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What are the available risk assessment methods for breast cancer and how accurate are they?

May 8, 2010

Other than age, the presence of a significant family history of breast cancer is the most important risk factor for developing breast cancer.  However, less than 5% of new cancer diagnoses are hereditary breast cancers.  Women and clinicians need accurate individualized risk assessments to guide their decision-making process on the appropriate care.  In this review, the researchers have provided an overview of available risk assessment methods.

Over the past two decades, a number of statistical models have been developed and validated to assess breast cancer risk. Current risk assessment models, which are based on a combination of risk factors, produce breast cancer risk estimates over a specific time and/or over the lifetime of the individual.  The most widely known and commonly used model is the Gail model.  Designed in 1989, the Gail model uses 6 breast cancer risk factors (i.e., age, hormonal or reproductive history, previous history of breast disease, and family history).  The Gail model is the only model that has been validated in three large population-based databases, but a recent systematic review has shown that the Gail model has limited discriminatory accuracy in individualized risk assessment (Cummings et al. 2009).  The model still needs to be validated in Hispanic women, Asian women, and other subgroups.

Another model used widely is the Claus model.  This model includes a substantially more comprehensive family history of breast cancer than the Gail model.  But the model does not include nonhereditary risk factors (e.g., hormonal or reproductive factors) and the agreement (concordance) between the Gail and Claus models has been relatively poor.  Other risk assessment models such as BRCAPRO, Jonker model, IBIS or the Tyrer-Cuzick model have similar limitations such as not incorporating nonhereditary risk factors and factoring in non-BRCA gene mutations. 

Researchers have tried to validate and compare various BRCA1 and BRCA2 risk estimation models.  But a 2007 study that independently compared these models showed no one model was superior (Parmigiani et al. 2007).  Some models can predict both mutation carriage risk and breast cancer risk, but all have limitations with their reliance on known risk factors, since data show that up to 60% of breast cancer can arise in the absence of any known risk factors.  Other weaknesses in the models include the fact that they incorporate information only about 1st or 2nd degree relatives of the person being assessed.  Some models also do not include mammographic breast density or family history of other types of cancers such as prostate or pancreatic cancers which are known to be influenced by BRCA1 or BRCA2 mutations.  Also, genome-based research will most likely lead to the development of new risk assessment models.  Current models do not incorporate single-nucleotide polymorphisms (SNPs) which have been associated with breast cancer risk.  Ongoing efforts are needed to assess and measure vastly complex gene-gene and gene-environment interactions which will lead to improved individualized risk assessment and care.