BACKGROUND: Several germline single nucleotide polymorphisms (SNPs) have been consistently associated with prostate cancer (PCa) risk. OBJECTIVE: To determine whether there is an improvement in PCa risk prediction by adding these SNPs to existing predictors of PCa. DESIGN, SETTING, AND PARTICIPANTS: Subjects included men in the placebo arm of the randomized Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial in whom germline DNA was available. All men had an initial negative prostate biopsy and underwent study-mandated biopsies at 2 yr and 4 yr. Predictive performance of baseline clinical parameters and/or a genetic score based on 33 established PCa risk-associated SNPs was evaluated. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Area under the receiver operating characteristic curves (AUC) were used to compare different models with different predictors. Net reclassification improvement (NRI) and decision curve analysis (DCA) were used to assess changes in risk prediction by adding genetic markers. RESULTS AND LIMITATIONS: Among 1654 men, genetic score was a significant predictor of positive biopsy, even after adjusting for known clinical variables and family history (p = 3.41 × 10(-8)). The AUC for the genetic score exceeded that of any other PCa predictor at 0.59. Adding the genetic score to the best clinical model improved the AUC from 0.62 to 0.66 (p<0.001), reclassified PCa risk in 33% of men (NRI: 0.10; p=0.002), resulted in higher net benefit from DCA, and decreased the number of biopsies needed to detect the same number of PCa instances. The benefit of adding the genetic score was greatest among men at intermediate risk (25th percentile to 75th percentile). Similar results were found for high-grade (Gleason score ≥ 7) PCa. A major limitation of this study was its focus on white patients only. CONCLUSIONS: Adding genetic markers to current clinical parameters may improve PCa risk prediction. The improvement is modest but may be helpful for better determining the need for repeat prostate biopsy. The clinical impact of these results requires further study.
BACKGROUND: Several germline single nucleotide polymorphisms (SNPs) have been consistently associated with prostate cancer (PCa) risk. OBJECTIVE: To determine whether there is an improvement in PCa risk prediction by adding these SNPs to existing predictors of PCa. DESIGN, SETTING, AND PARTICIPANTS: Subjects included men in the placebo arm of the randomized Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial in whom germline DNA was available. All men had an initial negative prostate biopsy and underwent study-mandated biopsies at 2 yr and 4 yr. Predictive performance of baseline clinical parameters and/or a genetic score based on 33 established PCa risk-associated SNPs was evaluated. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Area under the receiver operating characteristic curves (AUC) were used to compare different models with different predictors. Net reclassification improvement (NRI) and decision curve analysis (DCA) were used to assess changes in risk prediction by adding genetic markers. RESULTS AND LIMITATIONS: Among 1654 men, genetic score was a significant predictor of positive biopsy, even after adjusting for known clinical variables and family history (p = 3.41 × 10(-8)). The AUC for the genetic score exceeded that of any other PCa predictor at 0.59. Adding the genetic score to the best clinical model improved the AUC from 0.62 to 0.66 (p<0.001), reclassified PCa risk in 33% of men (NRI: 0.10; p=0.002), resulted in higher net benefit from DCA, and decreased the number of biopsies needed to detect the same number of PCa instances. The benefit of adding the genetic score was greatest among men at intermediate risk (25th percentile to 75th percentile). Similar results were found for high-grade (Gleason score ≥ 7) PCa. A major limitation of this study was its focus on white patients only. CONCLUSIONS: Adding genetic markers to current clinical parameters may improve PCa risk prediction. The improvement is modest but may be helpful for better determining the need for repeat prostate biopsy. The clinical impact of these results requires further study.
