Romosozumab significantly improves vertebral cortical bone mass and structure compared with teriparatide, whereas both treatments increase vertebral trabecular bone mass similarly: high-resolution quantitative computed tomography analyses of randomized controlled trial results in postmenopausal women with low bone mineral density
Bibliographic record
Abstract
Abstract Romosozumab, a sclerostin inhibitor, exerts a dual effect of increasing bone formation while decreasing bone resorption to rapidly increase bone mineral density (BMD) and reduce fracture risk in postmenopausal women. Iterative Convolution OptimizatioN (ICON) allows accurate calculation of deconvolved cortical thickness from high-resolution quantitative computed tomography (HR-QCT) scanning. This study employed HR-QCT to evaluate compartmental (including endosteal and periosteal) changes in the vertebral cortical shell in postmenopausal women who received romosozumab, teriparatide, or placebo. In a subset of a phase 2, randomized study (NCT00896532), women (55-85 yr) with low BMD (T-score ≤ −2.0, but not <−3.5, at the lumbar spine, total hip, or femoral neck) treated with subcutaneous (SC) romosozumab monthly (210 mg; n = 11), SC teriparatide daily (20 μg; n = 12), or SC placebo (n = 8) had spine HR-QCT scans at baseline and Month 12 to assess treatment effects on cortical and cancellous compartments of the T12 vertebra. HR-QCT was obtained at 120 kVp and 360 mAs. Cortical changes were evaluated using ICON software. At Month 12, compared to teriparatide and placebo, romosozumab treatment was associated with greater gains in all cortical parameters. Changes in cancellous bone parameters were similar with romosozumab and teriparatide. Romosozumab significantly increased cortical thickness (mean ± SD; 53 ± 18%) and the magnitude of this change was greater than that of teriparatide (20 ± 13%) and placebo (3 ± 6%); all p < .001. With romosozumab, cortical BMC and apparent cortical BMD were also significantly increased from baseline, and compared to teriparatide and placebo (all p < .001). These changes occurred through endosteal and periosteal bone matrix apposition, with greatest changes seen at the endosteal surface. The location and magnitude of these changes likely form the basis of the rapid improvement in bone mass, structure, and strength that contribute to romosozumab’s rapid vertebral fracture risk reduction efficacy; however, conclusions are limited by the small sample size.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".