Comparisons of Novel Risk Stratification Models to the Current cT1a/b Staging in Incidental Prostate Cancer
Lukas Scheipner1,2, Andrea Baudo1,3, Letizia Maria Ippolita Jannello1,4,5
1Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montréal Health Center, Montréal, Québec, Canada.
Objective:
Incidental prostate cancer (PCa) patients are currently stratified to either cT1a vs. cT1b stage, depending on tumor volume (< 5% vs. > 5%) in the resected tissue. We tested for other models that could improve cancer-specific survival (CSS) predictions.
Methods:
Incidental (cT1a/cT1b) PCa patients were retrospectively identified within the Surveillance, Epidemiology, and End Results (SEER) database (2004-2015). Kaplan-Meier plots illustrated CSS at 5 years of follow-up. Combination of variables resulted in three distinct stratification models based on cT1a vs. cT1b and Gleason score sum (GS). Multivariable Cox regression models that predicted CSS were used for area under the curve (AUC) quantification after 20-fold cross validation.
Results:
We identified a total of 5155 incidental PCa patients. CSS at 5 years was 98% for cT1a vs. 90% for cT1b (p < 0.0001). CSS at 5 years for combination of cT1a and GS 6 patients was 99% vs. 92% for patients with either cT1b or GS ≥ 7 (p < 0.0001). Finally, for patients with GS < 8, CSS at 5 years was 98% vs. 72% for patients with GS ≥ 8 (p < 0.0001). The multivariable adjusted AUC was 0.83 vs. 0.82 vs. 0.88, for each model, respectively.
Conclusion:
Of all tested stratification models, the consideration of GS stratified between < 8 and ≥ 8 resulted in the best survival discrimination, as well as highest accuracy after cross-validation. In consequence, the use of this model (GS < 8 vs. ≥ 8) appears better suited than the standard cT1a vs. cT1b substaging, when CSS represents the endpoint of interest.
