Utilization of biopsy-based genomic classifier to predict distant metastasis after definitive radiation and short-course ADT for intermediate and high-risk prostate cancer

Abstract

Background: We examined the ability of a biopsy-based 22-marker genomic classifier (GC) to predict for distant metastases after radiation and a median of 6 months of androgen deprivation therapy (ADT).

Methods: We studied 100 patients with intermediate-risk (55%) and high-risk (45%) prostate cancer who received definitive radiation plus a median of 6 months of ADT (range 3-39 months) from 2001-2013 at a single center and had available biopsy tissue. Six to ten 4 micron sections of the needle biopsy core with the highest Gleason score and percentage of tumor involvement were macrodissected for RNA extraction. GC scores (range, 0.04-0.92) were determined. The primary end point of the study was time to distant metastasis. Median follow-up was 5.1 years. There were 18 metastases during the study period.

Results: On univariable analysis (UVA), each 0.1 unit increase in GC score was significantly associated with time to distant metastasis (hazard ratio: 1.40 (1.10-1.84), P=0.006) and remained significant after adjusting for clinical variables on multivariable analysis (MVA) (adjusted hazard ratio: 1.36 (1.04-1.83), P=0.024). The c-index for 5-year distant metastasis was 0.45 (95% confidence interval: 0.27-0.64) for Cancer of the Prostate Risk Assessment score, 0.63 (0.40-0.78) for National Comprehensive Cancer Network (NCCN) risk groups, and 0.76 (0.57-0.89) for the GC score. Using pre-specified GC risk categories, the cumulative incidence of metastasis for GC>0.6 reached 20% at 5 years after radiation (P=0.02).

Conclusions: We believe this is the first demonstration of the ability of the biopsy-based GC score to predict for distant metastases after definitive radiation and ADT for intermediate- and high-risk prostate cancer. Patients with the highest GC risk (GC>0.6) had high rates of metastasis despite multi-modal therapy suggesting that they could potentially be candidates for treatment intensification and/or enrollment in clinical trials of novel therapy.

Figure 1

Distributions of the study cohort by (a) Cancer of the Prostate Risk Assessment (CAPRA), (b) genomic classifier risk scores.

Figure 2

(a) Least absolute shrinkage and selection operator (LASSO) coefficient path demonstrating the order of importance of genomic classifier (GC) and clinical variables in predicting metastasis. Moving from right to left, the order of nonzero hazards coefficients represents the order of variable importance. (b) LASSO coefficient path without penalization on GC using a cross-validated penalty parameter of 0.049, represented by a vertical dashed line. Only GC, percent of positive cores and clinical stage have nonzero hazards coefficients at this level of penalization. This model estimates a less biased hazard ratio for GC when the number of events per variable is low. (c) Survival c-indices at 5 years following radiation therapy (RT) for GC, Cancer of the Prostate Risk Assessment (CAPRA) and National Comprehensive Cancer Network (NCCN) risk. (d) Decision curve analysis comparing net benefit at 5 years post-RT of GC and CAPRA across various threshold probabilities. Compared with ‘treat none' and ‘treat all' scenarios (in which no risk prediction model is employed) to make treatment decisions, across a range of threshold probabilities GC had the highest net benefit compared with the clinical-only CAPRA risk model. The net benefit is defined as a measure of the relative value of benefits from identifying higher risk men that should for example, receive more intensive therapy (for example, longer duration hormonal suppression) and harms (for example, morbidity of long-term androgen deprivation therapy (ADT)) associated with the GC and CAPRA risk models.

Figure 3

(a) Cumulative incidence curves in which patients are stratified by National Comprehensive Cancer Network (NCCN) risk categories. (b) Cumulative incidence curves in which patients are stratified by Cancer of the Prostate Risk Assessment (CAPRA) risk categories. (c) Cumulative incidence curves in which patients are stratified by genomic classifier (GC) risk categories. (d) Cumulative incidence curves in which patients are stratified by GC risk using an exploratory cutoff of 0.2. RT, radiation therapy.