DUARTE, Calif. -- In the face of early-onset breast cancer, too few women in the family can taint the potential accuracy of models to determine the need for full-blown BRCA testing.
DUARTE, Calif., June 19 -- In the face of early-onset breast cancer, too few women in the family can taint the accuracy of models to determine the need for full-blown BRCA testing.
These probability models work better at predicting the likelihood of finding the breast cancer-susceptibility mutations in BRCA1 and BRCA2 among women with early-onset disease when the number of older female relatives is high, found Jeffrey N. Weitzel, M.D., of City of Hope here, and colleagues.
This finding illustrates the limitations of the commonly used predictive tools and may challenge the accuracy of some breast cancer prediction models that may not take small family structure into account, they reported in the June 20 issue of the Journal of the American Medical Association.
"This report demonstrates the effect of family structure on mutation probability models and the need for clinicians to consider family structure when deciding whether to offer BRCA testing to a 'single case' of early onset breast cancer," the researchers said.
Identifying candidates for genetic cancer risk assessment is challenging, the researchers wrote. Although the consensus is that BRCA testing is not appropriate for unaffected women in the general population, there is less clarity in for women with early onset disease and no family history of breast or ovarian cancer.
The study aimed to determine whether BRCA gene mutations are more prevalent among single cases of early onset breast cancer in families with a limited number of women than would be predicted by currently available probability models.
This was defined as fewer than two first- or second-degree female relatives surviving beyond age 45 in either the maternal or paternal lineage.
On the basis of this information and available medical records, the probability of carrying a BRCA gene mutation was calculated by three commonly used predictive models.
A total of 1,543 women seen at U.S. high-risk clinics for genetic cancer-risk assessment and BRCA testing were enrolled in a prospective registry study from April 1997 to February 2007.
Of these women, 306 had breast cancer before age 50 and no first- or second-degree relatives with breast or ovarian cancers.
Family size was limited in 153 cases (50%). BRCA gene mutations were detected in 13.7% of participants with limited versus 5.2% with adequate family structure, the researchers reported. Patients with a limited family size had an increased likelihood of being carriers of BRCA mutations than those with more female relatives.
Family size was a significant predictor of mutation status (odds ratio, 2.8; 95% confidence interval, 1.19 to 6.73; P=0.02), the researchers said.
The three models used for estimating the mutation probability and accounting for family size were Couch, Myriad, and BRCAPRO.
Although none of the models performed well, analysis indicated that modification of BRCAPRO output was the most accurate predictor of BRCA mutation status (area under the curve, 0.72; 95% confidence interval, 0.63 to0.81; P<0.001) for single cases of breast cancer, the investigators reported.
Nevertheless, the influence of family size on the performance of predictive models should be confirmed in other high-risk clinic populations, they added.
For the entire cohort, mean age for the genetic consultation was 40.7, and the mean age of breast cancer diagnosis was 37.7 years. Nineteen women had bilateral cancer.
The problem of limited family structure is not uncommon, in part because of smaller family size, premature mortality, loss of family information in events such as the Holocaust, even risk-reduction surgery, which may all obscure recognition of hereditary traits, the researchers said.
Fewer older female relatives is similar to the problem of "missing values" and is a limitation of all common mutation probability models. Consequently, the researchers said, lacking better models, cancer risk-assessment practices and genetic testing guidelines need to take into account single cases of breast cancer when there is limited family information.
The fact that commonly used models for estimating the probability of BRCA mutation were insensitive to family size as a predictive factor is a cautionary note for community practitioners, Dr. Weitzel and his colleagues said.
"Given the significant effect of family structure, illustrated by limited accuracy of probability models for single cases of breast cancer, and the commonality of the missing data problem, the databases of currently available probability models should be reanalyzed and limited family history recoded as a separate variable," the researchers wrote.
In an accompanying editorial, Noah D. Kauff, M.D., and Kenneth Offit, M.D., M.P.H., of Memorial Sloan-Kettering Cancer Center in New York, wrote that some genetic risk prediction models should be used cautiously.
The researchers, they said, have made a compelling argument that risk assessment models are likely not appropriate if only a limited number of informative relatives are available.
Perhaps more important than this specific conclusion are the implications this study has for the use and interpretation of risk assessment models in general, they said.
When applying quantitative risk assessment models to determine possible surgical approaches, the editorialists noted that even more caution is noted.
For example, they said, none of the models evaluated took into account that breast cancer risk may be conferred by as yet unidentified cancer susceptibility genes. Strong evidence suggests that almost half of hereditary breast cancer is caused by genes not linked to BRCA1 or BRCA2.
Given the limitations of the risk assessment models in this study, "important questions are whether currently available models are appropriate to triage individuals for genetic testing or are adequate to provide cancer risk predictions and guidance of care in the absence of genetic testing," Drs. Kauff and Offit said.
The editorial writers reported no financial conflicts.