Etanercept Increases Bone Mineral Density in Ankylosing Spondylitis, but Does Not Prevent Vertebral Fractures: Results of a Prospective Observational Cohort Study
Bibliographic record
Abstract
OBJECTIVE: Ankylosing spondylitis (AS) is characterized by chronic inflammation leading to ankylosis, but also to low bone mineral density (BMD) and vertebral fractures (VFx). Treatment with tumor necrosis factor-α blockers decreases inflammation and has shown to be effective in increasing BMD. We studied the effects of etanercept (ETN) on BMD and VFx in patients with AS after 2 years of treatment. Further, we studied changes in bone turnover markers and radiological damage. METHODS: Patients with active AS, treated with ETN for 2 years, were included. BMD lumbar spine and hip were measured at baseline and after 2 years, as well as radiological damage (modified Stoke Ankylosing Spondylitis Spinal Score with the addition of the thoracic spine), VFx (Genant method), and change in bone turnover markers. RESULTS: Forty-nine patients with AS were included. After 2 years of ETN, hip BMD increased by 2.2% (p = 0.014) and lumbar spine BMD by 7.0% (p < 0.001). The Bath Ankylosing Spondylitis Disease Activity Index decreased significantly (p < 0.001), as well as C-reactive protein and erythrocyte sedimentation rate (p < 0.001). Despite ETN therapy, the number of patients with VFx more than doubled (from 6 to 15 patients, p = 0.003). Also, the radiological damage increased significantly over time (from 12.1 to 18.5, p < 0.001); however, no significant change in bone turnover markers was found. CONCLUSION: This prospective longitudinal observational cohort study showed that after 2 years of ETN, BMD of the hip and spine increased significantly, but the number of patients with VFx and the severity of VFx increased as well. Besides that, radiological progression, including the thoracic spine, increased significantly. Thus, the favorable bone-preserving effect is accompanied by unfavorable outcomes on VFx and radiological damage.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".