Trinity Biotech plc, a global diagnostics company, announced successful results from a clinical study of a new, enhanced version of its EpiCapture prostate cancer test, engineered to deliver higher precision risk prediction of aggressive prostate cancer.
This next-generation version of EpiCapture utilises machine learning tools that integrate additional patient features, including patient ethnicity, in conjunction with the DNA biomarkers, enabling the test to generate more accurate, individualised risk prediction scores. This enhanced approach addresses a well-documented challenge in oncology diagnostics: meaningful performance variation across different demographic and ethnic groups, particularly in prostate cancer, where incidence and severity differ significantly among populations.
EpiCapture, as a urine liquid biopsy test, offers a simpler and more accessible alternative to traditional diagnostic methods for assessing high-grade prostate cancer risk. Current approaches — including high-resolution MRI scans, which are often costly and limited in availability, and needle biopsies, which may expose patients to infection risk and other complications — present significant barriers to early and accessible detection.
Prostate cancer is the most common non-skin cancer among men in the U.S., with about 1 in 8 men diagnosed during their lifetime and U.S. national expenditures for prostate cancer care recently estimated to be over $20 billion annually. The ability to accurately monitor prostate cancer progression is critical, as the disease can often be slow-growing, and unnecessary invasive interventions, such as prostate biopsies, can lead to significant complications.
The performance of the upgraded test was evaluated in a comprehensive clinical study involving approximately 750 patient samples, representing a substantially larger and more ethnically diverse cohort than EpiCapture’s earlier studies. The study was conducted independently by a specialist bioinformatics research partner to ensure rigorous and independent validation of the diagnostic performance obtained with the next-generation EpiCapture algorithm.
