Some patients with low-risk prostate cancer (PCa) receiving active surveillance (AS) can safely adopt a less intensive monitoring regimen after confirmatory biopsy, investigators suggest.
Matthew R. Cooperberg, MD, MPH, of the University of California, San Francisco (UCSF), and colleagues developed and validated the Canary model, a potential clinical tool that can be used to identify AS patients at very low risk or high risk for PCa reclassification at confirmatory biopsy, which is within a year of diagnosis at their institution. Eligible men had Gleason grade group (GG) 1 on diagnostic biopsy and GG1 (Gleason score 3+3) or no tumor on first surveillance biopsy. Reclassification was defined as any increase to GG 2 (Gleason score 3+4) or higher.
The model was developed using routinely collected clinical data from the Canary Prostate Active Surveillance Study (PASS) cohort of 850 men (median age 64 years; 91% White). It was validated using a separate UCSF cohort of 533 men (median age 61 years; 79% White). In results from a multivariable analysis published in JAMA Oncology, the following parameters predicted higher or lower risk for PCa reclassification:
- Higher maximum percent positive cores (10% increase; 30% higher risk; P =.004),
- Higher PSA at diagnosis (51% higher risk; P =.003)
- PSA kinetics (0.10 increase; 46% higher risk; P <.001)
- Time since diagnosis (62% higher risk; P <.001)
- Higher body mass index (8% higher risk; P <.001),
- History of any negative biopsy after diagnosis (82% and 48% lower risk for 2 or 1 negative biopsies, respectively, vs 0; P <.001)
- Larger prostate size (60% lower risk; 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, the investigators reported. For men in the bottom 25th and 10th percentile of reclassification risk, the negative predictive value of the model was 0.88 and 0.95, respectively.
The investigators found very low rates of missed reclassification for men in the lowest quartile of risk. For example, avoiding all surveillance for 4 years would miss only 29 reclassification events per 1000 men in this quartile.
“Although we present outcomes between confirmatory biopsy and the 4-year time point as a clinically relevant milestone, the model is intended to be calculable at any point in the surveillance trajectory as additional data accumulate,” Dr Cooperberg’s team explained. “Our findings suggest that large subpopulations of men eligible for active surveillance could safely adopt a much less intensive regimen after confirmatory biopsy, deferring not only biopsy but also imaging studies and, at least in principle, many interval PSA tests.”
Results from imaging and other biomarkers were not included in the model. Future studies might compare imaging and biomarker results to the model, the investigators discussed.
Dr Cooperberg’s team stressed that the model is meant to guide patient discussions, not dictate practice. A man with low risk for reclassification may choose to defer active surveillance interventions, such as biopsy, or not.
“Given that approximately half of all newly diagnosed prostate cancers are potentially appropriate for active surveillance,” the authors concluded, “deintensifying surveillance for substantial numbers of patients would reduce risks of biopsy and further shift the benefit-harm ratio for early detection in favor of PSA-based testing.”
Disclosure: Several study authors declared affiliations with the pharmaceutical industry. Please see the original reference for a full list of authors’ disclosures.
Cooperberg MR, Zheng Y, Faino AV, et al. Tailoring intensity of active surveillance for low-risk prostate cancer based on individualized prediction of risk stability. JAMA Oncol. Published online August 27, 2020. doi:10.1001/jamaoncol.2020.3187
Tailoring intensity of surveillance for prostate cancer based on prediction of risk stability. JN Learning. https://edhub.ama-assn.org/jn-learning/audio-player/18536720 Accessed August 27, 2020.
This article originally appeared on Oncology Nurse Advisor