Oncologic Outcomes after Localized Prostate Cancer Treatment: Associations with Pretreatment Prostate Magnetic Resonance Imaging Findings.

Abstract

We investigated whether T2-weighted magnetic resonance imaging findings could improve upon established prognostic indicators of metastatic disease and prostate cancer specific survival. For a cohort of 3,406 consecutive men who underwent prostate magnetic resonance imaging before prostatectomy (2,160) or radiotherapy (1,246) between 2001 and 2006, T2-weighted magnetic resonance imaging exams were retrospectively interpreted and categorized as I) no focal suspicious lesion, II) organ confined focal lesion, III) focal lesion with extraprostatic extension or IV) focal lesion with seminal vesicle invasion. Clinical risk was recorded based on European Association of Urology (EAU) guidelines and the Cancer of the Prostate Risk Assessment (CAPRA) scoring system. Survival probabilities and c-indices were estimated using Cox models and inverse probability censoring weights, respectively. The median followup was 10.8 years (IQR 8.6-13.0). Higher magnetic resonance imaging categories were associated with a higher likelihood of developing metastases (HR 3.5-18.1, p <0.001 for all magnetic resonance imaging categories) and prostate cancer death (HR 3.1-29.7, p <0.001-0.025); these associations were statistically independent of EAU risk categories, CAPRA scores and treatment type (surgery vs radiation). Combining EAU risk or CAPRA scores with magnetic resonance imaging categories significantly improved prognostication of metastases (c-indices: EAU: 0.798, EAU + magnetic resonance imaging: 0.872; CAPRA: 0.808, CAPRA + magnetic resonance imaging: 0.877) and prostate cancer death (c-indices: EAU 0.813, EAU + magnetic resonance imaging: 0.889; CAPRA: 0.814, CAPRA + magnetic resonance imaging: 0.892; p <0.001 for all). Magnetic resonance imaging findings of localized prostate cancer are associated with clinically relevant long-term oncologic outcomes. Combining magnetic resonance imaging and clinicopathological data results in more accurate prognostication, which could facilitate individualized patient management.