ER+? wondering what to tell your female relatives

[Lani]

about whether to use tamoxifen on a preventative basis. This study based on a large number of patients sought to answer the question, but did not include her2 as a factor as far as I can see (will modify if I learn differently) As her2+ER+ breast cancer has been estimated to make up less than 10% of ER+ breast cancer, any different results in that subset may not have been enough to alter the overall results of this study. Will try to investigate further

PS I have previously posted that there may be a subset (size unknown) of her2+er+ breast cancers due to an xlinked gene (FOXP3)--if they ever started testing for this, of course, and/or other genes they may find associated with her2+ER+ breast cancer, if any, risk assessment would be much simpler


LA BioMed research finds simpler way to assess breast cancer risk: Women and their doctors can more easily decide need for medication to reduce risk [Eureka News Service]
TORRANCE (Nov. 13, 2007) - A new, simpler model for predicting breast cancer risk in postmenopausal women appears to be as accurate as a more complicated method currently used to decide if women would benefit from medication to reduce their risk of getting cancer, according to research published today in the Journal of the National Cancer Institute.
A team of researchers led by Rowan T. Chlebowski, a lead investigator at the Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center (LA BioMed), sought a simpler method for measuring breast cancer risk so women and their doctors could easily determine when the women would be likely to benefit from tamoxifen treatment for reducing their chances of getting breast cancer.
"For the first time, a postmenopausal woman can use a simple model and determine by herself if she is at increased risk of getting breast cancer," said Dr. Chlebowski. "She could then raise this issue with her health care provider because interventions to reduce her risk of breast cancer are now available."
Using data from the Women's Health Initiative, a 15-year research program involving 161,808 postmenopausal women and funded by the National Institutes of Health, the researchers found postmenopausal women were at an "increased risk" of developing breast cancer if they were: 55 years of age or older and had either had a breast biopsy at any time, regardless of findings, or had a first-degree relative (mother, sister or daughter) who had breast cancer diagnosed at any age.
"Increased risk" is defined as about a 2 percent risk of developing breast cancer over the next five years. The researchers sought a quicker and easier way to determine risk because those who are at "increased risk" may benefit from tamoxifen treatment to reduce their chances of getting breast cancer.
Prior to this study, most physicians relied on the "Gail Model" to determine risk. But it involves so many variables that a computer is needed to determine a woman's risk of breast cancer. As a result, it wasn't used widely.
Previous surveys found only 11 percent of California primary care physicians had used the Gail Model for risk assessment in the past year. In a national survey, only 16 percent agreed that it is "easy to determine" who is eligible for breast cancer risk reduction strategies and only 25 percent had prescribed tamoxifen for risk reduction in the past year.
The Gail model underestimated 5-year breast cancer incidence by almost 20 percent, but it performed better when predicting estrogen receptor-positive breast cancer than estrogen receptor-negative breast cancer. The simpler model that used only three factors for calculating risk—age, family history of breast cancer, and previous breast biopsy—was almost as accurate as the Gail model for predicting estrogen receptor-positive breast cancer.
The simpler model "would be more accessible for routine and rapid prescreening in the prevention or routine care setting," the authors wrote in the Journal article.
ABSTRACT: Predicting Risk of Breast Cancer in Postmenopausal Women by Hormone Receptor Status [Journal of the National Cancer Institute]
Background: Strategies for estrogen receptor (ER)-positive breast cancer risk reduction in postmenopausal women require screening of large populations to identify those with potential benefit. We evaluated and attempted to improve the performance of the Breast Cancer Risk Assessment Tool (i.e., the Gail model) for estimating invasive breast cancer risk by receptor status in postmenopausal women.
Methods: In The Women's Health Initiative cohort, breast cancer risk estimates from the Gail model and models incorporating additional or fewer risk factors and 5-year incidence of ER-positive and ER-negative invasive breast cancers were determined and compared by use of receiver operating characteristics and area under the curve (AUC) statistics. All statistical tests were two-sided.
Results: Among 147 916 eligible women, 3236 were diagnosed with invasive breast cancer. The overall AUC for the Gail model was 0.58 (95% confidence interval [CI]=0.56 to 0.60). The Gail model underestimated 5-year invasive breast cancer incidence by approximately 20% (P<.001), mostly among those with a low estimated risk. Discriminatory performance was better for the risk of ER-positive cancer (AUC = 0.60, 95% CI = 0.58 to 0.62) than for the risk of ER-negative cancer (AUC = 0.50, 95% CI = 0.45 to 0.54). Age and age at menopause were statistically significantly associated with ER-positive but not ER-negative cancers (P=.05 and P=.04 for heterogeneity, respectively). For ER-positive cancers, no additional risk factors substantially improved the Gail model prediction. However, a simpler model that included only age, breast cancer in first-degree relatives, and previous breast biopsy examination performed similarly for ER-positive breast cancer prediction (AUC=0.58, 95% CI= 0.56 to 0.60); postmenopausal women who were 55 years or older with either a previous breast biopsy examination or a family history of breast cancer had a 5-year breast cancer risk of 1.8% or higher.
Conclusions: In postmenopausal women, the Gail model identified populations at increased risk for ER-positive but not ER-negative breast cancers. A model with fewer variables appears to provide a simpler approach for screening for breast cancer risk.