Veracyte Announces New Clinical Utility Data Suggesting Envisia Genomic Classifier Enables as Confident a Diagnosis in IPF as Surgical Pathology
- Interim CATALYST Study Findings Presented at PFF Summit -
In the interim report from the CATALYST clinical utility study, researchers found that two central MDTs - each comprised of a pulmonologist, radiologist and pathologist - diagnosed patients with suspected IPF similarly (92 percent agreement) when they were randomly assigned to review either the patients' surgical pathology or Envisia classifier results, along with clinical information and high-resolution computed tomography (HRCT). The study also showed that the Envisia classifier enabled the MDTs to agree on a diagnosis (94 percent agreement) based on Envisia classifier results, even when surgical pathology results were inconclusive. The findings are from a retrospective analysis involving 71 patients who were evaluated for potential IPF using HRCT, surgical pathology and genomic testing with the Envisia classifier.
"These findings signal a real potential for a shift in the current
diagnostic evaluation of patients undergoing evaluation for ILD," said
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About the Envisia Genomic Classifier
The Envisia Genomic Classifier is designed to improve physicians' ability to differentiate IPF from other ILDs without the need for surgery. The 190-gene classifier uses machine learning coupled with powerful, deep RNA sequencing to detect the presence or absence of usual interstitial pneumonia (UIP), a classic diagnostic pattern whose presence is essential for the diagnosis of IPF, using patient samples obtained through less-invasive transbronchial biopsy.
Cautionary Note Regarding Forward-Looking Statements
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