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J Clin Oncol. 2018 Feb 20;36(6):581-590. doi: 10.1200/JCO.2017.74.2940. Epub 2017 Nov 29.

Development and Validation of a Novel Integrated Clinical-Genomic Risk Group Classification for Localized Prostate Cancer.

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Daniel E. Spratt, Robert T. Dess, Adam Cole, Shuang G. Zhao, and Rohit Mehra, University of Michigan, Ann Arbor; Firas Abdollah, Henry Ford Health System, Detroit, MI; Jingbin Zhang, María Santiago-Jiménez, Lucia L.C. Lam, Jijumon Chelliserry, Marguerite du Plessis, Voleak Choeurng, Maria Aranes, Tyler Kolisnik, Jennifer Margrave, Jason Alter, Jennifer Jordan, Christine Buerki, Kasra Yousefi, Zaid Haddad, and Elai Davicioni, GenomeDx Biosciences, Vancouver, British Columbia, Canada; John W. Davis, The University of Texas MD Anderson Cancer Center, Houston, TX; Robert B. Den, Adam P. Dicker, and Edouard J. Trabulsi, Thomas Jefferson University, Philadelphia, PA; Christopher J. Kane, University of California San Diego, San Diego; Edward Uchio, University of California Irvine; Josh M. Randall, Orange County Urology Associates, Irvine; Hao Nguyen, Peter R. Carroll and Felix Y. Feng, University of California San Francisco, San Francisco, CA; Alan Pollack and Radka Stoyanova, University of Miami, Miami, FL; Ashley E. Ross, Johns Hopkins School of Medicine, Baltimore, MD; Andrew G. Glass and Sheila Weinmann, Kaiser Permanente Northwest, Portland, OR; Stacy Loeb, New York University; Ashutosh Tewari, Icahn School of Medicine at Mount Sinai, New York, NY; Edward M. Schaeffer, Northwestern University, Evanston, IL; Eric A. Klein, Cleveland Clinic, Cleveland, OH; R. Jeffrey Karnes, Mayo Clinic, Rochester, MN; and Paul L. Nguyen, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.


Purpose It is clinically challenging to integrate genomic-classifier results that report a numeric risk of recurrence into treatment recommendations for localized prostate cancer, which are founded in the framework of risk groups. We aimed to develop a novel clinical-genomic risk grouping system that can readily be incorporated into treatment guidelines for localized prostate cancer. Materials and Methods Two multicenter cohorts (n = 991) were used for training and validation of the clinical-genomic risk groups, and two additional cohorts (n = 5,937) were used for reclassification analyses. Competing risks analysis was used to estimate the risk of distant metastasis. Time-dependent c-indices were constructed to compare clinicopathologic risk models with the clinical-genomic risk groups. Results With a median follow-up of 8 years for patients in the training cohort, 10-year distant metastasis rates for National Comprehensive Cancer Network (NCCN) low, favorable-intermediate, unfavorable-intermediate, and high-risk were 7.3%, 9.2%, 38.0%, and 39.5%, respectively. In contrast, the three-tier clinical-genomic risk groups had 10-year distant metastasis rates of 3.5%, 29.4%, and 54.6%, for low-, intermediate-, and high-risk, respectively, which were consistent in the validation cohort (0%, 25.9%, and 55.2%, respectively). C-indices for the clinical-genomic risk grouping system (0.84; 95% CI, 0.61 to 0.93) were improved over NCCN (0.73; 95% CI, 0.60 to 0.86) and Cancer of the Prostate Risk Assessment (0.74; 95% CI, 0.65 to 0.84), and 30% of patients using NCCN low/intermediate/high would be reclassified by the new three-tier system and 67% of patients would be reclassified from NCCN six-tier (very-low- to very-high-risk) by the new six-tier system. Conclusion A commercially available genomic classifier in combination with standard clinicopathologic variables can generate a simple-to-use clinical-genomic risk grouping that more accurately identifies patients at low, intermediate, and high risk for metastasis and can be easily incorporated into current guidelines to better risk-stratify patients.


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