Change in Bone Turnover and Hip, Non-Spine, and Vertebral Fracture in Alendronate-Treated Women: The Fracture Intervention Trial
Bibliographic record
Abstract
UNLABELLED: We used data from the Fracture Intervention Trial to assess the relationship change in bone turnover after 1 year of alendronate or placebo treatment and subsequent hip, non-spine, and spine fracture risk among 6186 postmenopausal women. In the alendronate group (n = 3105), greater reductions in one or more biochemical marker were associated with a lower risk of fracture. INTRODUCTION: There are few data on the relationship between short-term change in biochemical markers of bone turnover and non-spine fracture risk among bisphosphonate-treated women, and the clinical use of such measurements is unknown. MATERIALS AND METHODS: We measured biochemical markers of bone turnover (bone-specific alkaline phosphatase [bone ALP], intact N-terminal propeptide of type I collagen, and C-terminal crosslinked telopeptide of type 1 collagen) and BMD of the spine and hip at baseline and after 1 year of alendronate or placebo. During a mean follow-up of 3.6 years, 72 hip, 786 non-spine, and 336 vertebral fractures were documented. RESULTS AND CONCLUSIONS: Each 1 SD reduction in 1-year change in bone ALP was associated with fewer spine (odds ratio = 0.74; CI: 0.63, 0.87), non-spine (relative hazard [RH] = 0.89; CI: 0.78, 1.00; p < 0.050), and hip fractures (RH = 0.61; CI: 0.46, 0.78). Alendronate-treated women with at least a 30% reduction in bone ALP had a lower risk of non-spine (RH = 0.72; CI: 0.55, 0.92) and hip fractures (RH = 0.26; CI: 0.08, 0.83) relative to those with reductions <30%. We conclude that greater reductions in bone turnover with alendronate therapy are associated with fewer hip, non-spine, and vertebral fractures, and the effect is at least as strong as that observed with 1-year change in BMD.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".