Correspondence to: Donald A. Berry, Ph.D., Department of Biostatistics, The University of Texas M. D. Anderson Cancer Center, 1515 Holcombe Blvd., Box 447, Houston TX 770304009 (e-mail: dberry{at}odin.mdacc.tmc.edu).
The article by Loman et al. (1) in this issue of the Journal reports rates of germline mutations of breast and ovarian cancer susceptibility genes BRCA1 and BRCA2 among Swedish women who were diagnosed with breast cancer at age 40 years or less. The study is population based and includes all breast cancer patients diagnosed in southern Sweden during the period from 1990 through 1995. The study's principal conclusion is that 9% (21 of 234) of these young patients carried mutations. Among the youngest women, those younger than 36 years, the rate was 16% (13 of 81), whereas the corresponding rate for women aged 3640 years was 5% (eight of 153). Not surprisingly, women with a family history of breast or ovarian cancer (which was about half of the women in the study) were at greater risk of testing positive for carrying a mutation.
These estimates are similar in magnitude to those from a population-based study in the U.K. (2). However, many readers will view the rates as being rather low. In some populations, a 9% mutation rate is within the range proposed as appropriate for all women with breast cancer (3). Since both genes, and especially BRCA1, are associated with higher incidence in younger women, the same rate could not apply when restricted to young patients. Several factors may contribute to differences between the Swedish study on the one hand and other types of studies and clinical experiences on the other. The most obvious possibility is that the women in the study are Swedish and the prevalence of mutations may be different for Swedes (and also Britons) than for other populations.
A factor that can give rise to artificially low mutation rates is the testing method used. The Swedish investigators used sequencing for two exons and single-strand conformation polymorphisms (SSCPs) or denaturing high-performance liquid chromatography (dHPLC) for the rest. They do not advertise a level of accuracy for these methods, but they are unlikely to be very sensitive (46). Therefore, they may well have missed many deleterious mutations. Prevalence estimates should be adjusted to account for the possibility of false-negatives. For example, Peto et al. (2) adjusted rates for the U.K. using their study and assuming a testing sensitivity of 63%.
Another possible explanation for the difference between some readers' impressions and the magnitude of the estimates from the Swedish study is that families encountered in clinical and counseling situations are not randomly selected from the population at large. For example, young women who present to high-risk genetic counseling clinics are different from young women generally, and they may be very different. Most importantly, the families of these women tend to have more cancers. In addition, patients who actually seek testing may be at an even higher risk. Because they are guided by informed counselors, patients who submit to genetic testing tend to be at higher risk than those who are not tested. These high-risk genetic counseling clinics can be very different from other clinical settings in this regard, and they can have extremely high rates of positive tests. For example, for affected women aged 40 years or less in consecutive series at three clinics that I know, the rates of positive tests (in which testing involved the highly sensitive approach of fully sequencing the genes or using the Ashkenazi Jewish panel when appropriate) were 64%, 83%, and 85% (based on 14, 23, and 13 cases, respectively).1 These rates are a far cry from the corresponding figure of 9% in the population-based study from Sweden. And no researcher has ever suggested that SSCP or dHPLC is insensitive enough to increase the estimated mutation rate by a factor much greater than 2.
From a scientific perspective, population-based studies are important because they enable unbiased estimates of prevalence. Patients seen by genetic counselors are not randomly selected in any sense; therefore, studies involving such patients are biased. In these studies, patients' risk of carrying mutations tends to be greater than that in the population at large, but the extent of the bias is difficult to assess. Attitudes differ concerning which patients should be tested, and one clinic's experience may be very different from another clinic's experience. Still, estimates of prevalence from studies involving high-risk patients are usually appropriate references for counselors precisely because counselors deal with high-risk patients. Population-based studies do not specifically address high-risk populations. Therefore, estimates of mutation rates in the Swedish study have little relevance for clinical settings, in Sweden or elsewhere.
Loman et al. (1) present their results using rather crude characteristics of family history: numbers of first- and second-degree relatives with breast or ovarian cancer. They approximate mendelian inheritance using only the somewhat awkward device of counting two affected women related through a man as though they were first-degree relatives. Considering mendelian inheritance, patients' family histories can yield concise and informative probabilities that they carry deleterious mutations (7,8). Ideally, family history considered should include exact relationships and sexes of all relatives, age(s) at diagnosis and type(s) of cancer of each affected relative, age (or age at death) of each unaffected relative, and whether the family is Ashkenazi Jewish. For affected young women (Swedish or otherwise), carrier probabilities can vary from less than 1% to greater than 99%.
