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Published on: September 3, 2013
De-escalation of Monitoring in Active Surveillance for Prostate Cancer: Results from the GAP3 Consortium
Yoichiro Tohi1, John M Sahrmann2, Jaron Arbet2
1Department of Urology, Faculty of Medicine, Kagawa University, Kagawa, Japan.
Background And Objective:
There is no consensus on de-escalation of monitoring during active surveillance (AS) for prostate cancer (PCa). Our objective was to determine clinical criteria that can be used in decisions to reduce the intensity of AS monitoring.
Methods:
The global prospective AS cohort from the Global Action Plan prostate cancer AS consortium was retrospectively analyzed. The 24656 patients with complete outcome data were considered. The primary goal was to develop a model identifying a subgroup with a high ratio of other-cause mortality (OCM) to PCa-specific mortality (PCSM). Nonparametric competing-risks models were used to estimate cause-specific mortality. We hypothesized that the subgroup with the highest OCM/PCSM ratio would be good candidates for de-escalation of AS monitoring.
Key Findings And Limitations:
Cumulative mortality at 15 yr, accounting for censoring, was 1.3% for PCSM, 11.5% for OCM, and 18.7% for death from unknown causes. We identified body mass index (BMI) >25 kg/m2 and <11% positive cores at initial biopsy as an optimal set of criteria for discriminating OCM from PCSM. The 15-yr OCM/PCSM ratio was 34.2 times higher for patients meeting these criteria than for those not meeting the criteria. According to these criteria, 37% of the cohort would be eligible for de-escalation of monitoring. Limitations include the retrospective nature of the study and the lack of external validation.
Conclusions:
Our study identified BMI >25 kg/m2 and <11% positive cores at initial biopsy as clinical criteria for de-escalation of AS monitoring in PCa.
Patient Summary:
We investigated factors that could help in deciding on when to reduce the intensity of monitoring for patients on active surveillance for prostate cancer. We found that patients with higher BMI (body mass index) and lower prostate cancer volume may be good candidates for less intensive monitoring. This model could help doctors and patients in making decisions on active surveillance for prostate cancer.
