Pre‐Treatment <scp>MMP7</scp> Predicts Progressive Idiopathic Pulmonary Fibrosis in Antifibrotic Treated Patients
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with a poor prognosis. Antifibrotics slow the decline of pulmonary function after 12-months, but limited studies have examined the role of circulatory biomarkers in antifibrotic treated IPF patients. METHODS: Serum from 98 IPF participants, from the Australian Idiopathic Pulmonary Fibrosis Registry were collected at four time-points over 1 year post-antifibrotic treatment and analysed as two separate cohorts. Patients were stratified as progressive, if they experienced ≥ 10% decline in FVC or ≥ 15% decline in DLCO or were deceased within 1 year of treatment initiation: or otherwise as stable. Ten molecules of interest were measured by ELISAs in patient serum. RESULTS: Baseline MMP7 levels were higher in progressive than stable patients in Cohort 1 (p = 0.02) and Cohort 2 (p = 0.0002). Baseline MMP7 levels also best differentiated progressive from stable patients (Cohort 1, AUC = 0.74, p = 0.02; Cohort 2, AUC = 0.81, p = 0.0003). Regression analysis of the combined cohort showed that elevated MMP7 levels predicted 12-month progression (OR = 1.530, p = 0.010) and increased risk of overall mortality (HR = 1.268, p = 0.002). LASSO regression identified a multi-biomarker panel (MMP7, ICAM-1, CHI3L1, CA125) that differentiated progression more accurately than MMP7 alone. Furthermore, GAP combined with MMP7, ICAM-1, CCL18 and SP-D was more predictive of 3-year mortality than GAP alone. CONCLUSION: MMP7 along with a multi-biomarker and GAP panel can predict IPF progression and mortality, with the potential for optimising management.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".