelvis, distal forearm, or proximal humerus) within 3 years. Criteria for TPTD: within 3 years, ≥ 2 vertebral fractures or 1 vertebral fracture + BMD T-score (FN, TH, or LS) < -3. Data were collected from medical records. The primary end point was percentage change from baseline in BMD (FN, TH, and LS) at month 12. BMD was measured by dual-energy x-ray absorptiometry (DXA). RESULTS: At month 12, ROMO led to significantly (P < .001) larger increases than TPTD in BMD (FN: 4.8% vs 0.2%, TH: 5.7% vs 0.3%, and LS: 13.7% vs 9.3%). Discontinuation rate was lower with ROMO than with TPTD. Lower incidence of cardiovascular adverse events was observed with ROMO compared to TPTD. Treatment-naïve patients had nonsignificantly higher BMD increases compared to previously treated patients with both ROMO and TPTD. CONCLUSION: Treatment with ROMO yields larger increases in BMD than TPTD after 12 months and a higher rate of completion. ROMO was associated with a higher adherence.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".