Veracyte presented data at the recent American Thoracic Society (ATS) 2016 International Conference from a study proving the potential of its Envisia classifier to improve the diagnosis of interstitial lung diseases, including idiopathic pulmonary fibrosis (IPF), when compared only to high-resolution CT (HRCT) imaging.
Further results from three additional studies demonstrated the potential of the Envisia classifier to address challenges that presently delay an accurate and timely diagnosis of the disease.
IPF is a chronic and ultimately fatal disease characterized by a progressive decline in lung function. The term “pulmonary fibrosis” means scarring of lung tissue. It is the leading cause of worsening dyspnea (shortness of breath).
IPF belongs to a large group of more than 200 lung diseases known as interstitial lung diseases (ILDs), that affect lung interstitium, the tissue between the air sacs in the lung. The disorders also frequently affect lung airspaces, peripheral airways, and vessels. Lung tissue from people with IPF shows a histopathologic pattern known as usual interstitial pneumonia (UIP). UIP is the pathologic counterpart of IPF.
In the first study presented, researchers showed a new prototype genomic classifier which was developed using 211 samples from 59 patients through less-invasive transbronchial biopsy (TBB). The classifier uses deep RNA sequencing to differentiate the presence of UIP from samples without UIP.
In experiments that involved 35 patients who each had up to five TBB samples, the new classifier was able to identify the samples as UIP from 20 patients with a UIP pattern, compared to HRCT which was only able to identify 5 of 19 patients with an UIP histopathologic pattern.
“Physicians traditionally use HRCT imaging to diagnose IPF, but results can be ambiguous and surgical lung biopsy (SLB) is often needed to obtain a more definitive diagnosis,” said study author Giulia C. Kennedy in a press release. “These findings are significant because they suggest that the Envisia classifier may potentially help improve IPF diagnosis and reduce the need for surgery in patients with suspected ILD. This is particularly important because these patients are often too frail to undergo such an invasive procedure.”
Results from the second study demonstrated the potential for the Envisia classifier to improve clinical decision-making in IPF diagnosis. Results from 96 biopsy samples from 56 patients with suspected ILD, revealed that pathologists missed over one third of IPF cases, compared to expert pathology identification of UIP.
Kennedy, Veracyte’s scientific officer who presented the data at ATS 2016, said IPF diagnosis can be challenging for physicians in all types of settings.
“However, in this study, community-based pathologists missed a substantial number of IPF diagnoses compared to experts who specialize in diagnosing the disease, potentially impacting treatment for patients diagnosed at the local level,” Kennedy said. “This suggests that a diagnostic tool with high sensitivity for UIP could be particularly helpful to physicians who do not have access to expert pathology review.”
In a third study, a team from The University of Michigan and Weill Cornell Medical College presented the results of a physician survey indicating the potential of the genomic classifier in reducing the need of invasive diagnostic procedures and in increasing proper IPF treatment.
In a fourth presentation, researchers from the Pulmonary Fibrosis Foundation presented the results of a Veracyte funded survey of patients with a diagnosis of IPF or another ILD, to access the rate misdiagnoses, diagnostic delays, and often invasive diagnostic procedures.
“We believe that the Envisia classifier will help transform care among the hundreds of thousands of patients who present each year with a suspected ILD,” said Bonnie Anderson, president and chief executive officer of Veracyte. “A growing body of data suggests that Envisia has the potential to both reduce the time required for patients to receive an accurate diagnosis and to reduce the number of patients who must undergo risky, invasive surgeries to obtain such a diagnosis.”
Veracyte is planning to launch the Envisia classifier later this year.
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