Prostate cancer polygenic risk scores evaluated in large data sets

In this video, Randy A. Vince Jr, MD, MS, shares insights from the European Urology study “Assessing the Clinical Utility of Published Prostate Cancer Polygenic Risk Scores in a Large Biobank Data Set.” Vince is an assistant professor of urologic oncology at Case Western Reserve University and University Hospitals Urology Institute, as well as the director of Minority Men's Health at University Hospitals Cutler Center for Men in Cleveland, Ohio.

Transcription:

The abstract mentions obtaining clinical and pathological data from the MUSIC registry. Were there any specific challenges in matching cases to controls based on this data, and how were they addressed?

I think the biggest challenge, and I think the biggest critique of our study, was the fact that it was men of European ancestry only. That was largely in part because of there were 2 data sets. One was our MUSIC collaborative, which is an extremely robust data set. And then the other portion were those men who were enrolled in what we call the Michigan Genomics Initiative. And so we had to link that data, and the majority of the men in the Michigan Genomics Initiative were of European ancestry. I think that was the biggest challenge that we had - not having as diverse a population as we would have liked for the study. But when it came down to linking the clinical information with both biopsy reports as well as the prostatectomy pathology reports, we didn't have much of a challenge with that.

Are there any other potential avenues for improvement you see in identifying men at risk for clinically significant prostate cancer?

One of the things that I want to make sure I say, is that while our study did not show a direct association with the increasing polygenic risk score to increasing disease aggressiveness, I think there are a number of people who are working specifically in this lane to develop polygenic risk scores so that way they can have a better clinical utility. So I do think that is promising in the future. However, we also have other tests, genomic tests like Decipher, which can help us differentiate those men who are more likely to have disease that will behave more aggressively. And then there are other things, like AI, which are now able to incorporate clinical information from patients, as well as that biopsy data, to give a better risk stratification on how that cancer might behave. All of these things are very promising.

This transcription was edited for clarity.