Related Experiment Video
Updated: Jul 25, 2026

07:35
Use of Ultra-high Field MRI in Small Rodent Models of Polycystic Kidney Disease for In Vivo Phenotyping and Drug Monitoring
Published on: June 23, 2015
11.5K
Mayo Clinic Validation of the AUA Risk Groups for Localized Renal Cell Carcinoma
Andrew Zganjar1, Abhinav Khanna1, Dan Joyce1
1Department of Urology, Mayo Clinic, Rochester, Minnesota.
The Journal of Urology
|May 30, 2024
Summary
The AUA risk stratification system offers a straightforward approach for categorizing localized renal cell carcinoma (RCC) after surgery. It demonstrates good predictive ability for progression-free survival (PFS) and cancer-specific survival (CSS).
Area of Science:
- Urology
- Oncology
- Nephrology
Background:
- Localized renal cell carcinoma (RCC) requires effective risk stratification for post-surgical surveillance.
- The American Urological Association (AUA) introduced a new risk stratification system based on tumor stage and grade.
Purpose of the Study:
- To evaluate the predictive accuracy of the AUA risk stratification system for progression-free survival (PFS) and cancer-specific survival (CSS).
- To compare the performance of the AUA system against established institutional risk models.
Main Methods:
- Retrospective analysis of the Nephrectomy Registry (1980-2012).
- Inclusion of adult patients with unilateral, M0, clear cell RCC, or papillary RCC.
- Kaplan-Meier method for PFS and CSS estimation.
- Cox proportional hazards regression models with C indexes to assess predictive ability.
Main Results:
- The AUA system achieved C indexes around 0.80 for PFS and CSS in clear cell and papillary RCC.
- For clear cell RCC, the institutional model showed slightly better prediction than the AUA system (PFS: 0.815 vs 0.780; CSS: 0.857 vs 0.811).
- For papillary RCC, the AUA system showed comparable or slightly better prediction for PFS (0.775 vs 0.751) and similar prediction for CSS (0.830 vs 0.803).
Conclusions:
- The AUA stratification system is a parsimonious tool for categorizing localized clear cell and papillary RCC.
- It provides reliable predictive performance for PFS and CSS following surgical treatment.
- The system aids in guiding surveillance strategies for RCC patients.

