1. A prostate cancer risk calculator (PCRC-MRI): Use of clinical and magnetic resonance imaging data to predict biopsy outcome in North American men
- Author
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Kinnaird, Adam, Brisbane, Wayne, Kwan, Lorna, Priester, Alan, Chuang, Ryan, Barsa, Danielle E, Delfin, Merdie, Sisk, Anthony, Margolis, Daniel, Felker, Ely, Hu, Jim, and Marks, Leonard S
- Subjects
Biomedical and Clinical Sciences ,Clinical Sciences ,Oncology and Carcinogenesis ,Prostate Cancer ,Cancer ,Prevention ,Clinical Research ,Biomedical Imaging ,Urologic Diseases ,Aging ,4.1 Discovery and preclinical testing of markers and technologies ,Detection ,screening and diagnosis ,4.2 Evaluation of markers and technologies ,Urology & Nephrology ,Clinical sciences ,Oncology and carcinogenesis - Abstract
IntroductionA functional tool to optimize patient selection for magnetic resonance imaging (MRI)-guided prostate biopsy (MRGB) is an unmet clinical need. We sought to develop a prostate cancer risk calculator (PCRC-MRI) that combines MRI and clinical characteristics to aid decision-making for MRGB in North American men.MethodsTwo prospective registries containing 2354 consecutive men undergoing MRGB (September 2009 to April 2019) were analyzed. Patients were randomized into five groups, with one group randomly assigned to be the validation cohort against the other four groups as the discovery cohort. The primary outcome was detection of clinically significant prostate cancer (csPCa) defined as Gleason grade group ≥2. Variables included age, ethnicity, digital rectal exam (DRE), prior biopsy, prostate-specific antigen (PSA), prostate volume, PSA density, and MRI score. Odds ratios (OR) were calculated from multivariate logistic regression comparing two models: one with clinical variables only (clinical) against a second combining clinical variables with MRI data (clinical+MRI).ResultscsPCa was present in 942 (40%) of the 2354 men available for study. The positive and negative predictive values for csPCa in the clinical+MRI model were 57% and 89%, respectively. The area under the curve of the clinical+MRI model was superior to the clinical model in discovery (0.843 vs. 0.707, p
- Published
- 2022