On the use of familial aggregation in population-based case probands for calculating penetrance.
BACKGROUND
Estimating the lifetime risk associated with (i.e., the penetrance of) genetic abnormalities that predispose individuals to cancer is important for genetic counseling. (Penetrance may be estimated from the degree of familial aggregation of cancer, that is, the extent to which cancers cluster in families.) Early penetrance studies of BRCA1 and BRCA2 mutations used high-risk families with multiple cases of breast cancer, a study design that led to very high penetrance estimates. However, such studies were subject to potential ascertainment biases. To offset such biases, recent studies have used data from family members of probands ascertained from population-based incident cases of cancer. The use of case probands is, however, also subject to bias because all risk factors are over-represented in case patients. To draw attention to this problem, literature on the penetrance of breast cancer in BRCA1 and BRCA2 carriers is reviewed.


METHODS
A theory is presented to show that the use of case probands is itself biased, leading to inflated penetrance estimates. The strategy is unbiased only if all carriers share an identical risk. Any unexplained heterogeneity of risk caused by unknown genetic or shared environmental factors within families leads to an inflated estimate of penetrance.


RESULTS
Eight published studies using population-based methods are reviewed. All but one of the family-based studies used case probands.


CONCLUSIONS
Penetrance estimates from case proband studies must be inflated if other factors influence breast cancer risk in addition to the specific genetic abnormality. Thus, women with such genetic abnormalities and a strong family history of breast cancer are likely to possess a much higher risk for breast cancer than women with such abnormalities but without a strong family history. Methodologic techniques to improve the prediction of cancer risk are needed.
Memororial Sloan-Kettering Cancer Center, New York, NY 10021, USA. beggc@mskcc.org
Colin B
CB
Begg
D015982:Bias; D001943:Breast Neoplasms / Q000453:epidemiology* / Q000235:genetics*; D005260:Female; D019398:Genes, BRCA1; D024522:Genes, BRCA2; D020022:Genetic Predisposition to Disease; D006801:Humans; D009154:Mutation; D019683:Penetrance; D015995:Prevalence; D018570:Risk Assessment; D012307:Risk Factors