PRospective phenotypIng and Multi-omic Endotyping of Progressive Pulmonary Fibrosis

Overview

This is a prospective, observational cohort study. Participants with non-idiopatic pulmonary fibrosis, interstitial lung disease (ILD) will be followed for 24 months to systematically collect clinical, imaging, and biospecimen data. The primary objective is to optimize progressive pulmonary fibrosis (PPF) classification and establish PPF incidence for key ILD subtypes. Additional exploratory objectives are to 1) Prospectively validate a novel PPF classifier and assess performance durability over time, and 2) Determine whether multi-dimensional PPF prediction outperforms component approaches.

This is a prospective, cohort study with no study investigational therapy prescribed. Patients with non-idiopathic pulmonary fibrosis (non-IPF) fibrosing ILD, including connective tissue disease associated ILD (CTD-ILD), fibrotic hypersensitivity pneumonitis (fHP) and non-IPF idiopathic interstitial pneumonia (IIP) will be recruited. Consented participants with non-IPF ILD will be carefully phenotyped with extensive clinical, physiological, and imaging data. After confirmation of eligibility, participants will undergo protocolized follow-up over 24 months. Clinical data and blood biospecimens will be collected at protocolized time points throughout the study. The primary outcome is 12-month transplant-free survival (TFS), following a 12-month observation period with TFS defined as the time from 12-month PFT to death, lung transplant or censoring at 12 months or earlier if lost to follow-up. This research will determine whether a ≥10% relative decline in FVC occurring during the 12-month observation period is associated with TFS over the subsequent 12 months. The investigators will then explore other proposed PPF criteria using the same approach. Additionally, the investigators will determine test performance characteristics of a novel proteomic biomarker for predicting PPF at 12 months and compare performance of this classifier to a multi-dimensional approach that incorporates clinical data and quantitative CT data.

Conditions