Clinical relevance of rheumatoid factor and anti‐citrullinated peptides in fibrotic interstitial lung disease
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Rheumatoid arthritis (RA) is a frequent cause of interstitial lung disease (ILD); however, the impact of rheumatoid factor and anti-citrullinated peptide antibody seropositivity in ILD without connective tissue disease (CTD) is unclear. We examined the association of seropositivity with ILD progression, mortality and response to immunosuppression in non-CTD ILD. METHODS: A total of 1570 non-CTD patients (with idiopathic pulmonary fibrosis, hypersensitivity pneumonitis, interstitial pneumonia with autoimmune features or unclassifiable ILD) and 181 RA-ILD patients were included from a prospective registry. Longitudinal forced vital capacity (FVC), transplant-free survival and incidence of progressive fibrosing-ILD (PF-ILD) were compared between seronegative non-CTD ILD (reference group), seropositive non-CTD ILD and RA-ILD using linear mixed-effect and Cox proportional hazards models adjusted for age, sex, smoking pack-years and baseline FVC. Interaction between seropositivity and immunosuppression on FVC decline was assessed in patients with ≥6 months of follow-up before and after the treatment. RESULTS: Two hundred and seventeen (13.8%) patients with seropositive non-CTD ILD had similar rates of FVC decline and transplant-free survival compared to seronegative non-CTD ILD, but more frequently met the criteria for PF-ILD (hazard ratio [HR] = 1.35, p = 0.004). RA-ILD had slower FVC decline (p = 0.03), less PF-ILD (HR = 0.75, p = 0.03) and lower likelihood of lung transplant or death (HR = 0.66, p = 0.01) compared to seronegative non-CTD ILD. No interaction was found between seropositivity and treatment on FVC decline in non-CTD ILD. CONCLUSION: Seropositivity in non-CTD ILD was not associated with improved outcomes or treatment response, highlighting the importance of other disease features in determining prognosis and predicting response to immunosuppression.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".