SAN ANTONIO, Texas — bioAffinity Technologies said a new real-world clinical case study demonstrates how its noninvasive CyPath Lung test supported physician decision-making and helped reduce patient anxiety in the assessment of pulmonary nodules in a high-risk patient.
The case involved a 59-year-old patient with a 30-year smoking history of three packs per day and underlying chronic obstructive pulmonary disease. Imaging revealed multiple scattered pulmonary nodules measuring between 3 and 7 millimeters, categorized as Lung-RADS 3, indicating a probably benign condition but one that often requires careful follow-up.
“Determining appropriate care for a patient with multiple nodules and a significant smoking history is often complicated by patient anxiety and concern about an ongoing risk of malignancy,” said Daya Nadarajah, MD, the patient’s pulmonologist. “Follow-up can be problematic without the additional diagnostic information provided by CyPath Lung. A negative CyPath Lung result helps reassure both physician and patient that an early cancer is unlikely to have been missed.”
Dr. Nadarajah ordered a CyPath Lung test, which returned a negative result of “unlikely malignancy.” Based on the result, the physician and patient proceeded with a serial six-month CT surveillance plan consistent with Lung-RADS 3 guidelines. A follow-up CT scan showed the sub-centimeter nodules remained stable.
“Patients with multiple small nodules and many years of tobacco use often face months of uncertainty and fear,” said Gordon Downie, MD, PhD, chief medical officer of bioAffinity Technologies. “CyPath Lung provides physicians with additional, objective information that helps stratify risk and supports confident clinical decision-making while maintaining appropriate vigilance for patients at high risk for lung cancer.”
According to the company, CyPath Lung is designed as a noninvasive diagnostic to aid in the early detection of lung cancer in high-risk patients with indeterminate nodules. The test uses flow cytometry and proprietary artificial intelligence to identify cell populations in sputum samples associated with malignancy, incorporating a fluorescent porphyrin that is preferentially taken up by cancer-related cells.
Clinical study results for CyPath Lung have shown 92% sensitivity, 87% specificity, and 88% accuracy in detecting lung cancer in patients at high risk who have small indeterminate lung nodules measuring less than 20 millimeters.
