Importance: Active surveillance is increasingly recognized as the preferred standard of care for men with low-risk prostate cancer. However, active surveillance requires repeated assessments, including prostate-specific antigen tests and biopsies that may increase anxiety, risk of complications, and cost.Objective: To identify and validate clinical parameters that can identify men who can safely defer follow-up prostate cancer assessments.Design, Setting, and Participants: The Canary Prostate Active Surveillance Study (PASS) is a multicenter, prospective active surveillance cohort study initiated in July 2008, with ongoing accrual and a median follow-up period of 4.1 years. Men with prostate cancer managed with active surveillance from 9 North American academic medical centers were enrolled. Blood tests and biopsies were conducted on a defined schedule for least 5 years after enrollment. Model validation was performed among men at the University of California, San Francisco (UCSF) who did not enroll in PASS. Men with Gleason grade group 1 prostate cancer diagnosed since 2003 and enrolled in PASS before 2017 with at least 1 confirmatory biopsy after diagnosis were included. A total of 850 men met these criteria and had adequate follow-up. For the UCSF validation study, 533 active surveillance patients meeting the same criteria were identified. Exclusion criteria were treatment within 6 months of diagnosis, diagnosis before 2003, Gleason grade score of at least 2 at diagnosis or first surveillance biopsy, no surveillance biopsy, or missing data.Exposures: Active surveillance for prostate cancer.Main Outcomes and Measures: Time from confirmatory biopsy to reclassification, defined as Gleason grade group 2 or higher on subsequent biopsy.Results: A total of 850 men (median [interquartile range] age, 64 [58-68] years; 774 [91%] White) were included in the PASS cohort. A total of 533 men (median [interquartile range] age, 61 [57-65] years; 422 [79%] White) were included in the UCSF cohort. Parameters predictive of reclassification on multivariable analysis included maximum percent positive cores (hazard ratio [HR], 1.30 [95% CI, 1.09-1.56]; P=.004), history of any negative biopsy after diagnosis (1 vs 0: HR, 0.52 [95% CI, 0.38-0.71]; P<.001 and =2 vs 0: HR, 0.18 [95% CI, 0.08-0.4]; P<.001), time since diagnosis (HR, 1.62 [95% CI, 1.28-2.05]; P<.001), body mass index (HR, 1.08 [95% CI, 1.05-1.12]; P<.001), prostate size (HR, 0.40 [95% CI, 0.25-0.62]; P<.001), prostate-specific antigen at diagnosis (HR, 1.51 [95% CI, 1.15-1.98]; P=.003), and prostate-specific antigen kinetics (HR, 1.46 [95% CI, 1.23-1.73]; P<.001). For prediction of nonreclassification at 4 years, the area under the receiver operating curve was 0.70 for the PASS cohort and 0.70 for the UCSF validation cohort. This model achieved a negative predictive value of 0.88 (95% CI, 0.83-0.94) for those in the bottom 25th percentile of risk and of 0.95 (95% CI, 0.89-1.00) for those in the bottom 10th percentile.Conclusions and Relevance: In this study, among men with low-risk prostate cancer, heterogeneity prevailed in risk of subsequent disease reclassification. These findings suggest that active surveillance intensity can be modulated based on an individual's risk parameters and that many men may be safely monitored with a substantially less intensive surveillance regimen.
View details for DOI 10.1001/jamaoncol.2020.3187
View details for PubMedID 32852532