Tissue-based Genomics Augments Post-prostatectomy Risk Stratification in a Natural History Cohort of Intermediate- and High-Risk Men

European Urology

Volumn 69, Issue 1, 2016, Pages 157-165

  Ross, Ashley E ^a   Johnson, Michael H ^a   Yousefi, Kasra ^b   Davicioni, Elai ^b   Netto, George J ^a   Marchionni, Luigi ^a   Fedor, Helen L ^a   Glavaris, Stephanie ^a   Choeurng, Voleak ^b   Buerki, Christine ^b   Erho, Nicholas ^b   Lam, Lucia L ^b   Humphreys, Elizabeth B ^a   Faraj, Sheila ^a   Bezerra, Stephania M ^a   Han, Misop ^a   Partin, Alan W ^a   Trock, Bruce J ^a   Schaeffer, Edward M ^a  

^a JOHNS HOPKINS HOSPITAL   (United States)

^b GenomeDx Biosciences Inc   (Canada)

Author keywords

Genomic classifier; Metastasis; Prognosis; Prostate cancer; Transcriptome

Indexed keywords

PROSTATE SPECIFIC ANTIGEN; RNA;

ADULT; ARTICLE; ASSESSMENT OF HUMANS; CANCER ADJUVANT THERAPY; CANCER GROWTH; CANCER INCIDENCE; CANCER MORTALITY; CANCER PATIENT; CANCER PROGNOSIS; CANCER RISK; CANCER STAGING; COHORT ANALYSIS; COMPARATIVE STUDY; DECIPHER SCORE; FOLLOW UP; GENOMICS; GLEASON SCORE; HIGH RISK PATIENT; HISTORY; HUMAN; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; OUTCOME ASSESSMENT; POSTOPERATIVE CARE; PREDICTION; PRIORITY JOURNAL; PROSTATE CANCER; PROSTATECTOMY; QUALITY CONTROL; RETROSPECTIVE STUDY; SALVAGE THERAPY; SURGICAL PATIENT; BLOOD; CANCER GRADING; CASE CONTROL STUDY; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENETICS; METASTASIS; MORTALITY; PATHOLOGY; POSTOPERATIVE PERIOD; PROGNOSIS; PROSTATIC NEOPLASMS; RECEIVER OPERATING CHARACTERISTIC; RISK ASSESSMENT;

CASE-CONTROL STUDIES; GENE EXPRESSION PROFILING; GENOMICS; HUMANS; MALE; MIDDLE AGED; NEOPLASM GRADING; NEOPLASM METASTASIS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; POSTOPERATIVE PERIOD; PROGNOSIS; PROSTATE-SPECIFIC ANTIGEN; PROSTATECTOMY; PROSTATIC NEOPLASMS; RETROSPECTIVE STUDIES; RISK ASSESSMENT; RNA; ROC CURVE;

EID: 84955660212     PISSN: 03022838     EISSN: 18737560     Source Type: Journal    
DOI: 10.1016/j.eururo.2015.05.042     Document Type: Article

References (37)

