Tumor Necrosis Factor-α Blockers in SAPHO Syndrome: Table 1.
Bibliographic record
Abstract
OBJECTIVE: To analyze the clinical efficacy of anti-tumor necrosis factor-alpha (TNF-alpha) therapy in treatment of synovitis, acne, pustulosis, hyperostosis, osteitis (SAPHO) syndrome, we describe cases of refractory SAPHO syndrome and review cases treated with anti-TNF-alpha reported in the literature. METHODS: We describe 6 cases of patients with SAPHO syndrome treated with anti-TNF-alpha between 2004 and 2008. Therapeutic response was evaluated according to improvement in pain score, amelioration of disease activity, and improvement in function. The efficacy of treatment was considered to be reduced need for analgesics and/or antiinflammatory therapy. RESULTS: In our series, 4 patients received infliximab, 1 etanercept, and 1 adalimumab. These treatments brought clinical response in 4 patients (66.6%): response was sustained with infliximab in 1 case for 7 months; with adalimumab in another case for 22 months; and with etanercept in 2 cases for 1 and 42 months, respectively. In contrast, 2 other patients showed no response to infliximab. Improvement was initially temporary after infusions 1 and 2, then pain recurred at Week 14. Skin lesions were healed in 3 of 4 cases, but recurred or worsened in 2 cases, after infusion 2 of infliximab. Treatment was generally well tolerated. Paradoxical psoriasis was noted in 2 cases and urticaria in 1. CONCLUSION: Given our results and those from the literature, TNF-alpha blockers should be considered in the therapeutic strategy of refractory cases of SAPHO syndrome, despite their effect seeming less impressive than in other spondyloarthropathies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".