Head-to-head comparisons of bisphosphonates and teriparatide in osteoporosis: a meta-analysis
Bibliographic record
Abstract
PURPOSE: This meta-analysis aimed to compare the efficacy and safety of teriparatide vs. bisphosphonates in the management of osteoporosis. METHODS: A total of 1,967 patients from eight randomized controlled trials were analyzed; outcomes included bone mineral density (BMD) of the femoral neck, total hip and lumbar spine, vertebral and nonvertebral fractures and any adverse event. A subgroup analysis of treatment effectiveness was performed according to the etiology of osteoporosis; i.e., glucocorticoid-induced osteoporosis (GIO) vs. post-menopausal osteoporosis (PO). RESULTS: Teriparatide increased the BMD of the lumbar spine, femoral neck and total hip to a greater extent than bisphosphonates. Patients treated with teriparatide also had a lower risk of vertebral fractures compared with bisphosphonates; however, no difference in risk of nonvertebral fractures (or adverse events) was found. GIO subgroups showed larger increases in BMD of the lumbar spine, total hip and femoral neck in patients treated with teriparatide compared with bisphosphonates. The PO subgroup showed larger increases in BMD of the lumbar spine in patients treated with teriparatide compared with bisphosphonates. Patients in the GIO subgroup (but not the PO subgroup) were less likely to suffer a vertebral fracture on teriparatide as compared with bisphosphonates. In contrast, no significant difference in the percentage of nonvertebral fractures was noted between the two types of treatment for either subgroup. CONCLUSION: Teriparatide significantly increased the BMD of lumbar spine, total hip and femoral neck, particularly in GIO-induced osteoporosis. Teriparatide did not lower the risk of nonvertebral fractures when compared with bisphosphonates.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.051 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".