Authors: Julius Gudmundsson; Patrick Sulem; Thorunn Rafnar; Jon T Bergthorsson; Andrei Manolescu; Daniel Gudbjartsson; Bjarni A Agnarsson; Asgeir Sigurdsson; Kristrun R Benediktsdottir; Thorarinn Blondal; Margret Jakobsdottir; Simon N Stacey; Jelena Kostic; Kari T Kristinsson; Birgitta Birgisdottir; Shyamali Ghosh; Droplaug N Magnusdottir; Steinunn Thorlacius; Gudmar Thorleifsson; S Lilly Zheng; Jielin Sun; Bao-Li Chang; J Bradford Elmore; Joan P Breyer; Kate M McReynolds; Kevin M Bradley; Brian L Yaspan; Fredrik Wiklund; Par Stattin; Sara Lindström; Hans-Olov Adami; Shannon K McDonnell; Daniel J Schaid; Julie M Cunningham; Liang Wang; James R Cerhan; Jennifer L St Sauver; Sara D Isaacs; Kathleen E Wiley; Alan W Partin; Patrick C Walsh; Sonia Polo; Manuel Ruiz-Echarri; Sebastian Navarrete; Fernando Fuertes; Berta Saez; Javier Godino; Philip C Weijerman; Dorine W Swinkels; Katja K Aben; J Alfred Witjes; Brian K Suarez; Brian T Helfand; Michael L Frigge; Kristleifur Kristjansson; Carole Ober; Eirikur Jonsson; Gudmundur V Einarsson; Jianfeng Xu; Henrik Gronberg; Jeffrey R Smith; Stephen N Thibodeau; William B Isaacs; William J Catalona; Jose I Mayordomo; Lambertus A Kiemeney; Rosa B Barkardottir; Jeffrey R Gulcher; Unnur Thorsteinsdottir; Augustine Kong; Kari Stefansson Journal: Nat Genet Date: 2008-02-10 Impact factor: 38.330
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Authors: Sheila M J Aubin; Jennifer Reid; Mark J Sarno; Amy Blase; Jacqueline Aussie; Harry Rittenhouse; Roger Rittmaster; Gerald L Andriole; Jack Groskopf Journal: J Urol Date: 2010-09-17 Impact factor: 7.450
Authors: Julius Gudmundsson; Patrick Sulem; Daniel F Gudbjartsson; Thorarinn Blondal; Arnaldur Gylfason; Bjarni A Agnarsson; Kristrun R Benediktsdottir; Droplaug N Magnusdottir; Gudbjorg Orlygsdottir; Margret Jakobsdottir; Simon N Stacey; Asgeir Sigurdsson; Tiina Wahlfors; Teuvo Tammela; Joan P Breyer; Kate M McReynolds; Kevin M Bradley; Berta Saez; Javier Godino; Sebastian Navarrete; Fernando Fuertes; Laura Murillo; Eduardo Polo; Katja K Aben; Inge M van Oort; Brian K Suarez; Brian T Helfand; Donghui Kan; Carlo Zanon; Michael L Frigge; Kristleifur Kristjansson; Jeffrey R Gulcher; Gudmundur V Einarsson; Eirikur Jonsson; William J Catalona; Jose I Mayordomo; Lambertus A Kiemeney; Jeffrey R Smith; Johanna Schleutker; Rosa B Barkardottir; Augustine Kong; Unnur Thorsteinsdottir; Thorunn Rafnar; Kari Stefansson Journal: Nat Genet Date: 2009-09-20 Impact factor: 38.330
Authors: Rosalind A Eeles; Zsofia Kote-Jarai; Ali Amin Al Olama; Graham G Giles; Michelle Guy; Gianluca Severi; Kenneth Muir; John L Hopper; Brian E Henderson; Christopher A Haiman; Johanna Schleutker; Freddie C Hamdy; David E Neal; Jenny L Donovan; Janet L Stanford; Elaine A Ostrander; Sue A Ingles; Esther M John; Stephen N Thibodeau; Daniel Schaid; Jong Y Park; Amanda Spurdle; Judith Clements; Joanne L Dickinson; Christiane Maier; Walther Vogel; Thilo Dörk; Timothy R Rebbeck; Kathleen A Cooney; Lisa Cannon-Albright; Pierre O Chappuis; Pierre Hutter; Maurice Zeegers; Radka Kaneva; Hong-Wei Zhang; Yong-Jie Lu; William D Foulkes; Dallas R English; Daniel A Leongamornlert; Malgorzata Tymrakiewicz; Jonathan Morrison; Audrey T Ardern-Jones; Amanda L Hall; Lynne T O'Brien; Rosemary A Wilkinson; Edward J Saunders; Elizabeth C Page; Emma J Sawyer; Stephen M Edwards; David P Dearnaley; Alan Horwich; Robert A Huddart; Vincent S Khoo; Christopher C Parker; Nicholas Van As; Christopher J Woodhouse; Alan Thompson; Tim Christmas; Chris Ogden; Colin S Cooper; Melissa C Southey; Artitaya Lophatananon; Jo-Fen Liu; Laurence N Kolonel; Loic Le Marchand; Tiina Wahlfors; Teuvo L Tammela; Anssi Auvinen; Sarah J Lewis; Angela Cox; Liesel M FitzGerald; Joseph S Koopmeiners; Danielle M Karyadi; Erika M Kwon; Mariana C Stern; Roman Corral; Amit D Joshi; Ahva Shahabi; Shannon K McDonnell; Thomas A Sellers; Julio Pow-Sang; Suzanne Chambers; Joanne Aitken; R A Frank Gardiner; Jyotsna Batra; Mary Anne Kedda; Felicity Lose; Andrea Polanowski; Briony Patterson; Jürgen Serth; Andreas Meyer; Manuel Luedeke; Klara Stefflova; Anna M Ray; Ethan M Lange; Jim Farnham; Humera Khan; Chavdar Slavov; Atanaska Mitkova; Guangwen Cao; Douglas F Easton Journal: Nat Genet Date: 2009-09-20 Impact factor: 38.330
Authors: A Karim Kader; Jielin Sun; Sarah D Isaacs; Kathleen E Wiley; Guifang Yan; Seong-Tae Kim; Helen Fedor; Angelo M DeMarzo; Jonathan I Epstein; Patrick C Walsh; Alan W Partin; Bruce Trock; S Lilly Zheng; Jianfeng Xu; William Isaacs Journal: Prostate Date: 2009-08-01 Impact factor: 4.104
Authors: Rosalind A Eeles; Zsofia Kote-Jarai; Graham G Giles; Ali Amin Al Olama; Michelle Guy; Sarah K Jugurnauth; Shani Mulholland; Daniel A Leongamornlert; Stephen M Edwards; Jonathan Morrison; Helen I Field; Melissa C Southey; Gianluca Severi; Jenny L Donovan; Freddie C Hamdy; David P Dearnaley; Kenneth R Muir; Charmaine Smith; Melisa Bagnato; Audrey T Ardern-Jones; Amanda L Hall; Lynne T O'Brien; Beatrice N Gehr-Swain; Rosemary A Wilkinson; Angie Cox; Sarah Lewis; Paul M Brown; Sameer G Jhavar; Malgorzata Tymrakiewicz; Artitaya Lophatananon; Sarah L Bryant; Alan Horwich; Robert A Huddart; Vincent S Khoo; Christopher C Parker; Christopher J Woodhouse; Alan Thompson; Tim Christmas; Chris Ogden; Cyril Fisher; Charles Jamieson; Colin S Cooper; Dallas R English; John L Hopper; David E Neal; Douglas F Easton Journal: Nat Genet Date: 2008-02-10 Impact factor: 38.330
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