This well-written article can benefit only from reinforcement of a few of its major points, some supplemental discussion about the important role of biologic models in understanding and managing breast cancer development, and a note about the critical need for research and perspectives from the social sciences concerning this subject. I say "only" because this article beautifully and clearly explores some of the language of epidemiology critical to the subject, language which is becoming increasingly important in routine medical practice. Practitioners and, increasingly, the public (medical "consumers") are concerned with risks and numbers.
This well-written article can benefit only from reinforcementof a few of its major points, some supplemental discussion aboutthe important role of biologic models in understanding and managingbreast cancer development, and a note about the critical needfor research and perspectives from the social sciences concerningthis subject. I say "only" because this article beautifullyand clearly explores some of the language of epidemiology criticalto the subject, language which is becoming increasingly importantin routine medical practice. Practitioners and, increasingly,the public (medical "consumers") are concerned withrisks and numbers.
Three Important Messages
The article has three messages that deserve emphasis: First, womenoverestimate their risks for breast cancer, both their lifetimeprobabilities and, more importantly, their immediate future--say,5-year--risks. The adverse consequences of these overestimatesdo demand our careful clinical attention. As Vogel nicely shows,we can use available models to estimate risks for individuals,but, for those at greatest risk, for example, those with BRCA1mutations, interpreting the genetic test results is challengingbecause of allelic heterogeneity.
A second critical message is that the optimal details or componentsof the counseling encounter are not yet defined. Experienced geneticcounselors suggest that several hours of individual counselingis the norm for women with a high prior probability of testingpositive for a BRCA1 mutation. In my experience, in contrast tothe suggestion Vogel makes, the period around the diagnosis ofbreast cancer in a close relative is a bad time to work with anat-risk patient, possibly because most women are emotionally inturmoil at this time.
Finally, management also is tricky. Vogel does not mention theuncertainties over the risks and benefits of mammography in premenopausalwomen, even those at increased risk for breast cancer. Given thecomplexities and uncertainties inherent in managing and counselingthese women, I would strongly second his suggestion for referralfor counseling and possibly genetic testing when prophylacticsurgery is under consideration.
Biologic Models of Breast Cancer Development
Well-read clinicians will recognize the limitations of the modelsVogel describes. His discussion does not bring these "riskfactors" together into a rational biologic model. To supplementthis article, let me add these perspectives. Clearly, geneticfactors, that is, familial (presumably primarily inherited) mutatedgenes, are the most powerful conferrers of risk for breast cancer.At present, the mechanisms through which these genes exert theirpowerful influences are unknown.
Beyond genetic influences, there are essentially two, not mutuallyexclusive, biologic models for breast cancer development. Thefirst is a differentiation model. The major observation in humansthat provides support for this model is the linear relationshipof age at first birth and risk of breast cancer so definitivelydescribed a quarter-century ago by MacMahon et al (Figure 1).How one states that relationship governs how numerically significantit seems. In contrast to Vogel's suggestion, I believe that Russoet al have provided us with an explanation for this observation:Lobular maturation and terminal-end bud differentiation consequentto a full-term pregnancy decrease the numbers of undifferentiatedcells in the mammary glands of rodents.
The second model is essentially a hormone exposure model. Theassociations of breast cancer risk with age at menarche, age atmenopause (natural or artificially induced, as by surgical oophorectomy),obesity, anovulatory cycles (increased by exercise), hormone density,and hormone replacement therapy in postmenopausal women (a weakassociation) all support such a model. Pike et al have emphasizedthis model, calculating the significant consequences of prematuretermination of ovarian function. In their calculations, theyhave used the repeated observation that (for breast cancer priorto menopause) the graphed age incidence curve for major malignancieson log/log scales is linear. The details of which hormones aremost significant and timing of exposures are unclear, but thisshould not distract us from appreciating the broad picture.
What Vogel's discussion and the comments above suggest is thatwe need to devote greater attention to the construction of modelsof breast cancer development. We must then use available clinicaldata and observations to test these models and to develop, wheneverpossible, model-based studies.
Need for Involvement of the Social Sciences
Finally, it is critical to note that breast cancer risk is nota subject solely for medical clinicians or geneticists. Perspectivesand research from a broad range of social sciences, from historiansand anthropologists through journalists and educators, are needed.Only 3% of the budget of the Human Genome Project is earmarkedfor such research, and there is only one social science memberon the Task Force on Genetic Testing of the National Center forHuman Genome Research. In my view, we can achieve the best resultsfor individuals and our society only by giving significantly greaterrecognition to the importance of conducting social science researchin this area and by committing further resources to that end.
1. MacMahon B, Cole P, Lin TM, et al: Age at first birth and breastcancer risk. Bull World Health Organ 43:209-221, 1970.
2. Ciocca DR, Parente A, Russo J: Endocrinologic milieu and susceptibilityof the rat mammary gland to carcinogenesis. Am J Pathol 109:47-56,1982.
3. Pike MC, Ross RK, Lobo RA, et al: LHRH agonists and the preventionof breast and ovarian cancer. Br J Cancer 60:142-148, 1989.