Risk assessment models limited in predicting development of breast cancer

Current breast cancer risk assessment tools cannot sufficiently determine who will develop breast cancer; therefore, models should integrate new risk factors and newly discovered genetic variants and be revalidated, according to a recent review.

Researchers aimed to provide clinicians with an overview of available risk assessment models. They examined the Gail, Claus, BRCAPRO, Jonker, International Breast Cancer Intervention Study (IBIS), and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) models.

All of the models had major limitations, according to the researchers. For example, although findings from studies have shown that up to 60% of breast cancers arise in the absence of any known risk factors, most models rely on known risk factors.

Additionally, none of the six models, except for the Gail model, has been extensively validated, and most do not include nonhereditary factors. Also, the Gail model’s ability to distinguish between individuals at risk is limited, particularly for those at high risk, according to the researchers.

Future improvements may include conducting new genome-based research and studies examining additional risk factors, such as breast density, weight gain and hormone levels.

Mitchell H. Gail, MD, PhD,and Phuong L. Mai, MD, said the review offers a useful and informative summary of the six models, but the models differ in important details, and physicians should be aware of these differences.

“Thus, continuing efforts are needed to improve and assess risk models so that they can play a useful role in concert with preventive interventions in reducing the burden of breast cancer,” Gail and Mai said.

Gail is senior investigator and Mai is staff clinician in the division of cancer and epidemiology and genetics at the National Cancer Institute, Bethesda, Md.

Amir E. J Natl Cancer Inst. 2010;102:doi.10.1093/jnci/djq088.

Gail MH. J Natl Cancer Inst. 2010; 102:doi:10.1093/jnci/djq141.