A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy

A. E. Ross, F. Y. Feng, M. Ghadessi, N. Erho, A. Crisan, C. Buerki, D. Sundi, A. P. Mitra, I. A. Vergara, D. J S Thompson, T. J. Triche, E. Davicioni, E. J. Bergstralh, R. B. Jenkins, R. J. Karnes, E. M. Schaeffer

Research output: Contribution to journalArticlepeer-review

Abstract

Background:Due to their varied outcomes, men with biochemical recurrence (BCR) following radical prostatectomy (RP) present a management dilemma. Here, we evaluate Decipher, a genomic classifier (GC), for its ability to predict metastasis following BCR.Methods:The study population included 85 clinically high-risk patients who developed BCR after RP. Time-dependent receiver operating characteristic (ROC) curves, weighted Cox proportional hazard models and decision curves were used to compare GC scores to Gleason score (GS), PSA doubling time (PSAdT), time to BCR (ttBCR), the Stephenson nomogram and CAPRA-S for predicting metastatic disease progression. All tests were two-sided with a type I error probability of 5%.Results:GC scores stratified men with BCR into those who would or would not develop metastasis (8% of patients with low versus 40% with high scores developed metastasis, P

Original languageEnglish (US)
Pages (from-to)64-69
Number of pages6
JournalProstate Cancer and Prostatic Diseases
Volume17
Issue number1
DOIs
StatePublished - Mar 2014

Keywords

  • biochemical recurrence
  • clinical validation
  • genomic classifier
  • metastasis
  • prognostic models

ASJC Scopus subject areas

  • Oncology
  • Urology
  • Cancer Research
  • Medicine(all)

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