Serum Biomarkers of Pulmonary Damage and Risk for Progression of Rheumatoid Arthritis–Associated Interstitial Lung Disease
Bibliographic record
Abstract
OBJECTIVE: To investigate baseline and change of pulmonary damage biomarkers (serum Krebs von den Lungen 6 [KL-6], human surfactant protein D [hSP-D], and matrix metalloproteinase 7 [MMP-7]) with rheumatoid arthritis-associated interstitial lung disease (RA-ILD) progression. METHODS: In the Korean Rheumatoid Arthritis Interstitial Lung Disease (KORAIL) cohort, a prospective cohort, we enrolled patients with RA and ILD confirmed by chest computed tomography imaging and followed annually. ILD progression was defined as worsening in physiological and radiological domains of the 2022 American Thoracic Society, European Respiratory Society, Japanese Respiratory Society, and Latin American Thoracic Society guideline for progressive pulmonary fibrosis (PPF). Associations between biomarkers and RA-ILD progression were analyzed using multivariable Cox regression, adjusting for potential confounders. RESULTS: We analyzed 136 patients with RA-ILD (mean age 66.5 yrs, 30% male, 60.3% with usual interstitial pneumonia pattern). During a median 3.0 years of follow-up, 47 patients (34.6%) experienced progression. Higher baseline KL-6 and hSP-D levels were associated with higher risk of ILD progression (multivariable hazard ratios [HRs] 1.37 [95% CI 1.03-1.82] and 1.51 [95% CI 1.09-2.08], respectively), whereas only the highest quartile of MMP-7 showed an increased risk (multivariable HR 2.60 [95% CI 1.07-6.33]). Increasing levels of serum KL-6 at 1 year showed the strongest association with progression (∆KL-6: multivariable HR 2.00 [95% CI 1.29-3.11]), additionally adjusting for baseline biomarker levels. CONCLUSION: In this first prospective study to apply PPF criteria to RA-ILD, 34.6% progressed over 3 years. Higher baseline KL-6 and hSP-D were associated with progression. In follow-up, greater change in KL-6 was associated with progression. Serial measurement of pulmonary damage biomarkers may predict RA-ILD progression and may be helpful in monitoring patients and treatment decisions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".