PURPOSE:

The three main treatment options for primary prostate cancer are surgery, radiation, and active surveillance. Surgical and radiation intervention for prostate cancer can be associated with significant morbidity. Therefore, accurate stratification predictive of outcome for prostate cancer patients is essential for appropriate treatment decisions. Nomograms that use clinical and pathologic variables are often used for risk prediction. Favorable outcomes exist even among men classified by nomograms as being at high risk of recurrence.

EXPERIMENTAL DESIGN:

Previously, we identified a set of DNA-based biomarkers termed Genomic Evaluators of Metastatic Prostate Cancer (GEMCaP) and have shown that they can predict risk of recurrence with 80% accuracy. Here, we examined the risk prediction ability of GEMCaP in a high-risk cohort and compared it to a Kattan nomogram.

RESULTS:

We determined that the GEMCaP genotype alone is comparable with the nomogram, and that for a subset of cases with negative lymph nodes improves upon it.

CONCLUSION:

Thus, GEMCaP shows promise for predicting unfavorable outcomes for negative lymph node high-risk cases, where the nomogram falls short, and suggests that addition of GEMCaP to nomograms may be warranted.