Efficacy of Raloxifene on Vertebral Fracture Risk Reduction in Postmenopausal Women with Osteoporosis: Four-Year Results from a Randomized Clinical Trial
Bibliographic record
Abstract
The Multiple Outcomes of Raloxifene Evaluation trial studied 7705 postmenopausal women with osteoporosis randomized to placebo, or raloxifene 60 or 120 mg/d [JAMA 282(1999): 637]. This report assesses the efficacy of raloxifene on the long-term cumulative incidence new vertebral fractures through 4 yr. New vertebral fractures was assessed from radiographs taken at baseline, yr 2-4. The primary analysis was the cumulative incidence of new vertebral fractures through 4 yr. A posthoc analysis compared the vertebral fracture risk in yr 4 alone with that observed in the first 3 yr. The 4-yr cumulative relative risks (RR) for one or more new vertebral fractures were 0.64 [95% confidence interval (CI) 0.53, 0.76] with raloxifene 60 mg/d and 0.57 (95% CI 0.48, 0.69) with raloxifene 120 mg/d. In yr 4 alone, raloxifene 60 mg/d reduced the new vertebral fracture risk by 39% [RR 0.61 (95% CI 0.43, 0.88)], which was not found to be significantly different from the RR observed in the first 3 yr in both raloxifene groups, irrespective of prevalent fracture status. The nonvertebral fracture risk was not significantly reduced [RR 0.93 (95% CI 0.81, 1.06)]. The safety profile after 4 yr was similar to that observed after 3 yr. Raloxifene 60 and 120 mg/d through 4 yr decreased the cumulative risk of new vertebral fractures in postmenopausal women with osteoporosis. The decreased vertebral fracture risk in yr 4 alone was not different from that observed in the first 3 yr.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".