Prostate Cancer Coverage from Every Angle

Urinary Biomarkers in Detection of Prostate Cancer

By: Julia Fiederlein
Posted: Thursday, May 28, 2020

Daniel S. Brewer, PhD, of the University of East Anglia, Norwich, United Kingdom, and colleagues identified a combination of urinary biomarkers that may be used to accurately detect prostate cancer. This research, which was published in The Prostate, suggested the noninvasive ExoMeth model may reduce unnecessary biopsies while still harnessing the sensitivity required to detect aggressive disease. 

“Current practice assesses a patient’s disease using a PSA blood test, prostate biopsy, and MRI. But up to 60% of men with a raised PSA level are negative for prostate cancer on biopsy,” commented initial study author Shea P. Connell, BSc, also of the University of East Anglia, in a press release. “We wanted to see if other biological information from urine could be integrated together with clinical information to create a new predictive test with even greater potential.”

The researchers collected urine samples from 197 patients within the Movember Global Action Plan 1 cohort and performed a series of assays and machine-learning techniques. A model using clinical data alone, a model using genetic methylation data alone, and a model using cell-free RNA data alone were employed as comparator models. The ExoMeth risk prediction model was developed by combining all of the aforementioned variables.

As the model’s risk scores increased, so did the probability of disease detection from a biopsy. The researchers observed that their model provided an accurate prediction of the presence of Gleason ≥ 3 + 4, Gleason ≥ 4 + 3, and all prostate cancers with an AUC of 0.89, 0.81, and 0.91, respectively. Based on the AUC and distributions of risk scores, the ExoMeth model seemed to provide a more accurate discrimination of Gleason ≥ 3 + 4 disease from other outcomes than any of the comparator models (P < .01). Notably, at a decision threshold of 0.25, implementation of the ExoMeth model may result in a 66% reduction in unnecessary biopsies.

Disclosure: The study authors reported no conflicts of interest.

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