Performance of common genetic variants in breast-cancer risk models

Sholom Wacholder, Patricia Hartge, Ross Prentice, Montserrat Garcia-Closas, Heather Spencer Feigelson, W. Ryan Diver, Michael J. Thun, David G. Cox, Susan E. Hankinson, Peter Kraft, Bernard Rosner, Christine D. Berg, Louise A. Brinton, Jolanta Lissowska, Mark E. Sherman, Rowan Chlebowski, Charles Kooperberg, Rebecca D. Jackson, Dennis W. Buckman, Peter HuiRuth Pfeiffer, Kevin B. Jacobs, Gilles D. Thomas, Robert N. Hoover, Mitchell H. Gail, Stephen J. Chanock, David J. Hunter

Research output: Contribution to journalArticlepeer-review

360 Scopus citations

Abstract

BACKGROUND: Genomewide association studies have identified multiple genetic variants associated with breast cancer. The extent to which these variants add to existing risk-assessment models is unknown. METHODS: We used information on traditional risk factors and 10 common genetic variants associated with breast cancer in 5590 case subjects and 5998 control subjects, 50 to 79 years of age, from four U.S. cohort studies and one case-control study from Poland to fit models of the absolute risk of breast cancer. With the use of receiver-operating-characteristic curve analysis, we calculated the area under the curve (AUC) as a measure of discrimination. By definition, random classification of case and control subjects provides an AUC of 50%; perfect classification provides an AUC of 100%. We calculated the fraction of case subjects in quintiles of estimated absolute risk after the addition of genetic variants to the traditional risk model. RESULTS: The AUC for a risk model with age, study and entry year, and four traditional risk factors was 58.0%; with the addition of 10 genetic variants, the AUC was 61.8%. About half the case subjects (47.2%) were in the same quintile of risk as in a model without genetic variants; 32.5% were in a higher quintile, and 20.4% were in a lower quintile. CONCLUSIONS: The inclusion of newly discovered genetic factors modestly improved the performance of risk models for breast cancer. The level of predicted breast-cancer risk among most women changed little after the addition of currently available genetic information.

Original languageEnglish (US)
Pages (from-to)986-993
Number of pages8
JournalNew England Journal of Medicine
Volume362
Issue number11
DOIs
StatePublished - Mar 18 2010

ASJC Scopus subject areas

  • Medicine(all)

Fingerprint Dive into the research topics of 'Performance of common genetic variants in breast-cancer risk models'. Together they form a unique fingerprint.

Cite this