Change search
ReferencesLink to record
Permanent link

Direct link
Common genetic variants in prostate cancer risk prediction-results from the NCI breast and prostate cancer cohort consortium (BPC3)
Show others and affiliations
2012 (English)In: Cancer Epidemiology, Biomarkers and Prevention, ISSN 1055-9965, E-ISSN 1538-7755, Vol. 21, no 3, 437-444 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2012. Vol. 21, no 3, 437-444 p.
National Category
Cancer and Oncology
URN: urn:nbn:se:umu:diva-53868DOI: 10.1158/1055-9965.EPI-11-1038ISI: 000301284100007OAI: diva2:514712
Available from: 2012-04-10 Created: 2012-04-04 Last updated: 2016-03-07Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Johansson, Mattias
By organisation
Urology and Andrology
In the same journal
Cancer Epidemiology, Biomarkers and Prevention
Cancer and Oncology

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 39 hits
ReferencesLink to record
Permanent link

Direct link