BREAST DENSITY AND CALIFORNIA LAW
California women who have dense breasts on their mammograms are currently receiving written notification that they have “dense breasts.” Some institutions are notifying all women of their density – both high density and low density – whereas some institutions are notifying only women with dense breasts, the minimum that the law requires. The law does not stipulate any action that a physician must take, but the letter raises more questions than it answers.
Does breast density correlate with density on clinical examination?
No! Breast density – both in the context of SB-1538 and as a risk factor discussed below – is a specific finding revealed only by mammograms. Dense breasts on clinical breast examination may be dense either 1. because of dense gland tissue as seen in radiographically dense breasts, or 2. because of accumulated fatty tissue that can exist in breasts that are almost entirely fat on mammograms, i.e very non-dense. It is not possible to determine whether tissue or fat causes the palpable density by clinical breast examination alone.
How many women have dense breasts?
Half of women have dense breasts on their mammogram. This “half” breaks down as approximately 10% of all women with extremely dense breasts and 40% with heterogeneously dense breasts [click here, Table 1]. The breakdown is important because only the 10% of women with extremely dense breasts have the maximum increase in risk, and only one-fifth of women who are told they have dense breasts will have a very high risk.
For comparison, about 10% of women have almost entirely fatty breasts and 40% have scattered densities.
What is the risk with extremely dense breasts?
Independent of other risk factors, a woman with extremely dense breasts (10% of all women) has roughly twice the risk of developing breast cancer as a woman with scattered densities (40% of all women and the majority of women with non-dense breasts) [click here, Table 5].
Similarly- as an approximation – breast density divides any risk group of women – for example those with family history, higher alcohol use, etc. – into higher risk (dense breasts) or lower risk (non-dense breasts) sub-groups. However, the ability to detect truly low-risk versus truly high-risk groups by mammographic density is limited because the ratio of risk between the highest and the lowest groups is only about two fold.
For example, a woman with atypical duct hyperplasia has about an 8% chance of cancer over 10 years. This can be divided into higher and lower risk groups, but the ratio between low and high is always two to one and they must average to 8%. This limits how high the high risk really is, but more importantly, it also limits how low the risk is for lower risk women. These are real differences, but it is not clear how to apply this information since women with low-density mammograms can still develop breast cancer. [See previous post on Breast Density.]
Why study breast density?
Wolfe in 1967 reported that breast parenchyma patterns could identify women at high risk of developing breast cancer. Breast cancer increased with the progression from N1 through P1 and P2 to DY parenchyma patterns. These patterns correspond roughly – though not exactly – to current breast density classifications ranging from almost entirely fatty to extremely dense.
Predicting risk from parenchyma patterns is complicated because many women do not fit one category or another. Measuring breast density has the same problem. Computerized systems help, but there is an unavoidable arbitrariness in selecting the cut points between density groups. Even using arithmetic quartile groups assumes that the point of separation between quartiles has biological significance.
Cost cutting is the new goal.
Cost cutting – the opposite of risk identification – is the reason for recent research on breast density. Instead of finding high-risk women, the goal has become to identify a group of women with an absolute low-risk of cancer – or a low enough risk – for whom mammograms can be done less frequently or omitted altogether [click for abstract].
Kerlikowski et al expand on this reasoning advocating biennial (every two years) instead of annual screening for most women [click for abstract]. However, they also note that women 40 to 49 years of age – with extremely dense breasts – are more likely to be diagnosed with advanced breast cancer if they have biennial rather than annual mammograms.
They contend this risk of more advance cancer is acceptable because annual mammograms for ten years are also associated with a significant possibility of a false positive mammogram with attendant stress and unnecessary testing, perhaps even a benign biopsy.
Women who undergo any breast diagnostic workup experience stress. They ignore, however, the likelihood of greater stress from remorse for a woman with delayed cancer diagnosis after skipping her mammogram for a year or more. Such stress has not been considered in their arguments.
What is recommended for women with dense breasts in 2013?
A group of radiologists representing Stanford, UC Davis, UC Irvine, UC Los Angeles, UC San Francisco, UC San Diego, California Pacific Medical Center, and Alta- Bates Summit Medical Center in Berkeley have created a website with recommendations for representative patient scenarios. www.breastdensity.info
They advise physicians to base screening recommendations on breast density only when density is considered along with other factors.
Their recommendations have a general theme. If a woman has dense breasts – and after risk assessment of family history and/ or other factors – is at increased risk for reasons in addition to breast density alone, they recommend screening MRI. Otherwise, mammography should be recommended. Other modalities, e.g. screening ultrasound and 3-D mammography, are investigational as of March 2013.
New tests are being developed.
Berg and colleagues have evaluated adding hand-held ultrasound to screening for women with at least heterogeneously dense breasts on mammograms [click here]. Ultrasound significantly increased cancer detection by an additional 4.2 cases per 1000 exams, but the false positive rate increased from 4.4% for mammograms alone, to 8.1% for ultrasound alone, and 10.2% for combined mammograms and ultrasound. Ultrasound helps, but at the cost of more false positive evaluations.
Computerized tomosynthesis or 3-D mammography processes two breast exposures to create a set of multiple tomographic images of the breast. In preliminary studies, tomosynthesis detected 27% more cancers with a simultaneous 15% decrease in false positives [click for abstract]. The tomographic study itself has only a little more radiation exposure than a screening mammogram, but interpretation is based on both standard mammograms and tomosynthesis together – done with two different exposures at the same time – so currently the total radiation dose is doubled. Computer algorithms to use one pair of exposures to create both tomosynthetic and standard whole thickness images are being developed to resolve the problem of increased radiation exposure.