Anti-SAE autoantibody in dermatomyositis: original comparative study and review of the literature
Bibliographic record
Abstract
OBJECTIVE: Among specific autoantibodies in DM, the anti-small ubiquitin-like modifier activating enzyme (SAE) antibody is rare. We aim to describe the clinical characteristics, cancer prevalence, and muscle pathology of anti-SAE-positive DM. METHODS: Patients with a diagnosis of DM and sera positive for the anti-SAE antibody were recruited from 19 centres in this retrospective observational study. The available muscular biopsies were reviewed. We conducted a comparison with anti-SAE-negative DM and a review of the literature. RESULTS: Of the patients in the study (n = 49), 84% were women. Skin involvement was typical in 96% of patients, with 10% having calcinosis, 18% ulceration and 12% necrosis; 35% presented with a widespread skin rash. Muscular disease affected 84% of patients, with mild weakness [Medical Research Council (MRC) scale 4 (3, 5)], although 39% of patients had dysphagia. Muscular biopsies showed typical DM lesions. Interstitial lung disease was found in 21% of patients, mainly with organizing pneumonia pattern, and 26% of patients showed dyspnoea. Cancer-associated myositis was diagnosed in 16% of patients and was responsible for the majority of deaths, its prevalence being five times that of the general population. IVIG therapy was administered to 51% of the patients during the course of the disease. Comparison with anti-SAE-negative DM (n = 85) showed less and milder muscle weakness (P = 0.02 and P = 0.006, respectively), lower creatinine kinase levels (P < 0.0001) and less dyspnoea (P = 0.003). CONCLUSION: Anti-SAE positive DM is a rare subgroup associated with typical skin features but a potentially diffuse rash, a mild myopathy. Interstitial lung disease defines an organizing pneumonia pattern. Cancer associated DM prevalence is five times that of the general population. TRIAL REGISTRATION: ClinicalTrials.gov, http://clinicaltrials.gov, NCT04637672.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".