title: A review of cancer risk prediction models with genetic variants.
abstract: Cancer risk prediction models are important in identifying individuals at high risk of developing cancer, which could result in targeted screening and interventions to maximize the treatment benefit and minimize the burden of cancer. The cancer-associated genetic variants identified in genome-wide or candidate gene association studies have been shown to collectively enhance cancer risk prediction, improve our understanding of carcinogenesis, and possibly result in the development of targeted treatments for patients. In this article, we review the cancer risk prediction models that have been developed for popular cancers and assess their applicability, strengths, and weaknesses. We also discuss the factors to be considered for future development and improvement of models for cancer risk prediction.
authors.affiliation: Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
authors.forename: Xuexia
authors.initials: X
authors.lastname: Wang
authors.affiliation: Criminology and Anthropology Department, University of Wisconsin-Whitewater, Whitewater, WI, USA.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Oldani
authors.affiliation: Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
authors.forename: Xingwang
authors.initials: X
authors.lastname: Zhao
authors.affiliation: Sanofi-Aventis, Bridgewater, NJ, USA.
authors.forename: Xiaohui
authors.initials: X
authors.lastname: Huang
authors.affiliation: City of Hope, Durate, CA, USA.
authors.forename: Dajun
authors.initials: D
authors.lastname: Qian
keywords: cancer; cancer intervention; cancer risk prediction; genetic variants; risk prediction models