Opinion|Videos|June 10, 2026

Clinical Application of MMAI Score in Patients with Prostate Cancer

In this video, R. Jeffrey Karnes, MD, translates MMAI scoring into practical clinical guidance, discussing how MMAI High and MMAI Low results can inform surveillance intensity, early salvage radiation consideration, and adjuvant therapy planning, and outlining the shared decision-making framework he uses when ordering the test.

Integrating a new prognostic score into real-world clinical practice requires not only confidence in the underlying evidence but also a clear framework for translating test results into actionable decisions—and an understanding of when the information is most likely to benefit a given patient. In the fourth segment of this 5-part series, R. Jeffrey Karnes, MD, the Dr. Anson Clark Professor of Urology at Mayo Clinic in Rochester, Minnesota, outlines how he approaches MMAI scoring in the post–radical prostatectomy (RP) setting, with attention to both surveillance planning and treatment escalation.

For patients who have not yet developed biochemical recurrence, Karnes describes MMAI as a potential tool for calibrating PSA surveillance intensity rather than prompting immediate therapeutic intervention. Patients with MMAI High scores may warrant more frequent PSA testing—potentially every 3 months—before any de-intensification of surveillance intervals, whereas MMAI Low results may support a more conservative follow-up cadence. In patients with a rising but sub-threshold PSA, a high MMAI score may prompt earlier consideration of salvage radiation, and potentially adjuvant radiation at a prostate-specific antigen level below 0.2 ng/mL, whereas a low score may support continued observation. Karnes also notes that in his radiation oncology collaborations, MMAI scores are routinely used to guide decisions about whether to add concomitant hormonal therapy to curative-intent radiation.

Karnes places significant emphasis on the role of shared decision-making in ordering prognostic tests. Before a result is available, he walks patients through the meaning of both possible outcomes and the clinical implications of each, ensuring that a plan is already in place before the score is returned. He uses an analogy of weather probability to illustrate that patients interpret the same numeric risk differently, and that understanding a patient's threshold for action is essential to using test results constructively. He identifies the favorable intermediate-risk population—particularly Gleason grade group 2 patients weighing active surveillance against active treatment—as a setting where he has seen meaningful clinical utility for MMAI in practice, even acknowledging that the evidence base in this group is still developing.