A group of genome-based biomarkers that add to a Kattan nomogram for predicting progression in men with high-risk prostate cancer.
OBJECTIVE
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.


METHODS
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.


CONCLUSIONS
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.
Paris
Pamela L
PL
Department of Urology, Helen Diller Family Comprehensive Cancer, and Helen Diller Family Comprehensive Cancer Biostatistics Core, University of California at San Francisco, California 94143, USA. pparis@cc.ucsf.edu
Weinberg
Vivian
V
Albo
Giancarlo
G
Roy
Ritu
R
Burke
Catherine
C
Simko
Jeffry
J
Carroll
Peter
P
Collins
Colin
C
D014408:Biomarkers, Tumor / Q000032:analysis*; D055028:Comparative Genomic Hybridization / Q000379:methods; D018450:Disease Progression; D006801:Humans; D008297:Male; D009362:Neoplasm Metastasis; D009364:Neoplasm Recurrence, Local; D049451:Nomograms; D011379:Prognosis; D011471:Prostatic Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D012189:Retrospective Studies; D018570:Risk Assessment
D014408:Biomarkers, Tumor