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Updated: Feb 15, 2026
05:19
A New Technique for Treating Low-risk Prostate Cancer—Super Active Surveillance
Published on: November 7, 2025
883
Clinical and pathologic factors predicting reclassification in active surveillance cohorts
Pablo S Sierra1, Shivashankar Damodaran2, David Jarrard2,3
1Fundacion Valle del Lili -Universidad Icesi, Cali, Colombia.
Summary
Identifying aggressive prostate cancer in low-risk patients is crucial. Features like higher PSA density and African American race can predict which patients need closer monitoring or treatment instead of active surveillance.
Area of Science:
- Urology
- Oncology
- Pathology
Background:
- Increasing incidence of low-risk prostate cancer leads to more patients considered for conservative management.
- Active Surveillance (AS) is an option for low-risk prostate cancer, but some patients may have aggressive disease.
- Overtreatment and associated morbidity are concerns in prostate cancer management.
Purpose of the Study:
- To identify clinicopathologic features that predict suboptimal candidates for Active Surveillance in prostate cancer.
- To improve risk stratification for patients with low-risk prostate cancer considering AS.
Main Methods:
- Systematic Medline/PubMed review conducted in January 2017.
- PRISMA guidelines followed for study selection.
- 83 relevant articles selected for full-text review.
Main Results:
- For Gleason Score 6 prostate cancer candidates for AS, higher PSA density, bilateral cancer, African American race, small prostate volume, and low testosterone are risk factors for reclassification.
- Nomograms incorporating these features enhance risk stratification.
- Clinical and pathologic features provide over 70% of information for risk stratification.
Conclusions:
- Certain clinicopathologic features can identify prostate cancer patients at higher risk for disease reclassification on Active Surveillance.
- These findings aid in selecting appropriate candidates for AS and may guide treatment decisions.
- Further research with longer-term AS data will refine recommendations.
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