Purpose To perform the first meta-analysis of the performance of the genomic classifier test, Decipher, in men with prostate cancer postprostatectomy. Methods MEDLINE, EMBASE, and the Decipher genomic resource information database were searched for published reports between 2011 and 2016 of men treated by prostatectomy that assessed the benefit of the Decipher test. Multivariable Cox proportional hazards models fit to individual patient data were performed; meta-analyses were conducted by pooling the study-specific hazard ratios (HRs) using random-effects modeling. Extent of heterogeneity between studies was determined with the I2 test. Results Five studies (975 total patients, and 855 patients with individual patient-level data) were eligible for analysis, with a median follow-up of 8 years. Of the total cohort, 60.9%, 22.6%, and 16.5% of patients were classified by Decipher as low, intermediate, and high risk, respectively. The 10-year cumulative incidence metastases rates were 5.5%, 15.0%, and 26.7% ( P < .001), respectively, for the three risk classifications. Pooling the study-specific Decipher HRs across the five studies resulted in an HR of 1.52 (95% CI, 1.39 to 1.67; I2 = 0%) per 0.1 unit. In multivariable analysis of individual patient data, adjusting for clinicopathologic variables, Decipher remained a statistically significant predictor of metastasis (HR, 1.30; 95% CI, 1.14 to 1.47; P < .001) per 0.1 unit. The C-index for 10-year distant metastasis of the clinical model alone was 0.76; this increased to 0.81 with inclusion of Decipher. Conclusion The genomic classifier test, Decipher, can independently improve prognostication of patients postprostatectomy, as well as within nearly all clinicopathologic, demographic, and treatment subgroups. Future study of how to best incorporate genomic testing in clinical decision-making and subsequent treatment recommendations is warranted.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2017 Mar 30 [Epub]
Daniel E Spratt, Kasra Yousefi, Samineh Deheshi, Ashley E Ross, Robert B Den, Edward M Schaeffer, Bruce J Trock, Jingbin Zhang, Andrew G Glass, Adam P Dicker, Firas Abdollah, Shuang G Zhao, Lucia L C Lam, Marguerite du Plessis, Voleak Choeurng, Zaid Haddad, Christine Buerki, Elai Davicioni, Sheila Weinmann, Stephen J Freedland, Eric A Klein, R Jeffrey Karnes, Felix Y Feng
Daniel E. Spratt and Shuang G. Zhao, University of Michigan, Ann Arbor; Firas Abdollah, Henry Ford Health System, Detroit, MI; Kasra Yousefi, Samineh Deheshi, Jingbin Zhang, Lucia L.C. Lam, Marguerite du Plessis, Voleak Choeurng, Zaid Haddad, Christine Buerki, and Elai Davicioni, GenomeDx Biosciences, Vancouver, British Columbia, Canada; Ashley E. Ross and Bruce J. Trock, Johns Hopkins Hospital, Baltimore, MD; Robert B. Den and Adam P. Dicker, Thomas Jefferson University, Philadelphia, PA; Edward M. Schaeffer, Northwestern University, Evanston, IL; Andrew G. Glass and Sheila Weinmann, Center for Health Research, Kaiser Permanente Northwest, Portland, OR; Stephen J. Freedland, Cedars-Sinai Medical Center, Los Angeles; Felix Y. Feng, University of California, San Francisco, CA; Eric A. Klein, Cleveland Clinic, Cleveland, OH; and R. Jeffrey Karnes, Mayo Clinic, Rochester, MN.