Prostate Cancer Coverage from Every Angle
Advertisement
Advertisement

Can Prostate Cancer Surveillance Be Tailored to Individual Risk?

By: Julia Fiederlein
Posted: Monday, September 28, 2020

Daniel W. Lin, MD, of the University of Washington, Seattle, and colleagues analyzed data from two large, prospective surveillance cohorts to determine the clinical parameters that may be used to identify patients with prostate cancer who are eligible for deference of follow-up assessments. The results of this multicenter cohort study were published in JAMA Oncology.

"These findings suggest that active surveillance regimens can be tailored to individual risk, and many men can be followed up at longer intervals than those specified by most current protocols, thereby reducing anxiety, toxic effects, and cost," the investigators remarked.

The investigators focused on 850 patients from The Canary Prostate Active Surveillance Study (PASS) who were undergoing active surveillance. A total of 533 patients who were undergoing surveillance at the University of California, San Francisco (UCSF) were included for model validation. For both the PASS and UCSF cohorts, patients diagnosed since 2003 with Gleason grade group 1 on the diagnostic biopsy and Gleason grade group 1 or no tumor on the first surveillance biopsy were eligible for inclusion.

Seven parameters predictive of reclassification were identified: maximum percent positive cores (hazard ratio = 1.30; P = .004); history of any negative biopsy after diagnosis (1 vs. 0: hazard ratio = 0.52; P < .001, and at least 2 vs. 0: hazard ratio = 0.18; P < .001); time since diagnosis (hazard ratio = 1.62; P < .001); body mass index (hazard ratio = 1.08; P < .001); prostate size (hazard ratio = 0.40; P < .001); prostate-specific antigen (PSA) level at diagnosis (hazard ratio = 1.51; P = .003); and PSA kinetics (hazard ratio = 1.46; P < .001). For the prediction of nonreclassification at 4 years after the first surveillance biopsy, the area under the receiver operating curve was 0.70 for both the PASS and UCSF cohorts. The negative predictive values for those in the bottom 25th and 10th percentiles of risk were 0.88 and 0.95, respectively.

Disclosure: For full disclosures of the study authors, visit jamanetwork.com.



By continuing to browse this site you permit us and our partners to place identification cookies on your browser and agree to our use of cookies to identify you for marketing. Read our Privacy Policy to learn more.