Systematic Review and Metaanalysis of Pharmacological Interventions in Adult-Onset Still Disease and the Role of Biologic Disease-Modifying Antirheumatic Drugs
Bibliographic record
Abstract
Objective To conduct a systematic review of the effectiveness and safety of pharmacological treatments for adult-onset Still disease (AOSD). Methods Six databases, 2 trial registries, and conference abstracts were searched from January 2012 to February 2023 for studies of pharmacological interventions in people with AOSD. Outcomes were rates of remission and response, discontinuation of concurrent treatments, complications of AOSD, and treatment-related adverse events. Risk of bias was assessed with the Cochrane risk of bias tool and the Joanna Briggs Institute tool for case series. Results Forty-four studies evaluated treatments, including nonsteroidal antiinflammatory drugs (NSAIDs), corticosteroids (CS), conventional synthetic disease-modifying antirheumatic drugs (DMARDs), and biologic DMARDs (bDMARDs). For bDMARDs, tocilizumab (TCZ), anakinra (ANK), and canakinumab (CNK) had the most available data. Although 3 randomized controlled trials did not show statistically significant benefits of bDMARDs, metaanalyses showed high rates of complete remission and CS discontinuation. Complete remission was 80% (95% CI 59-92%, I 2 36%), 73% (95% CI 58-84%, I 2 66%), and 77% (95% CI 29-97%, I 2 82%) and CS discontinuation was 57% (95% CI 29-81%, I 2 66%), 47% (95% CI 18-78%, I 2 79%), and 34% (95% CI 6-81%, I 2 59%), respectively, for TCZ, ANK, and CNK. Studies with a higher proportion of patients previously treated with bDMARDs showed a trend toward lower rates of CS discontinuation ( P = 0.05). The analyses had high clinical heterogeneity, largely because treatments were prescribed as different lines of therapy. Conclusion Evidence supports TCZ, ANK, and CNK therapy for AOSD. However, the magnitude of effect and comparative effectiveness of treatments is uncertain.
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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 | 0.031 | 0.070 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.031 | 0.036 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".