Literature DB >> 28400167

Validation of a Genomic Risk Classifier to Predict Prostate Cancer-specific Mortality in Men with Adverse Pathologic Features.

R Jeffrey Karnes1, Voleak Choeurng2, Ashley E Ross3, Edward M Schaeffer4, Eric A Klein5, Stephen J Freedland6, Nicholas Erho2, Kasra Yousefi2, Mandeep Takhar2, Elai Davicioni2, Matthew R Cooperberg7, Bruce J Trock8.   

Abstract

BACKGROUND: Risk of prostate cancer-specific mortality (PCSM) is highly variable for men with adverse pathologic features at radical prostatectomy (RP); a majority will die of other causes. Accurately stratifying PCSM risk can improve therapy decisions.
OBJECTIVE: Validate the 22 gene Decipher genomic classifier (GC) to predict PCSM in men with adverse pathologic features after RP. DESIGN, SETTING, AND PARTICIPANTS: Men with adverse pathologic features: pT3, pN1, positive margins, or Gleason score >7 who underwent RP in 1987-2010 at Johns Hopkins, Cleveland Clinic, Mayo Clinic, and Durham Veteran's Affairs Hospital. We also analyzed subgroups at high risk (prostate-specific antigen >20 ng/ml, RP Gleason score 8-10, or stage >pT3b), or very high risk of PCSM (biochemical recurrence in<2 yr [BCR2], or men who developed metastasis after RP [MET]). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Logistic regression evaluated the association of GC with PCSM within 10 yr of RP (PCSM10), adjusted for the Cancer of the Prostate Risk Assessment Postsurgical Score (CAPRA-S). GC performance was evaluated with area under the receiver operating characteristic curve (AUC) and decision curves. RESULTS AND LIMITATIONS: Five hundred and sixty-one men (112 with PCSM10), median follow-up 13.0 yr (patients without PCSM10). For high GC score (> 0.6) versus low-intermediate (≤ 0.6), the odds ratio for PCSM10 adjusted for CAPRA-S was 3.91 (95% confidence interval: 2.43-6.29), with AUC=0.77, an increase of 0.04 compared with CAPRA-S. Subgroup odds ratios were 3.96, 3.06, and 1.95 for high risk, BCR2, or MET, respectively (all p<0.05), with AUCs 0.64-0.72. GC stratified cumulative PCSM10 incidence from 2.8% to 30%. Combined use of case-control and cohort data is a potential limitation.
CONCLUSIONS: In a large cohort with the longest follow-up to date, Decipher GC demonstrated clinically important prediction of PCSM at 10 yr, independent of CAPRA-S, in men with adverse pathologic features, BCR2, or MET after RP. PATIENT
SUMMARY: Decipher genomic classifier may improve treatment decision-making for men with adverse or high risk pathology after radical prostatectomy.
Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Adverse pathologic features; CAPRA-S; Genomic classifier; Prostate cancer-specific mortality; Radical prostatectomy

Mesh:

Year:  2017        PMID: 28400167      PMCID: PMC5632569          DOI: 10.1016/j.eururo.2017.03.036

Source DB:  PubMed          Journal:  Eur Urol        ISSN: 0302-2838            Impact factor:   20.096


  27 in total

Review 1.  Multidisciplinary intervention of early, lethal metastatic prostate cancer: Report from the 2015 Coffey-Holden Prostate Cancer Academy Meeting.

Authors:  Andrea K Miyahira; Joshua M Lang; Robert B Den; Isla P Garraway; Tamara L Lotan; Ashley E Ross; Tanya Stoyanova; Steve Y Cho; Jonathan W Simons; Kenneth J Pienta; Howard R Soule
Journal:  Prostate       Date:  2015-10-19       Impact factor: 4.104

2.  The CAPRA-S score: A straightforward tool for improved prediction of outcomes after radical prostatectomy.

Authors:  Matthew R Cooperberg; Joan F Hilton; Peter R Carroll
Journal:  Cancer       Date:  2011-06-03       Impact factor: 6.860

Review 3.  Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.

Authors:  F E Harrell; K L Lee; D B Mark
Journal:  Stat Med       Date:  1996-02-28       Impact factor: 2.373

4.  Declining Use of Radiotherapy for Adverse Features After Radical Prostatectomy: Results From the National Cancer Data Base.

Authors:  Helmneh M Sineshaw; Phillip J Gray; Jason A Efstathiou; Ahmedin Jemal
Journal:  Eur Urol       Date:  2015-04-18       Impact factor: 20.096

5.  Predicting 15-year prostate cancer specific mortality after radical prostatectomy.

Authors:  Scott E Eggener; Peter T Scardino; Patrick C Walsh; Misop Han; Alan W Partin; Bruce J Trock; Zhaoyong Feng; David P Wood; James A Eastham; Ofer Yossepowitch; Danny M Rabah; Michael W Kattan; Changhong Yu; Eric A Klein; Andrew J Stephenson
Journal:  J Urol       Date:  2011-01-15       Impact factor: 7.450

6.  Decision curve analysis: a novel method for evaluating prediction models.

Authors:  Andrew J Vickers; Elena B Elkin
Journal:  Med Decis Making       Date:  2006 Nov-Dec       Impact factor: 2.583

7.  Overdetection of recurrence after radical prostatectomy: estimates based on patient and tumor characteristics.

Authors:  Jing Xia; Bruce J Trock; Roman Gulati; Leslie Mallinger; Matthew R Cooperberg; Peter R Carroll; H Ballentine Carter; Ruth Etzioni
Journal:  Clin Cancer Res       Date:  2014-10-15       Impact factor: 12.531

8.  Combined value of validated clinical and genomic risk stratification tools for predicting prostate cancer mortality in a high-risk prostatectomy cohort.

