R. Jeffrey Karnes, MD, addresses the limitations of the retrospective validation study design, outlines the future research he considers necessary for broad clinical adoption of MMAI, and offers his perspective on the trajectory of digital pathology and multimodal AI across urologic oncology over the next 5 years.
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.
R. Jeffrey Karnes, MD, presents the performance results of the MMAI model in the Mayo Clinic long-term survivor cohort, including its ability to outperform CAPRA-S in multivariable analysis, its sustained discrimination at 15 years of follow-up, and its prognostic value in patients with biochemical recurrence, salvage radiotherapy receipt, and persistent postoperative PSA.
In this video, R. Jeffrey Karnes, MD, describes the design of the Mayo Clinic external validation study of the post-RP MMAI model, including the rationale for focusing on a long-term survivor cohort, the structure of the MMAI score, and the primary and secondary end points used in the analysis.
R. Jeffrey Karnes, MD, frames the ongoing challenge of post–radical prostatectomy prognostication and explains the key criteria urologists should apply when evaluating new AI-based prognostic tools, including the centrality of external validation and patient population diversity.
