Background Idiopathic pulmonary fibrosis (IPF) is characterized 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. Methods Plasma from 1280 IPF patients in ISABELA 1 and 2 (NCT03711162, NCT03733444) was analysed for 17 circulating soluble disease-related biomarkers at multiple timepoints and for the MUC5B (rs35705950T) 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. Results 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 rs35705950T genotype predicted neither mortality nor disease progression. Conclusions 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.
Randall et al. (Thu,) studied this question.