Literature DB >> 22237985

Common genetic variants in prostate cancer risk prediction--results from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3).

Sara Lindström1, Fredrick R Schumacher, David Cox, Ruth C Travis, Demetrius Albanes, Naomi E Allen, Gerald Andriole, Sonja I Berndt, Heiner Boeing, H Bas Bueno-de-Mesquita, E David Crawford, W Ryan Diver, J Michael Gaziano, Graham G Giles, Edward Giovannucci, Carlos A Gonzalez, Brian Henderson, David J Hunter, Mattias Johansson, Laurence N Kolonel, Jing Ma, Loïc Le Marchand, Valeria Pala, Meir Stampfer, Daniel O Stram, Michael J Thun, Anne Tjonneland, Dimitrios Trichopoulos, Jarmo Virtamo, Stephanie J Weinstein, Walter C Willett, Meredith Yeager, Richard B Hayes, Gianluca Severi, Christopher A Haiman, Stephen J Chanock, Peter Kraft.   

Abstract

BACKGROUND: One of the goals of personalized medicine is to generate individual risk profiles that could identify individuals in the population that exhibit high risk. The discovery of more than two-dozen independent single-nucleotide polymorphism markers in prostate cancer has raised the possibility for such risk stratification. In this study, we evaluated the discriminative and predictive ability for prostate cancer risk models incorporating 25 common prostate cancer genetic markers, family history of prostate cancer, and age.
METHODS: We fit a series of risk models and estimated their performance in 7,509 prostate cancer cases and 7,652 controls within the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also calculated absolute risks based on SEER incidence data.
RESULTS: The best risk model (C-statistic = 0.642) included individual genetic markers and family history of prostate cancer. We observed a decreasing trend in discriminative ability with advancing age (P = 0.009), with highest accuracy in men younger than 60 years (C-statistic = 0.679). The absolute ten-year risk for 50-year-old men with a family history ranged from 1.6% (10th percentile of genetic risk) to 6.7% (90th percentile of genetic risk). For men without family history, the risk ranged from 0.8% (10th percentile) to 3.4% (90th percentile).
CONCLUSIONS: Our results indicate that incorporating genetic information and family history in prostate cancer risk models can be particularly useful for identifying younger men that might benefit from prostate-specific antigen screening. IMPACT: Although adding genetic risk markers improves model performance, the clinical utility of these genetic risk models is limited. ©2012 AACR.

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Year:  2012        PMID: 22237985      PMCID: PMC3318963          DOI: 10.1158/1055-9965.EPI-11-1038

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  30 in total

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4.  Cancer statistics, 2010.

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5.  Genetic correction of PSA values using sequence variants associated with PSA levels.

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Review 9.  The comparability of models for predicting the risk of a positive prostate biopsy with prostate-specific antigen alone: a systematic review.

Authors:  Fritz Schröder; Michael W Kattan
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10.  Multiple newly identified loci associated with prostate cancer susceptibility.

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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  35 in total

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Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2015-12-15       Impact factor: 4.254

2.  Randomized trial finds that prostate cancer genetic risk score feedback targets prostate-specific antigen screening among at-risk men.

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3.  Utility of single nucleotide polymorphisms in prostate biopsy decisions.

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Journal:  Rev Urol       Date:  2012

4.  Prostate cancer (PCa) risk variants and risk of fatal PCa in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium.

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Journal:  Eur Urol       Date:  2014-01-04       Impact factor: 20.096

5.  Familial prostate cancer.

Authors:  Veda N Giri; Jennifer L Beebe-Dimmer
Journal:  Semin Oncol       Date:  2016-08-18       Impact factor: 4.929

Review 6.  A genetic-based approach to personalized prostate cancer screening and treatment.

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7.  Testing for the recurrent HOXB13 G84E germline mutation in men with clinical indications for prostate biopsy.

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Review 8.  Prostate cancer in young men: an important clinical entity.

Authors:  Claudia A Salinas; Alex Tsodikov; Miriam Ishak-Howard; Kathleen A Cooney
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9.  Adding genetic risk score to family history identifies twice as many high-risk men for prostate cancer: Results from the prostate cancer prevention trial.

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10.  The role of lifestyle characteristics on prostate cancer progression in two active surveillance cohorts.

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