Back pain in patients with severe osteoporosis on teriparatide or antiresorptives: a prospective observational study in a multiethnic population
Bibliographic record
Abstract
INTRODUCTION: We evaluated reduced back pain in a multiethnic population treated with teriparatide and/or antiresorptives in real-life clinical settings over 12 months. METHODS: This prospective observational study comprised 562 men and postmenopausal women (mean age 68.8 years) receiving either teriparatide (n = 230), antiresorptives (raloxifene or bisphosphonates; n = 322), or both (n = 10) for severe osteoporosis. The primary endpoint was the relative risk of new/worsening back pain at six months. RESULTS: At baseline, a higher proportion of teriparatide-treated than antiresorptive-treated patients had severe back pain (30.9% vs. 17.7%), extreme pain/discomfort (25.3% vs. 16.8%), extreme anxiety/depression (16.6% vs. 7.8%) and were confined to bed (10.0% vs. 5.3%). Teriparatide-treated patients had higher visual analog scale (VAS) scores for pain (5.8 ± 2.42 vs. 5.1 ± 2.58) and lower mean European Quality of Life-5 Dimensions (EQ-5D) scores (37.7 ± 29.15 vs. 45.5 ± 31.42) than antiresorptive-treated patients. The incidence of new/worsening back pain at six months for patients on teriparatide and antiresorptives was 9.8% and 10.3% (relative risk 0.99, 95% confidence interval 0.80-1.23), respectively. The incidence of severe back pain at 12 months was 1.3% and 1.6% in the teriparatide and antiresorptive treatment groups, respectively. Teriparatide-treated patients had lower mean VAS (2.71 ± 2.21 vs. 3.30 ± 2.37) and EQ‑5D (46.1 ± 33.18 vs. 55.4 ± 32.65) scores at 12 months. More teriparatide-treated patients felt better (82.7% vs. 71.0%) and were very satisfied with treatment (49.4% vs. 36.8%) compared to antiresorptive-treated patients. CONCLUSION: Patients treated with either teriparatide or antiresorptives had similar risk of new/worsening back pain at six months.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".