National Cancer Institute's Working Group on Biochemically Recurrent Prostate Cancer: Clinical Trial Design Considerations.

PURPOSE: Biochemical recurrence (BCR) of prostate cancer (PCa) after definitive surgery and/or radiation (including salvage strategies) is a burgeoning area of clinical research inspired by ultrasensitive next-generation imaging. Most phase III trials in PCa have focused on metastatic disease, defined by conventional imaging. Despite the emergence of new imaging, clinical trial principles from metastatic studies will not optimize future BCR trials. METHODS: A Working Group convened at the National Cancer Institute on November 13, 2024 (NCI BCR WG). Key areas of discussion included nomenclature, baseline criteria for data capture, imaging considerations, delineation of high-risk populations to be targeted for trial development, requirements of metastasis-directed therapy (MDT) or hormonal therapy, quality-of-life considerations, and potential study end points. RESULTS: The NCI BCR WG defined the novel term "prostate-specific membrane antigen (PSMA)+BCR" to identify the emerging concept of recurrent PCa identifiable only on PSMA positron emission tomography (PET), overlapping with BCR and distinct from metastatic hormone-sensitive PCa as traditionally defined by conventional imaging. The WG suggested defining high-risk BCR with a prostate-specific antigen doubling time of ≤6 months, regardless of PET findings. The WG provided recommendations for baseline data capture and imaging requirements. Neither systemic therapy nor MDT were considered mandatory for control arms. The WG also discussed novel end points and quality-of-life metrics in this disease space. CONCLUSION: These discussions should inform future clinical BCR trials in this distinct disease space relative to metastatic disease defined by conventional imaging. The NCI BCR WG strongly advocates that future trials explore deintensification of treatment to minimize toxicity in this relatively indolent disease state.

Duke Scholars

Author Susan Halabi Biostatistics & Bioinformatics, Division of Biostatistics