Veracyte Announces New Data Demonstrating That Envisia Genomic Classifier Improves IPF Diagnosis
Results From Three Studies Presented at CHEST 2019 Suggest Test Increases Physicians’ Confidence in Diagnosis and Can Reduce the Need for Invasive, Risky Procedures
“The new Envisia classifier data being presented at CHEST add to the growing body of evidence showing that the test complements HRCT and clinical factors for a more confident diagnosis,” said
Each year in
The Envisia classifier is the first commercially available test that helps distinguish IPF from other ILDs, without the need for risky surgery.
Data being presented for the first time at CHEST 2019 consistently demonstrate that the Envisia classifier is a valuable complement to HRCT in the diagnosis of ILDs and IPF.
Sadia Benzaquen, M.D., chair of Pulmonary/Critical Care at Einstein Healthcare Network, will share data today which show that adding Envisia classifier results to HRCT identified twice as many UIP patients as HRCT alone (Abstract #4060). Using scans from 46 patients, researchers evaluated the diagnostic performance of HRCT when combined with the Envisia classifier, both among central and local radiology teams. Among the central radiology teams in this study, combined classifier and HRCT results identified true UIP in 8 additional patients (17 vs. 9 with HRCT alone), with a joint sensitivity of 81 percent and specificity of 88 percent. When coupled with local radiology, combined classifier and HRCT results identified true UIP in 7 additional patients (21 vs. 14 with HRCT alone), substantially improving sensitivity (95 percent vs. 64 percent with local HRCT alone), while maintaining HRCT specificity of 71 percent.
Findings from a study presented by
Jonathan Chung, M.D., of The University of Chicago Medicine, further validate the Envisia classifier’s ability to enhance physician confidence in IPF diagnosis, with high concordance to multidisciplinary review teams (MDDs) informed by histopathology (Abstract #4010). In this study, two MDDs were asked to make an IPF or non-IPF diagnosis for 94 patients enrolled in the BRAVE (Bronchial Sample Collection for a Novel Genomic Test) trial. Researchers found a high (>86 percent) concordance between IPF and non-IPF diagnoses made by MDDs using the Envisia classifier as compared to surgical histopathology results. This concordance was even higher (90 percent) among patients who had HRCT results that were inconsistent with UIP. Among patients diagnosed with IPF by both MDDs (n=17), the use of the Envisia classifier significantly improved the confidence of an IPF diagnosis (94 percent confidence with the classifier vs. 53 percent with histopathology; p=0.02).
Finally, data that will be presented on
Tuesday, Oct. 22from an independent study conducted at Tulane Universityalso show that adding Envisia classifier results to HRCT findings significantly improves physicians’ confidence in IPF diagnosis (Abstract #4805). Investigators shared test results from 24 patients who were inconclusive for UIP following HRCT with two MDDs: The first sequentially reviewed clinical and HRCT findings, followed by results from cryobiopsy (a diagnostic procedure that is sometimes conducted during bronchoscopy) and then, the Envisia classifier. The second reviewed results from the Envisia test first, followed by cryobiopsy results. Among the first MDD, adding Envisia test results to cryobiopsy pathology findings significantly increased physicians’ confidence in making an IPF diagnosis (from 36 percent to 71 percent p=0.03). The overall agreement between the Envisia classifier and the first and second MDD diagnosis for UIP was 96 percent and 88 percent, respectively.
“The diagnosis of IPF often remains a challenge for physicians and patients, particularly given the risk involved with invasive diagnostic procedures and the urgency of getting patients onto appropriate treatment in order to slow disease progression,” said
The Envisia Genomic Classifier is the first commercially available test to improve the diagnosis of idiopathic pulmonary fibrosis (IPF). The genomic test enables physicians to more confidently differentiate IPF from other interstitial lung diseases (ILDs), helping to guide an optimal patient treatment plan that can improve outcomes and reduce risk. The Envisia classifier was developed using RNA whole-transcriptome sequencing and machine learning to identify the usual interstitial pneumonia (UIP) pattern, which is a hallmark of IPF. The test assesses patient samples obtained through bronchoscopy, a nonsurgical procedure commonly used in lung evaluation, and is used as a complement to high-resolution computed tomography (HRCT). The Envisia classifier is proven to detect UIP with high correlation to the gold standard – histopathology results read by ILD experts – without the need for surgery.
Cautionary Note Regarding Forward-Looking Statements
This press release contains "forward-looking statements" within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements can be identified by words such as: "anticipate," "intend," "plan," "expect," "believe," "should," "may," "will" and similar references to future periods. Examples of forward-looking statements include, among others, the ability of Envisia to improve IPF diagnosis and to reduce surgeries. Forward-looking statements are neither historical facts nor assurances of future performance, but are based only on our current beliefs, expectations and assumptions. These statements involve risks and uncertainties, which could cause actual results to differ materially from our predictions, and include, but are not limited to: our ability to achieve milestones under the collaboration agreement with
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