Prognostic biomarkers for idiopathic pulmonary fibrosis: findings from ISABELA clinical trials.

Authors

Matthew J Randall, Claus A Andersen, Kevin K Brown, Simon de Bernard, Paul Ford, Naftali Kaminski, Michael Kreuter, Sharlene Lim, Toby M Maher, Niyati Prasad, Antje Prasse, Philippe Pujuguet, Vincenzo Teneggi, Bernt van den Blink, Louise V Wain, Timothy R Watkins, Wim Wuyts, Yasmina Bauer

Published in

ERJ open research. Volume 12. Issue 1. Epub Feb 16, 2026.

Abstract

Idiopathic pulmonary fibrosis (IPF) is characterised by progressive loss of pulmonary function and poor survival. Although biomarkers for disease progression and mortality exist, their reliability in large studies remains unproven. This study investigates prognostic biomarkers from the ISABELA trials, the largest IPF cohort to date, to identify those predicting worse clinical outcomes.
Plasma from 1280 IPF patients in ISABELA 1 and 2 (NCT03711162, NCT03733444) was analysed for 17 circulating soluble disease-related biomarkers at multiple time-points and for the MUC5B (rs35705950_T) genotype. Statistical learning algorithms investigated biomarker levels/status with disease progression (≥10% decline in forced vital capacity (FVC) or mortality within 1 year) and pharmacotherapy.
Patients with ≥10% annual decline in FVC had higher median baseline of matrix metalloproteinase-7 (MMP-7) versus those with <10% decline (5.5 versus 4.2 µg·L^-1; p<0.005). Patients with baseline MMP-7 ≥5.2 μg·L^-1 and/or C-C motif chemokine ligand 18 (CCL18) ≥75.2 μg·L^-1 had increased risk of mortality (p<0.0001); with patients having both elevated biomarkers at an even greater risk. Machine learning identified CCL18 changes by week 26 as a predictor of disease progression. The rs35705950_T genotype predicted neither mortality nor disease progression.
We provide new insights into the prognostic value of MMP-7 and CCL18 in identifying high-risk IPF patients in the largest cohort to date. The combination of high baseline MMP-7 and CCL18 levels, along with longitudinal changes in CCL18, has the potential to enhance risk stratification and support efficacy assessment and monitoring in clinical trials.

PMID:
41704719
Bibliographic data and abstract were imported from PubMed on 14 Sep 2026.

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