Meta-Analyses of Therapies for Postmenopausal Osteoporosis
Bibliographic record
Abstract
The availability of new therapeutic agents has made clinical decision-making in osteoporosis more complex.Because individual clinicians cannot systematically collect and assimilate all the evidence bearing on the efficacy of osteoporosis therapies, they require summaries for evidence-based decision-making.Systematic reviews using rigorous methods provide an unbiased, comprehensive summary of the available evidence, and meta-analysis provides the most precise possible estimate of the treatment effect.The articles in this series represent systematic reviews of a number of osteoporosis therapies: calcium and vitamin D, the bisphosphonates alendronate and risedronate, hormone replacement therapy, raloxifene, and calcitonin.We used state-of-the-art methodology to provide the most clear and accurate characterization of the effectiveness of these therapies.These include explicit eligibility criteria; a comprehensive search; validity assessment that focused on concealment of randomization, blinding, and completeness of follow-up; and sophisticated analytic methods.In addition, two or more reviewers made independent, reproducible decisions regarding study inclusion and assessments of study validity.Only alendronate and risedronate reduced the risk of both nonvertebral and vertebral fractures.Other agents that reduced vertebral fracture included raloxifene, etidronate, vitamin D, and calcitonin.Clinicians should consider these results when selecting antiosteoporosis therapies for postmenopausal women.(Endocrine Reviews 23: 496 -507, 2002) Series Outline I. Systematic Reviews of Randomized Trials in Osteoporosis: Introduction and Methodology A. Introduction B. The importance of osteoporosis C. Problems of a world without systematic reviews D. What is a systematic review?E. Eligibility criteria for these reviews: defining the questions F. Background of the group G. Methodology H. Strengths and limitations of our meta-analyses I. Conclusions J. Acknowledgments K. Bibliography II.Meta-Analysis of Alendronate for the Treatment of Postmenopausal Women A. Abstract B. Background C. Methods D. Results
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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 | 0.018 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.032 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".