Stephen J Freedland1, Voleak Choeurng2, Lauren Howard3, Amanda De Hoedt4, Marguerite du Plessis2, Kasra Yousefi2, Lucia L Lam2, Christine Buerki2, Seong Ra5, Bruce Robbins5, Edouard J Trabulsi6, Nikhil L Shah2, Firas Abdollah7, Felix Y Feng8, Elai Davicioni2, Adam P Dicker6, Robert J Karnes9, Robert B Den10. 1. Department of Surgery, Division of Urology, Center for Integrated Research on Cancer and Lifestyle, Samuel Oschin Comprehensive Cancer Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Surgery Section, Durham Veteran Affairs Medical Center, Durham, NC, USA. 2. GenomeDx Biosciences Inc., Vancouver, BC, Canada. 3. Surgery Section, Durham Veteran Affairs Medical Center, Durham, NC, USA; Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA. 4. Surgery Section, Durham Veteran Affairs Medical Center, Durham, NC, USA. 5. San Diego Pathologists Medical Group, San Diego, CA, USA. 6. Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA. 7. Vattikuti Urology Institute, Henry Ford Hospital, Detroit, MI, USA. 8. University of Michigan, Ann Arbor, MI, USA. 9. Department of Urology, Mayo Clinic, Rochester, MN, USA. 10. Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA. Electronic address: Robert.Den@jeffersonhospital.org.
Abstract
BACKGROUND: Despite salvage radiation therapy (SRT) for recurrent prostate cancer (PCa) after radical prostatectomy (RP), some patients still progress to metastases. Identifying these men would allow them to undergo systemic therapy including testing novel therapies to reduce metastases risk. OBJECTIVE: To test whether the genomic classifier (GC) predicts development of metastatic disease. DESIGN, SETTING, AND PARTICIPANTS: Retrospective multi-center and multi-ethnic cohort study from two academic centers and one Veterans Affairs Medical Center in the United States involving 170 men receiving SRT for recurrent PCa post-RP. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Time from SRT to development of metastatic disease tested using Cox regression, survival c-index, and decision curve analysis. Performance of GC was compared to the Cancer of the Prostate Risk Assessment Score and Briganti risk models based on these metrics. RESULTS AND LIMITATIONS: With a median 5.7 yr follow-up after SRT, 20 patients (12%) developed metastases. On multivariable analysis, for each 0.1 unit increase in GC (scaled from 0 to 1), the hazard ratio for metastasis was 1.58 (95% confidence interval 1.16-2.17; p=0.002). Adjusting for androgen deprivation therapy did not materially change the results. The c-index for GC was 0.85 (95% confidence interval 0.73-0.88) versus 0.63-0.65 for published clinico-pathologic risk models. The 5-yr cumulative incidence of metastasis post-SRT in patients with low, intermediate, and high GC scores was 2.7%, 8.4%, and 33.1%, respectively (p<0.001). CONCLUSIONS: While validation in larger, prospectively collected cohorts is required, these data suggest GC is a strong predictor of metastases among men receiving SRT for recurrent PCa post-RP, accurately identifying men who are excellent candidates for systemic therapy due to their very high-risk of metastases. PATIENT SUMMARY: Genomic classifier and two clinico-pathologic risk models were evaluated on their ability to predict metastases among men receiving salvage radiation therapy for recurrent prostate cancer. Genomic classifier was able to identify candidates for further therapies due to their very high-risk of metastases.
BACKGROUND: Despite salvage radiation therapy (SRT) for recurrent prostate cancer (PCa) after radical prostatectomy (RP), some patients still progress to metastases. Identifying these men would allow them to undergo systemic therapy including testing novel therapies to reduce metastases risk. OBJECTIVE: To test whether the genomic classifier (GC) predicts development of metastatic disease. DESIGN, SETTING, AND PARTICIPANTS: Retrospective multi-center and multi-ethnic cohort study from two academic centers and one Veterans Affairs Medical Center in the United States involving 170 men receiving SRT for recurrent PCa post-RP. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Time from SRT to development of metastatic disease tested using Cox regression, survival c-index, and decision curve analysis. Performance of GC was compared to the Cancer of the Prostate Risk Assessment Score and Briganti risk models based on these metrics. RESULTS AND LIMITATIONS: With a median 5.7 yr follow-up after SRT, 20 patients (12%) developed metastases. On multivariable analysis, for each 0.1 unit increase in GC (scaled from 0 to 1), the hazard ratio for metastasis was 1.58 (95% confidence interval 1.16-2.17; p=0.002). Adjusting for androgen deprivation therapy did not materially change the results. The c-index for GC was 0.85 (95% confidence interval 0.73-0.88) versus 0.63-0.65 for published clinico-pathologic risk models. The 5-yr cumulative incidence of metastasis post-SRT in patients with low, intermediate, and high GC scores was 2.7%, 8.4%, and 33.1%, respectively (p<0.001). CONCLUSIONS: While validation in larger, prospectively collected cohorts is required, these data suggest GC is a strong predictor of metastases among men receiving SRT for recurrent PCa post-RP, accurately identifying men who are excellent candidates for systemic therapy due to their very high-risk of metastases. PATIENT SUMMARY: Genomic classifier and two clinico-pathologic risk models were evaluated on their ability to predict metastases among men receiving salvage radiation therapy for recurrent prostate cancer. Genomic classifier was able to identify candidates for further therapies due to their very high-risk of metastases.
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