Dr. Spratt on the potential use of an AI biomarker in treatment decision making for prostate cancer

In this video, Daniel E. Spratt, MD, highlights the implications of findings from the study, “Artificial intelligence predictive model for hormone therapy use in prostate cancer,” for which he served as the lead author. Spratt is the chair of radiation oncology at University Hospitals Seidman Cancer Center and a professor at Case Western Reserve University School of Medicine in Cleveland, Ohio.

Video Transcript:

The implication of this work is that currently we use NCCN risk groups, the national guidelines, to dictate who should receive what therapy. Or, in this case, for men with intermediate risk prostate cancer, which men should receive hormone therapy. So, there's really an immediate use case for this in that patients present to us in clinic with what's called unfavorable intermediate risk. These are the men that guidelines would say we should give hormone therapy.

The real immediate use case is that this biomarker can be an adjunct, or it can be something to assist in making the shared decision making with patients. I've ordered this test myself a number of times for my patients. It's one more thing during that conversation, right? Because we treat patients, not just cancer; it's the whole person. And I think the more information you have, helps you to make that shared decision making to what's right for the individual.

This transcription has been edited for clarity.