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Envisia Genomic Classifier can successfully differentiate IPF
10-08-2018
by DDNews Staff  |  Email the author
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SAN FRANCISCO, Calif.—Veracyte, Inc. has confirmed the presentation of data demonstrating that the Envisia Genomic Classifier can help physicians more confidently diagnose interstitial lung disease (ILD), including idiopathic pulmonary fibrosis (IPF), without the need for surgery. The data were shared today in an oral presentation at CHEST 2018, the annual meeting of the American College of Chest Physicians, which is being held October 6 – 10 in San Antonio, Texas.
 
The Envisia Genomic Classifier is the first commercially available test to improve the diagnosis of IPF. The Envisia test enables physicians to more confidently differentiate IPF from other ILD, helping to guide an optimal patient treatment plan that can improve outcomes and reduce risk. The classifier works by harnessing the power of RNA sequencing and machine learning to detect a genomic pattern of usual interstitial pneumonia (UIP), whose presence is required for IPF diagnosis. The Envisia test is proven to detect UIP with high correlation to the gold standard – histopathology results read by ILD experts – without the need for surgery.
 
Using data from a prospective study of 49 patients presenting with new-onset ILD, researchers evaluated samples obtained through nonsurgical transbronchial biopsy to determine the Envisia classifier’s accuracy in detecting UIP. Utilizing histopathology as the reference standard, investigators found that the genomic test shows a specificity of 88 percent and sensitivity of 70 percent for detecting UIP.
 
“An accurate, timely diagnosis of IPF and other ILDs is a major challenge for physicians and patients, but is essential for optimal treatment,” said David Lynch, MB, BCh, Professor of Radiology at National Jewish Health, who presented the findings. “Our data, while based on relatively small numbers, suggest that the Envisia test can provide important information for diagnosis, as a complement to HRCT and clinical findings. This is particularly true among patients whose results are unclear following HRCT imaging.”
 
While high-resolution computed tomography (HRCT) is typically the first step in distinguishing IPF from other ILDs, previous data have shown that up to 50 percent of UIP cases are missed by HRCT alone. Among the 42 cases in the current study with the lowest diagnostic confidence following HRCT – i.e., those without definite or probable UIP – the Envisia classifier provided even more robust results (88 percent specificity and 76 percent sensitivity).
 
“Recent study findings show that patients being evaluated for suspected IPF or other ILDs often endure significant diagnostic delays, misdiagnosis and invasive, costly procedures, which can negatively impact outcomes and increase risk. These new data reinforce the valuable role that the Envisia Genomic Classifier can play in improving IPF diagnosis. They also add to the growing body of evidence supporting the use of our test,” noted Bonnie Anderson, Veracyte’s chairman and chief executive officer.
 
The Envisia classifier is currently available to a limited number of institutions through an Early Access Program. In August 2018, Veracyte received a draft Medicare coverage policy for the Envisia classifier through the MolDx program. The company expects the final policy will go into effect in early 2019 and plans to expand availability of the test in 2019.
 
Code: E10081801

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