S. Schmidt et al., BREAST-CANCER RISK ASSESSMENT - USE OF COMPLETE PEDIGREE INFORMATION AND THE EFFECT OF MISSPECIFIED AGES AT DIAGNOSIS OF AFFECTED RELATIVES, Human genetics, 102(3), 1998, pp. 348-356
Reliable risk estimates for hereditary breast cancer are important for
the genetic counseling of women who have one or more first- and/or se
cond-degree relatives affected by the disease. If no mutation analysis
of known high-penetrance breast cancer genes is performed, risk estim
ation is often based on published reference tables. These tables expre
ss a woman's age-specific risk of breast cancer as a function of the a
ges at diagnosis of one or two affected relatives with different degre
es of relationship to the counselee. However, unaffected relatives are
not taken into account when these estimates are derived. We report he
re the extent to which risk estimation is influenced by the number and
ages of any unaffected relatives and by the exact genealogical relati
onship between the proband and affected relative rather than merely th
e degree. Additionally, we describe the sensitivity of risk estimates
when ages at diagnosis of affected relatives are misspecified because
of inaccurate information supplied by the counselee. We determined a p
roband's probability of being a carrier of a highly penetrant breast c
ancer susceptibility gene, such as BRCA1 or BRCA2, by likelihood calcu
lations that take into account information from the entire pedigree. T
his genetic risk was used to estimate a phenotypic lifetime breast can
cer risk, which was compared with the risks derived from the published
reference tables. We demonstrate numerically that the tabulated value
s tend to over-estimate the probands risk and that the extent of over-
estimation depends greatly on the number and ages of unaffected relati
ves. The validity of the relatives ages at diagnosis can affect risk p
redictions considerably in small families with two or three affected r
elatives. Furthermore, the magnitude of the estimated breast cancer ri
sks depends upon the assumed genetic model and can therefore vary appr
eciably when different penetrance estimates are used.