1. Ross AE, Yousefi K, Davicioni E, et al. Utility of risk models in decision making after radical prostatectomy: lessons from a natural history cohort of intermediate- and high-risk men. Eur Urol. In press. http://dx.doi.org/10.1016/j.eururo.2015.04.016
2. J.W. Davis Novel commercially available genomic tests for prostate cancer: a roadmap to understanding their clinical impact BJU Int 114 2014 320 322
3. N. Erho, A. Crisan, I.A. Vergara, and et al. Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy PLoS One 8 2013 e66855
4. R.J. Karnes, E.J. Bergstralh, E. Davicioni, and et al. Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk patient population J Urol 190 2013 2047 2053
5. R.B. Den, F.Y. Feng, T.N. Showalter, and et al. Genomic prostate cancer classifier predicts biochemical failure and metastases in patients after postoperative radiation therapy Int J Radiat Oncol Biol Phys 89 2014 1038 1046
6. E.A. Klein, K. Yousefi, Z. Haddad, and et al. A genomic classifier improves prediction of metastatic disease within 5 years after surgery in node-negative high-risk prostate cancer patients managed by radical prostatectomy without adjuvant therapy Eur Urol 67 2015 778 786
7. R.B. Den, K. Yousefi, E.J. Trabulsi, and et al. Genomic classifier identifies men with adverse pathology after radical prostatectomy who benefit from adjuvant radiation therapy J Clin Oncol 33 2015 944 951
8. W.E. Barlow, L. Ichikawa, D. Rosner, and S. Izumi Analysis of case-cohort designs J Clin Epidemiol 52 1999 1165 1172
9. L.H. Sobin, and C.C. Compton TNM seventh edition: what's new, what's changed: communication from the International Union Against Cancer and the American Joint Committee on Cancer Cancer 116 2010 5336 5339
10. J.I. Epstein, W.C. Allsbrook, M.B. Amin, and L.L. Egevad The 2005 International Society of Urological Pathology (ISUP) consensus conference on Gleason grading of prostatic carcinoma Am J Surg Pathol 29 2005 1228 1242
11. M.S. Pepe, Z. Feng, H. Janes, P.M. Bossuyt, and J.D. Potter Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design J Natl Cancer Inst 100 2008 1432 1438
12. L.M. McShane, D.G. Altman, W. Sauerbrei, S.E. Taube, M. Gion, and G.M. Clark REporting recommendations for tumor MARKer prognostic studies (REMARK) Breast Cancer Res Treat 100 2006 229 235
13. H.E. Lockstone Exon array data analysis using Affymetrix power tools and R statistical software Brief Bioinform 12 2011 634 644
14. S.R. Piccolo, Y. Sun, J.D. Campbell, M.E. Lenburg, A.H. Bild, and W.E. Johnson A single-sample microarray normalization method to facilitate personalized-medicine workflows Genomics 100 2012 337 344
15. Cheourng V, Luo B, Yousefi K, et al. Re-calibration of genomic risk prediction models in prostate cancer to improve individual-level predictions. Presentation at the 2015 Joint Statistical Meeting. http://www.amstat.org/meetings/jsm/2015/onlineprogram/AbstractDetails.cfm?abstractid=317374
16. D.G. Altman, b. Lausen, W. Sauerbrei, and M. Schumacher Dangers of using "optimal" cutpoints in the evaluation of prognostic factors J Natl Cancer Inst 86 1994 829 835
17. A.J. Vickers, and D.D. Sjoberg Guidelines for reporting of statistics in European Urology Eur Urol 67 2015 181 187
18. M.R. Cooperberg, J.F. Hilton, and P.R. Carroll The CAPRA-S score: a straightforward tool for improved prediction of outcomes after radical prostatectomy Cancer 117 2011 5039 5046
19. S.E. Eggener, P.T. Scardino, P.C. Walsh, and et al. Predicting 15-year prostate cancer specific mortality after radical prostatectomy J Urol 185 2011 869 875
20. D.Y. Lin, and Z. Ying Cox regression with incomplete covariate measurements J Am Stat Assoc 88 1993 1341 1349
21. T.M. Therneau, and H. Li Computing the Cox model for case cohort designs Lifetime Data Anal 5 1999 99 112
22. J.P. Fine, and R.J. Gray A Proportional hazards model for the subdistribution of a competing risk J Am Stat Assoc 94 1999 496 509
23. P.J. Heagerty, T. Lumley, and M.S. Pepe Time-dependent ROC curves for censored survival data and a diagnostic marker Biometrics 56 2000 337 344
24. A.J. Vickers, A.M. Cronin, E.B. Elkin, and M. Gonen Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers BMC Med Inform Decis Mak 8 2008 53
25. A. Ganna, M. Reilly, U. de Faire, N. Pedersen, P. Magnusson, and E. Ingelsson Risk prediction measures for case-cohort and nested case-control designs: an application to cardiovascular disease Am J Epidemiol 175 2012 715 724
26. B.-X. Xie, H. Zhang, J. Wang, and et al. Analysis of differentially expressed genes in LNCaP prostate cancer progression model J Androl 32 2011 170 182
27. J.C. Cheville, R.J. Karnes, T.M. Therneau, and et al. Gene panel model predictive of outcome in men at high-risk of systemic progression and death from prostate cancer after radical retropubic prostatectomy J Clin Oncol 26 2008 3930 3936
28. E.A. Klein, M.R. Cooperberg, C. Magi-Galluzzi, and et al. A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling Eur Urol 66 2014 550 560
29. L.H. Saal, P. Johansson, K. Holm, and et al. Poor prognosis in carcinoma is associated with a gene expression signature of aberrant PTEN tumor suppressor pathway activity Proc Natl Acad Sci U S A 104 2007 7564 7569
30. J.M. D'Antonio, C. Ma, F.A. Monzon, and B.R. Pflug Longitudinal analysis of androgen deprivation of prostate cancer cells identifies pathways to androgen independence Prostate 68 2008 698 714
31. Q. Long, B.A. Johnson, A.O. Osunkoya, and et al. Protein-coding and microRNA biomarkers of recurrence of prostate cancer following radical prostatectomy Am J Pathol 179 2011 46 54
32. S.A. Eschrich, J. Pramana, H. Zhang, and et al. A gene expression model of intrinsic tumor radiosensitivity: prediction of response and prognosis after chemoradiation Int J Radiat Oncol Biol Phys 75 2009 489 496
33. S. Irshad, M. Bansal, M. Castillo-Martin, and et al. A molecular signature predictive of indolent prostate cancer Sci Transl Med 5 2013 202ra122
34. K.L. Penney, J.A. Sinnott, K. Fall, and et al. mRNA expression signature of Gleason grade predicts lethal prostate cancer J Clin Oncol 29 2011 2391 2396
35. P.R. Womble, J.E. Montie, Z. Ye, and et al. Contemporary use of initial active surveillance among men in Michigan with low-risk prostate cancer Eur Urol 67 2015 44 50
36. M.R. Cooperberg, E. Davicioni, A. Crisan, R.B. Jenkins, M. Ghadessi, and R.J. Karnes Combined value of validated clinical and genomic risk stratification tools for predicting prostate cancer mortality in a high-risk prostatectomy cohort Eur Urol 67 2015 326 333
37. C.R. Pound, A.W. Partin, M.A. Eisenberger, D.W. Chan, J.D. Pearson, and P.C. Walsh Natural history of progression after PSA elevation following radical prostatectomy JAMA 281 1999 1591 1597