Antifibrillarin Antibodies Are Associated with Native North American Ethnicity and Poorer Survival in Systemic Sclerosis
Bibliographic record
Abstract
OBJECTIVE: To examine the clinical correlates and survival in patients with antifibrillarin antibodies (AFA) in a large international study population consisting of well-characterized systemic sclerosis (SSc) cohorts from Canada, Australia, and the United States. METHODS: Baseline clinical data from the prospective cohorts (Canadian Scleroderma Research Group, the Australian Scleroderma Cohort Study, and the American Genetics versus Environment in Scleroderma Outcome Study) were investigated. Clinical variables were harmonized and sera were tested for AFA using a commercially available SSc profile line immunoassay, regardless of the immunofluorescence staining pattern. Association of demographic and clinical features with AFA was investigated by logistic or linear regression. Further, a survival analysis was performed by Cox regression analysis. RESULTS: A total of 1506 patients with SSc with complete serological profiles were included in the study. Fifty-two patients (3.5%) had antibodies detected against fibrillarin. Patients of African descent and Native North American ethnicity were more likely to be AFA-positive compared with other ethnicities. After adjustment for demographic factors, diffuse involvement, and intestinal bacterial overgrowth requiring antibiotics, gastrointestinal reflux disease showed a trend for association with AFA. Further, AFA positivity was associated with shorter survival independently of demographic factors and disease type (HR 1.76, 95% CI 1.11-2.79, p = 0.016). CONCLUSION: In this large multinational SSc cohort, AFA was associated with Native American ethnicity and was an independent predictor of mortality.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".