Authors:  Matthew R Cooperberg; Elai Davicioni; Anamaria Crisan; Robert B Jenkins; Mercedeh Ghadessi; R Jeffrey Karnes
Journal:  Eur Urol       Date:  2014-07-02       Impact factor: 20.096

9.  A single-sample microarray normalization method to facilitate personalized-medicine workflows.

Authors:  Stephen R Piccolo; Ying Sun; Joshua D Campbell; Marc E Lenburg; Andrea H Bild; W Evan Johnson
Journal:  Genomics       Date:  2012-08-19       Impact factor: 5.736

10.  Exon array data analysis using Affymetrix power tools and R statistical software.

Authors:  Helen E Lockstone
Journal:  Brief Bioinform       Date:  2011-04-15       Impact factor: 11.622

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  13 in total

1.  Correlation between MRI phenotypes and a genomic classifier of prostate cancer: preliminary findings.

Authors:  Andrei S Purysko; Cristina Magi-Galluzzi; Omar Y Mian; Sarah Sittenfeld; Elai Davicioni; Marguerite du Plessis; Christine Buerki; Jennifer Bullen; Lin Li; Anant Madabhushi; Andrew Stephenson; Eric A Klein
Journal:  Eur Radiol       Date:  2019-03-07       Impact factor: 5.315

2.  Performance of a Prostate Cancer Genomic Classifier in Predicting Metastasis in Men with Prostate-specific Antigen Persistence Postprostatectomy.

Authors:  Daniel E Spratt; Darlene L Y Dai; Robert B Den; Patricia Troncoso; Kasra Yousefi; Ashley E Ross; Edward M Schaeffer; Zaid Haddad; Elai Davicioni; Rohit Mehra; Todd M Morgan; Walter Rayford; Firas Abdollah; Edouard Trabulsi; Mary Achim; Elsa Li Ning Tapia; Mireya Guerrero; Robert Jeffrey Karnes; Adam P Dicker; Mark A Hurwitz; Paul L Nguyen; Felix F Y Feng; Stephen J Freedland; John W Davis
Journal:  Eur Urol       Date:  2017-12-10       Impact factor: 20.096

3.  Variation in Molecularly Defined Prostate Tumor Subtypes by Self-identified Race.

Authors:  Kevin H Kensler; Shivanshu Awasthi; Mohamed Alshalalfa; Bruce J Trock; Stephen J Freedland; Michael R Freeman; Sungyong You; Brandon A Mahal; Robert B Den; Adam P Dicker; R Jeffrey Karnes; Eric A Klein; Priti Lal; Yang Liu; Elai Davicioni; Walter Rayford; Kosj Yamoah; Timothy R Rebbeck
Journal:  Eur Urol Open Sci       Date:  2022-04-26

4.  Predicting prostate cancer specific-mortality with artificial intelligence-based Gleason grading.

Authors:  Ellery Wulczyn; Kunal Nagpal; Matthew Symonds; Melissa Moran; Markus Plass; Robert Reihs; Farah Nader; Fraser Tan; Yuannan Cai; Trissia Brown; Isabelle Flament-Auvigne; Mahul B Amin; Martin C Stumpe; Heimo Müller; Peter Regitnig; Andreas Holzinger; Greg S Corrado; Lily H Peng; Po-Hsuan Cameron Chen; David F Steiner; Kurt Zatloukal; Yun Liu; Craig H Mermel
Journal:  Commun Med (Lond)       Date:  2021-06-30

5.  A Novel Risk Score (P-score) Based on a Three-Gene Signature, for Estimating the Risk of Prostate Cancer-Specific Mortality.

Authors:  Fabian Söderdahl; Li-Di Xu; Johan Bring; Michael Häggman
Journal:  Res Rep Urol       Date:  2022-05-11

6.  Tissue-based biomarkers in prostate cancer.

Authors:  Timothy N Clinton; Aditya Bagrodia; Yair Lotan; Vitaly Margulis; Ganesh V Raj; Solomon L Woldu
Journal:  Expert Rev Precis Med Drug Dev       Date:  2017-09-05

Review 7.  Men with a susceptibility to prostate cancer and the role of genetic based screening.

Authors:  Rosalind Eeles; Holly Ni Raghallaigh
Journal:  Transl Androl Urol       Date:  2018-02

8.  Prediction of major depressive disorder onset in college students.

Authors:  David D Ebert; Claudia Buntrock; Philippe Mortier; Randy Auerbach; Kiona K Weisel; Ronald C Kessler; Pim Cuijpers; Jennifer G Green; Glenn Kiekens; Matthew K Nock; Koen Demyttenaere; Ronny Bruffaerts
Journal:  Depress Anxiety       Date:  2018-12-06       Impact factor: 6.505

9.  Assessment of biochemical recurrence of prostate cancer (Review).

Authors:  Xiaozeng Lin; Anil Kapoor; Yan Gu; Mathilda Jing Chow; Hui Xu; Pierre Major; Damu Tang
Journal:  Int J Oncol       Date:  2019-10-04       Impact factor: 5.650

Review 10.  Tissue-Based Biomarkers for the Risk Stratification of Men With Clinically Localized Prostate Cancer.

Authors:  Spyridon P Basourakos; Michael Tzeng; Patrick J Lewicki; Krishnan Patel; Bashir Al Hussein Al Awamlh; Siv Venkat; Jonathan E Shoag; Michael A Gorin; Christopher E Barbieri; Jim C Hu
Journal:  Front Oncol       Date:  2021-05-28       Impact factor: 6.244

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