Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk Patient population

Robert Jeffrey Karnes, Eric J. Bergstralh, Elai Davicioni, Mercedeh Ghadessi, Christine Buerki, Anirban P. Mitra, Anamaria Crisan, Nicholas Erho, Ismael A. Vergara, Lucia L. Lam, Rachel Carlson, Darby J S Thompson, Zaid Haddad, Benedikt Zimmermann, Thomas Sierocinski, Timothy J. Triche, Thomas Kollmeyer, Karla V. Ballman, Peter C. Black, George G. KleeRobert Brian Jenkins

Research output: Contribution to journalArticle

192 Citations (Scopus)

Abstract

Purpose: Patients with locally advanced prostate cancer after radical prostatectomy are candidates for secondary therapy. However, this higher risk population is heterogeneous. Many cases do not metastasize even when conservatively managed. Given the limited specificity of pathological features to predict metastasis, newer risk prediction models are needed. We report a validation study of a genomic classifier that predicts metastasis after radical prostatectomy in a high risk population. Materials and Methods: A case-cohort design was used to sample 1,010 patients after radical prostatectomy at high risk for recurrence who were treated from 2000 to 2006. Patients had preoperative prostate specific antigen greater than 20 ng/ml, Gleason 8 or greater, pT3b or a Mayo Clinic nomogram score of 10 or greater. Patients with metastasis at diagnosis or any prior treatment for prostate cancer were excluded from analysis. A 20% random sampling created a subcohort that included all patients with metastasis. We generated 22-marker genomic classifier scores for 219 patients with available genomic data. ROC and decision curves, competing risk and weighted regression models were used to assess genomic classifier performance. Results: The genomic classifier AUC was 0.79 for predicting 5-year metastasis after radical prostatectomy. Decision curves showed that the genomic classifier net benefit exceeded that of clinical only models. The genomic classifier was the predominant predictor of metastasis on multivariable analysis. The cumulative incidence of metastasis 5 years after radical prostatectomy was 2.4%, 6.0% and 22.5% in patients with low (60%), intermediate (21%) and high (19%) genomic classifier scores, respectively (p <0.001). Conclusions: Results indicate that genomic information from the primary tumor can identify patients with adverse pathological features who are most at risk for metastasis and potentially lethal prostate cancer.

Original languageEnglish (US)
Pages (from-to)2047-2053
Number of pages7
JournalJournal of Urology
Volume190
Issue number6
DOIs
StatePublished - Dec 2013

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Prostatectomy
Neoplasm Metastasis
Prostatic Neoplasms
Nomograms
Validation Studies
Prostate-Specific Antigen
ROC Curve
Population
Area Under Curve
Recurrence
Incidence
Therapeutics
Neoplasms

Keywords

  • Neoplasm metastasis
  • Prognosis
  • Prostate
  • Prostatic neoplasms
  • Transcriptome

ASJC Scopus subject areas

  • Urology

Cite this

Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk Patient population. / Karnes, Robert Jeffrey; Bergstralh, Eric J.; Davicioni, Elai; Ghadessi, Mercedeh; Buerki, Christine; Mitra, Anirban P.; Crisan, Anamaria; Erho, Nicholas; Vergara, Ismael A.; Lam, Lucia L.; Carlson, Rachel; Thompson, Darby J S; Haddad, Zaid; Zimmermann, Benedikt; Sierocinski, Thomas; Triche, Timothy J.; Kollmeyer, Thomas; Ballman, Karla V.; Black, Peter C.; Klee, George G.; Jenkins, Robert Brian.

In: Journal of Urology, Vol. 190, No. 6, 12.2013, p. 2047-2053.

