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Updated: Mar 27, 2026

A New Technique for Treating Low-risk Prostate Cancer—Super Active Surveillance
Published on: November 7, 2025
A hospital-based study of initial observation for low-risk prostate cancer and its predictors in the United States
Matthew J Maurice1, Hui Zhu2, Robert Abouassaly1
1University Hospitals Case Medical Center, Cleveland, OH.
Introduction:
Initial observation (IO) is a strategy to minimize prostate cancer overtreatment. We sought to evaluate contemporary trends in IO utilization for low-risk prostate cancer in the United States and to identify factors associated with its uptake.
Methods:
Using the National Cancer Database, we identified men with low-risk prostate cancer diagnosed between 2004 and 2011. IO utilization was plotted over time. Multivariate logistic regression was performed to determine the influence of diagnosis year and other factors on IO selection.
Results:
Of the 219 971 men with low-risk prostate cancer, 21 231 (9.7%) underwent IO. Beginning in 2008, IO use increased significantly with time (range: 7.5%-14.3%). Compared to 2004, patients diagnosed in 2011 had 2.5 times the odds of choosing IO (odds ratio [OR] 2.5, confidence interval [CI] 2.3-2.6, p < 0.01). Aside from diagnosis year, age, race, Charlson score, clinical T stage, and PSA level predicted IO use (p < 0.01). Other predictors of IO included hospital type, insurance provider, and household income. Specifically, comprehensive cancer centres, private insurance, and higher income predicted decreased IO usage (OR 0.5, CI 0.5-0.5, p < 0.01; OR 0.4, CI 0.4-0.4, p < 0.01; and OR 0.8, CI 0.8-0.9, p < 0.01, respectively). Less educated men were also less likely to undergo observation (OR 0.8, CI 0.8-0.9, p < 0.01). Treatment within the western United States was significantly, but weakly, associated with increased use of IO (p < 0.01).
Conclusions:
In recent years, low-risk prostate cancer has been increasingly managed with IO, appropriately driven by patient and disease factors. Unexpectedly, observation usage also varies by race, hospital, insurance, income, and geography, suggesting that non-clinical factors may affect treatment selection.
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