Moreover, carrier probabilities can vary greatly even among individuals with the same number of affected relatives. For example, for young women in the Swedish study having two first- or second-degree relatives with breast cancer or ovarian cancer, 38% (nine of 24) tested positive for carrying a mutation at either BRCA1 or BRCA2. I do not know their family histories, but using BRCAPRO (7,8) to find carrier probabilities for other patients who were younger than 41 years at diagnosis and who had two affected relatives, these carrier probabilities vary from 5% to nearly 100%. Ages of relatives can matter more than the age of the woman in question. And knowing the number and relationships of unaffected relatives is critical.
Calculations of carrier probabilities should use the same properties of mendelian inheritance whether the woman (or man) is randomly selected from a larger population or presents at a high-risk genetic counseling clinic. Because information concerning familial risk is used in the calculations, there is no bias associated with manner of ascertainment. In the example of high-risk genetic clinics mentioned above, with rates of positive tests of 64%, 83%, and 85%, the respective average values of BRCAPRO were 57%, 80%, and 91%, which approximate the actual risks within limits of sampling variability. On the other hand, BRCAPRO makes assumptions about prevalence and penetrance, and these parameters depend on the population of interest. Population-based studies are essential for delivering unbiased estimates of these quantities.
A larger question of risk assessment is whether knowing one's risk of harboring a mutation matters to a woman. Although the issues also apply more generally, consider the setting of the Swedish study in which young women have been diagnosed with breast cancer. Does it matter whether their risk of carrying a mutation is 1%, 9%, or 85%? The numbers are very different and suggest low, moderate, and high risks, respectively. It is important to separate one's numerical estimate of risk from the value of knowing that risk. Information content depends not only on the risk but also on the woman's attitudes. If the woman would not make any changes in her life on the basis of the information, then knowing her risk has no value (although she may "just want to know"). But some women will make different choices depending on the risk. For example, a woman may make no life changes if she finds that her risk is 1%, but she might opt for genetic testing if it is 9% and she might choose bilateral mastectomy and oophorectomy if it is 85%. (Eschewing genetic testing in the last case may be reasonable when the test is not very sensitive, and so her revised carrier probability would be moderately high even if the test is negative. If she would make the same choice whether the test is positive or negative, then the test has no value.) For 9% risk, testing may reduce her carrier probability to the point where she would avoid surgery for a negative test result and she would choose surgery in the event that the test is positive. Depending on her carrier probability, the benefit of testing measured in terms of additional quality-adjusted life-years can be substantial (9). Therefore, knowing one's riskat least within some rangeis important.
In summary, providing an accurate assessment of genetic risk can be important to patients. Rates of positive tests from a population-based study can be very different from those measured in high-risk genetic counseling clinics. The former are more important scientifically, whereas the latter are usually more relevant in clinical settings. Calculations based on exact family relationships and cancer statuses and ages of family members can vary greatly, even among families with the same total numbers of affected members.
NOTES
1 I thank Patrice Watson (Creighton University, Omaha, NE), Judy Garber (Dana-Farber Cancer Institute, Boston, MA), and Caryn Lerman (Georgetown University, Washington, DC, and University of Pennsylvania, Philadelphia) for permission to cite these rates.
REFERENCES
1
Loman N, Johannsson O, Kristoffersson U, Olsson H, Borg A. Family history of breast and ovarian cancers and BRCA1 and BRCA2 mutations in a population-based series of early-onset breast cancer. J Natl Cancer Inst 2001;93:121523.
2
Peto J, Collins N, Barfoot R, Seal S, Warren W, Rahman N, et al. Prevalence of BRCA1 and BRCA2 gene mutations in patients with early-onset breast cancer. J Natl Cancer Inst 1999;91:9439.
3 Szabo CI, King MC. Population genetics of BRCA1 and BRCA2. Am J Hum Genet 1997;60:101320.[Medline]
4 Sarkar G, Yoon HS, Sommer SS. Screening for mutations by RNA single-strand conformation polymorphism (rSSCP): comparison with DNA-SSCP. Nucleic Acids Res 1992;20:8718.[Abstract]
5 Cotton RG. Current methods of mutation detection. Mutat Res 1993;285:12544.[Medline]
6 Ravnik-Glavac M, Glavac D, Dean M. Sensitivity of single-strand conformation polymorphism and heteroduplex method for mutation detection in the cystic fibrosis gene. Hum Mol Genet 1994;3:8017.[Abstract]
7
Berry DA, Parmigiani G, Sanchez J, Schildkraut J, Winer E. Probability of carrying a mutation of breastovarian cancer gene BRCA1 based on family history. J Natl Cancer Inst 1997;89:22738.
8 Parmigiani G, Berry D, Aguilar O. Determining carrier probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2. Am J Hum Genet 1998;62:14558.[Medline]
9 Tengs TO, Winer EP, Paddock S, Aguilar-Chavez O, Berry DA. Testing for the BRCA1 and BRCA2 breastovarian cancer susceptibility genes: a decision analysis. Med Decis Making 1998;18:36575.[Medline]
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