A new study by Veracyte and collaborators demonstrates that the company’s Envisia genomic test can improve the diagnosis of patients being evaluated for interstitial lung disease.
The study, published this week in Lancet Respiratory Medicine, includes both clinical validation and clinical utility data from a subset of patients who are part of an ongoing prospective 29-site study known as BRAVE (Bronchial Sample Collection for a Novel Genomic Test).
Veracyte funded the study and had a role in the design, data collection, analysis, and interpretation.
For the study, the company’s clinical collaborators recruited 237 individuals from the BRAVE trial who were being evaluated for interstitial lung disease. They used RNA sequencing data from transbronchial lung biopsy samples from 90 patients to train a machine learning algorithm to identify a pattern for usual interstitial pneumonia (UIP), which is required for diagnosing idiopathic pulmonary fibrosis, a deadly but common subtype of interstitial lung disease that is difficult to diagnose.
After training the algorithm, the team tested it on a different set of 49 patients, achieving 88 percent specificity and 70 percent sensitivity for identifying UIP. The positive predictive value was 84 percent, while the negative predictive value was 77 percent.
"IPF is often challenging to distinguish from other [interstitial lung disease], but timely and accurate diagnosis is critical so that patients with IPF can access therapies that may slow progression of the disease, while avoiding potentially harmful treatments," Ganesh Raghu, director of the Center for Interstitial Lung Diseases at the University of Washington and lead author of the publication, said in a statement. The study shows that physicians may be able to use Veracyte’s Envisia assay along with clinical and radiological information "as a diagnostic tool to make a more informed and confident diagnosis," he added.
Go back
