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

Daniel E Spratt1, Jingbin Zhang1, María Santiago-Jiménez1

  • 1Daniel 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.

Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology
|November 30, 2017
PubMed
Summary

A new clinical-genomic risk grouping system improves metastasis prediction for localized prostate cancer patients. This system enhances treatment recommendations by providing more accurate risk stratification than existing models.

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Area of Science:

  • Oncology
  • Genomics
  • Biostatistics

Background:

  • Integrating numeric genomic classifier results into established risk groups for localized prostate cancer treatment is clinically challenging.
  • Current risk stratification models, such as the National Comprehensive Cancer Network (NCCN) and Cancer of the Prostate Risk Assessment (CAPRA), have limitations in predicting distant metastasis.
  • Accurate risk assessment is crucial for guiding treatment decisions in localized prostate cancer.

Purpose of the Study:

  • To develop and validate a novel clinical-genomic risk grouping system for localized prostate cancer.
  • To create a system that seamlessly integrates into existing treatment guidelines.
  • To improve the accuracy of risk stratification for distant metastasis compared to current methods.

Main Methods:

  • Utilized two multicenter cohorts (n = 991) for training and validation of the clinical-genomic risk groups.
  • Employed competing risks analysis to estimate the risk of distant metastasis.
  • Constructed time-dependent c-indices to compare the performance of the new system against clinicopathologic risk models (NCCN, CAPRA).

Main Results:

  • The developed three-tier clinical-genomic risk groups demonstrated distinct 10-year distant metastasis rates (3.5% low, 29.4% intermediate, 54.6% high), consistent across validation cohorts.
  • The clinical-genomic risk grouping system showed improved predictive accuracy (c-index = 0.84) compared to NCCN (0.73) and CAPRA (0.74).
  • Significant patient reclassification occurred: 30% from NCCN's three-tier and 67% from its six-tier system were reclassified by the new clinical-genomic system.

Conclusions:

  • A commercially available genomic classifier combined with clinicopathologic variables can create an easy-to-use clinical-genomic risk grouping system.
  • This novel system accurately identifies patients at low, intermediate, and high risk for metastasis.
  • The clinical-genomic risk grouping system is readily incorporable into current guidelines for improved patient risk stratification in localized prostate cancer.