Research output: Contribution to journalArticle

Karnes, RJ, Bergstralh, EJ, Davicioni, E, Ghadessi, M, Buerki, C, Mitra, AP, Crisan, A, Erho, N, Vergara, IA, Lam, LL, Carlson, R, Thompson, DJS, Haddad, Z, Zimmermann, B, Sierocinski, T, Triche, TJ, Kollmeyer, T, Ballman, KV, Black, PC, Klee, GG & Jenkins, RB 2013, 'Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk Patient population', Journal of Urology, vol. 190, no. 6, pp. 2047-2053. https://doi.org/10.1016/j.juro.2013.06.017
Karnes, Robert Jeffrey ; Bergstralh, Eric J. ; Davicioni, Elai ; Ghadessi, Mercedeh ; Buerki, Christine ; Mitra, Anirban P. ; Crisan, Anamaria ; Erho, Nicholas ; Vergara, Ismael A. ; Lam, Lucia L. ; Carlson, Rachel ; Thompson, Darby J S ; Haddad, Zaid ; Zimmermann, Benedikt ; Sierocinski, Thomas ; Triche, Timothy J. ; Kollmeyer, Thomas ; Ballman, Karla V. ; Black, Peter C. ; Klee, George G. ; Jenkins, Robert Brian. / Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk Patient population. In: Journal of Urology. 2013 ; Vol. 190, No. 6. pp. 2047-2053.
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abstract = "Purpose: Patients with locally advanced prostate cancer after radical prostatectomy are candidates for secondary therapy. However, this higher risk population is heterogeneous. Many cases do not metastasize even when conservatively managed. Given the limited specificity of pathological features to predict metastasis, newer risk prediction models are needed. We report a validation study of a genomic classifier that predicts metastasis after radical prostatectomy in a high risk population. Materials and Methods: A case-cohort design was used to sample 1,010 patients after radical prostatectomy at high risk for recurrence who were treated from 2000 to 2006. Patients had preoperative prostate specific antigen greater than 20 ng/ml, Gleason 8 or greater, pT3b or a Mayo Clinic nomogram score of 10 or greater. Patients with metastasis at diagnosis or any prior treatment for prostate cancer were excluded from analysis. A 20{\%} random sampling created a subcohort that included all patients with metastasis. We generated 22-marker genomic classifier scores for 219 patients with available genomic data. ROC and decision curves, competing risk and weighted regression models were used to assess genomic classifier performance. Results: The genomic classifier AUC was 0.79 for predicting 5-year metastasis after radical prostatectomy. Decision curves showed that the genomic classifier net benefit exceeded that of clinical only models. The genomic classifier was the predominant predictor of metastasis on multivariable analysis. The cumulative incidence of metastasis 5 years after radical prostatectomy was 2.4{\%}, 6.0{\%} and 22.5{\%} in patients with low (60{\%}), intermediate (21{\%}) and high (19{\%}) genomic classifier scores, respectively (p <0.001). Conclusions: Results indicate that genomic information from the primary tumor can identify patients with adverse pathological features who are most at risk for metastasis and potentially lethal prostate cancer.",
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AU - Karnes, Robert Jeffrey

AU - Bergstralh, Eric J.

AU - Davicioni, Elai

AU - Ghadessi, Mercedeh

AU - Buerki, Christine

AU - Mitra, Anirban P.

AU - Crisan, Anamaria

AU - Erho, Nicholas

AU - Vergara, Ismael A.

AU - Lam, Lucia L.

AU - Carlson, Rachel

AU - Thompson, Darby J S

AU - Haddad, Zaid

AU - Zimmermann, Benedikt

AU - Sierocinski, Thomas

AU - Triche, Timothy J.

AU - Kollmeyer, Thomas

AU - Ballman, Karla V.

AU - Black, Peter C.

AU - Klee, George G.

AU - Jenkins, Robert Brian

PY - 2013/12

Y1 - 2013/12

N2 - Purpose: Patients with locally advanced prostate cancer after radical prostatectomy are candidates for secondary therapy. However, this higher risk population is heterogeneous. Many cases do not metastasize even when conservatively managed. Given the limited specificity of pathological features to predict metastasis, newer risk prediction models are needed. We report a validation study of a genomic classifier that predicts metastasis after radical prostatectomy in a high risk population. Materials and Methods: A case-cohort design was used to sample 1,010 patients after radical prostatectomy at high risk for recurrence who were treated from 2000 to 2006. Patients had preoperative prostate specific antigen greater than 20 ng/ml, Gleason 8 or greater, pT3b or a Mayo Clinic nomogram score of 10 or greater. Patients with metastasis at diagnosis or any prior treatment for prostate cancer were excluded from analysis. A 20% random sampling created a subcohort that included all patients with metastasis. We generated 22-marker genomic classifier scores for 219 patients with available genomic data. ROC and decision curves, competing risk and weighted regression models were used to assess genomic classifier performance. Results: The genomic classifier AUC was 0.79 for predicting 5-year metastasis after radical prostatectomy. Decision curves showed that the genomic classifier net benefit exceeded that of clinical only models. The genomic classifier was the predominant predictor of metastasis on multivariable analysis. The cumulative incidence of metastasis 5 years after radical prostatectomy was 2.4%, 6.0% and 22.5% in patients with low (60%), intermediate (21%) and high (19%) genomic classifier scores, respectively (p <0.001). Conclusions: Results indicate that genomic information from the primary tumor can identify patients with adverse pathological features who are most at risk for metastasis and potentially lethal prostate cancer.

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KW - Neoplasm metastasis

KW - Prognosis

KW - Prostate

KW - Prostatic neoplasms

KW - Transcriptome

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