Role of Radiographic Fibrosis Extent in Identifying Immunomodulatory Treatment Response in Hypersensitivity Pneumonitis
Bibliographic record
Abstract
BACKGROUND: Treatment selection in chronic hypersensitivity pneumonitis (HP) remains empiric because of a lack of randomized trial data. Although radiographic fibrosis extent often is used to inform treatment decisions, its usefulness as a theragnostic marker for immunomodulatory therapy is unknown. RESEARCH QUESTION: Is visual fibrosis extent on high-resolution CT (HRCT) imaging associated with differential pulmonary function response to immunomodulation in chronic HP? STUDY DESIGN AND METHODS: This retrospective cohort study included 108 patients with HP from 2 interstitial lung disease (ILD) referral centers who received ≥ 3 months of immunomodulatory therapy (prednisone, azathioprine, mycophenolate mofetil, and rituximab) and had undergone pulmonary function testing and HRCT imaging before and after treatment. Fibrosis extent was classified as ≥ 10% or < 10% based on masked radiologist reads. Linear spline mixed-effects models were used to estimate FVC and diffusion capacity of the lungs for carbon monoxide (Dlco) % predicted trajectory before and after immunomodulation, with patients serving as their own controls. The primary analysis evaluated whether fibrosis extent modified the association between immunomodulation and lung function trajectory. RESULTS: Overall, immunomodulation was associated with a modest FVC improvement at 12 months (+2.63%; 95% CI, 0.72-4.54; P < .01). Among patients with < 10% fibrosis, immunomodulation was associated with improvements in both FVC (+5.83%; P < .01) and Dlco (+13.9%; P < .01). In contrast, no improvement in FVC (+0.81%; P = .42) or Dlco (-4.3%; P = .17) was observed in patients with ≥ 10% fibrosis at 12 months. Baseline demographics, smoking history, and antigen identification status were similar between fibrosis groups. INTERPRETATION: The results of this study indicate that visual fibrosis extent is associated with differential pulmonary function response to immunomodulatory therapy in chronic HP. Patients with limited fibrosis demonstrated improved pulmonary function compared with those with greater radiographic fibrosis. These findings may support the use of fibrosis extent as a clinical tool for treatment stratification and highlight the need for prospective trials to validate radiographic markers in guiding HP management.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".