Real-world Clinical Data Back Envisia Genomic Classifier’s Potential for IPF Diagnoses


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The diagnostic potential of the Envisia Genomic Classifier to distinguish idiopathic pulmonary fibrosis (IPF) from other interstitial lung diseases (ILDs) has once again been demonstrated, this time with data collected in real-world clinical settings.

The test, developed by Veracyte, helped improve the accuracy and effectiveness of IPF diagnoses by central multidisciplinary clinical teams without the need for invasive, expensive, and risky surgical procedures.

“These findings signal a real potential for a shift in the current diagnostic evaluation of patients undergoing evaluation for ILD,” Neil M. Barth, MD, chief medical officer of Veracyte, said in a press release.

The preliminary results were the subject of a presentation titled, “The CATALYST Study: A Clinical Utility Analysis of the BRAVE (Bronchial Sample Collection for A Novel Genomic Test) Registry, using the Envisia Genomic Classifier,” delivered at the Pulmonary Fibrosis Foundation (PFF) Summit 2017 in Nashville, Nov. 9-11.

The Envisia Genomic Classifier was designed to help clinicians differentiate between IPF and other lung diseases. Usually, IPF diagnosis requires surgery, but with this new approach, it is possible to recognize the disease based on genetic data.

The test analyzes the RNA sequence of 190 genes to detect the presence or absence of usual interstitial pneumonia (UIP), a classic diagnostic pattern that is essential for the diagnosis of IPF. To perform this analysis, small lung tissue samples are collected via bronchoscopy, a method that is less-invasive than surgery.

Results of a study published in the Annals of the American Thoracic Society showed that this new test could effectively distinguish patients who had UIP from those who did not. This diagnostic capacity was found to be even more accurate than currently used diagnostic methods.

The Envisia Genomic Classifier is currently being tested in real-world clinical scenarios in the CATALYST clinical study. The study includes common diagnostic information collected from 71 patients who had been evaluated for potential IPF, namely high-resolution computed tomography (HRCT) images, lung tissue analysis via surgery, and gene analysis with the Envisia classifier.

Two central multidisciplinary teams, each of them including a pulmonologist, a radiologist, and a pathologist, analyzed all of the data to reach a final diagnosis.

Preliminary data showed that when assigned to randomly evaluate the cases, the teams had a similar response to suspecting IPF in 92% of the cases. Use of data collected by the Envisia classifier was found to allow the teams to agree on a diagnosis in 94% of the cases, even when surgical data was inconclusive.

“Prior to the introduction of the Envisia classifier, clinicians and patients were limited to surgery for confirming a diagnosis of IPF, if the HRCT was inconclusive. Many patients are not willing or medically eligible to undergo such an invasive procedure,” Barth said. “Envisia has now been shown to enable as confident a diagnosis in IPF as surgical pathology. This removes many of the previous barriers to achieving a timely and accurate diagnosis.”