Progression of interstitial lung disease after the Envisia Genomic Classifier

Résumé fourni par la source

Background: Interstitial lung disease (ILD) represents a heterogenous group of diseases that have substantial morbidity and mortality. The Envisia Genomic Classifier (EGC) is a test that analyses RNA derived from transbronchial biopsy (TBBx) samples to make a positive or negative genomic usual interstitial pneumonitis (UIP) designation. Our study assesses the ability for the EGC to predict progression of disease, with a longer duration of follow-up than previous studies. Methods: Patients referred for cryobiopsy for outpatient workup of ILD concurrently had TBBx and EGC testing performed. We performed a retrospective analysis to assess differences in progression of disease between EGC-positive and negative patients, applying Kaplan-Meier survival analysis and log-rank tests. Confidence in ILD diagnosis before and after the EGC result was also noted, and the difference in confidence levels was assessed by a Wilcoxon signed-rank test. Results: 1487 median PFS days respectively. EGC-positive patients also had worse progression in the subsets of patients with "indeterminate for UIP" computed tomography (CT) (p=0.0052), "alternative diagnosis" CT (p=0.0144) and non-idiopathic pulmonary fibrosis ILD diagnosis (p=0.0157). Additionally, EGC increased the diagnostic confidence level (p<0.0001). Conclusion: EGC positivity predicts worse ILD progression over a sustained follow-up period. The ability to predict worse prediction early in the ILD course without the need for surgical biopsy would have significant clinical impact.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.