Affiliations of authors: J. S. Lee, Howard Hughes Medical Institute, Bethesda, MD, and Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), Bethesda; S. Wacholder, J. P. Struewing, M. A. Tucker, P. Hartge, Division of Cancer Epidemiology and Genetics, NCI; M. McAdams, D. Pee, Information Management Services Inc., Silver Spring, MD; L C. Brody, Genetics and Molecular Biology Branch, National Human Genome Research Institute, Bethesda.
Correspondence to: Patricia Hartge, Sc.D., National Institutes of Health, Executive Plaza North, Rm. 443, Bethesda, MD 20852 (e-mail: hartge{at} nih.gov).
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ABSTRACT |
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INTRODUCTION |
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More than 400 protein-truncating mutations in the BRCA1 and BRCA2 genes have been characterized.1 This wide range of mutations and the lack of functional assays have made determination of cancer survival among BRCA1 and/or BRCA2 mutation carriers difficult. In the Ashkenazi Jewish population, characteristic BRCA1 and BRCA2 mutations have been identified; therefore, within this population, a relatively large number of mutation carriers can be identified more efficiently to estimate survival after cancer.
In the Ashkenazi Jewish population, two BRCA1 mutations, 185delAG (two nucleotide deletion) and 5382insC (single nucleotide insertion), and one BRCA2 mutation, 6174delT (single nucleotide deletion), have a combined frequency exceeding 2% (12-14). Recently, a large community-based survey (15) of this population obtained family history data from participants who were subsequently tested for BRCA1 and BRCA2 mutations. This study investigates the effect of BRCA1 and/or BRCA2 mutations on survival among patients with breast and ovarian cancers.
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SUBJECTS AND METHODS |
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Recruitment of volunteers from the community-based survey, collection of data, and laboratory methods have been described in detail elsewhere (15). Briefly, 5318 Jewish men and women over the age of 20 years were recruited from the Washington, DC, area. After giving written informed consent, participants gave blood samples and completed a self-administered questionnaire. Polymerase chain reaction (PCR)-based assays on blood samples were performed to determine carrier status for two BRCA1 mutations, 185delAG and 5382insC, and one BRCA2 mutation, 6174delT. Positive mutation carrier status was defined by detection of either a BRCA1 or BRCA2 mutation. Only samples that were positive on at least two independent PCR-based assays were considered positive in the statistical analyses. The questionnaire elicited information on the participants' first-degree relatives, namely, history of cancer, including type(s) of cancer, age at diagnosis, and survival status. This project proposal was performed after approval by the institutional review board of the National Cancer Institute, Bethesda, MD.
Statistical Methods
We calculated follow-up time from diagnosis of cancer to date of death (from any cause) or, for those alive, we censored follow-up at the date of questionnaire completion. Individuals were excluded from the analyses if such data were missing and thus follow-up was unknown.
We analyzed survival difference in two ways. First, we estimated survival curves in the affected relatives of carriers and the affected relatives of noncarriers, overall and within strata defined by age at and calendar period of diagnosis. We estimated survival curves by using the Kaplan-Meier technique (16), compared survival curves using the two-sided logrank test (17) and the Cox proportional hazards model, and considered P values below .05 as statistically significant. This qualitative approach would reveal any marked differences in survival among carriers if one existed, even though we knew the BRCA1 and/or BRCA2 carrier status only of the study participants, not of their affected relatives.
The second survival analysis applied a more quantitative approach (see Appendix). We extended the kin-cohort method to infer the prevalence of BRCA1 and/or BRCA2 mutations in first-degree relatives of carriers and noncarriers, specific for age at diagnosis (15,18). With the use of estimates of age-specific penetrance from our previous report (15), we inferred the proportions of mutation carriers and noncarriers in these two groups of patients. A large proportion of affected relatives of mutation carriers are carriers themselves; by contrast, only a small minority of affected first-degree relatives of noncarriers are (or were) themselves carriers, since so few (<3%) of the general Ashkenazi Jewish population are BRCA1 and/or BRCA2 mutation carriers (15). We then fitted linear regression models, including terms for age at diagnosis, calendar period of diagnosis, and the related participant's mutation carrier status (19). From this, we determined and compared maximum likelihood estimates for survival after breast cancer among the inferred BRCA1 and/or BRCA2 mutation carriers and noncarriers. Because of small numbers, we used only the first method for ovarian cancer. P values given are from two-sided tests.
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RESULTS |
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We examined the effects of specific mutations. Of the 58 affected relatives of mutation carriers, 35 (60%) were reported by participants carrying a BRCA1 mutation and 23 (40%) were reported by participants carrying a BRCA2 mutation. The 5-year survival rate for relatives of carriers of BRCA1 mutations was 79% compared with 65% for BRCA2, a difference that was not statistically significant. Likewise, the survival times for relatives of 5382insC, 185delAG, and 6174delT mutation carriers did not differ significantly, with or without adjustment for age and year of diagnosis.
Table 3 shows survival estimates of first-degree
relatives with breast cancer according to their inferred mutation
status. Adjusting for age at and calendar period of diagnosis, we
estimate that carriers had a 5% survival advantage at 5 years
(95% CI = -12% to 22%) and a 4% advantage at 10 years
(95% CI = -15% to 22%). These small differences were not
statistically significant.
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DISCUSSION |
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Our survival rates and comparisons agree generally with two small studies of Jewish women by Haas et al. (3) and by Robson et al. (4). Our findings also agree with several studies (1,2,8) of patients with breast cancer not limited to those of Jewish descent. Marcus et al. (8) found no survival difference among 90 patients with BRCA1 mutations and 85 patients with no mutations in BRCA1. Verhoog et al. (2) and Johannsson et al. (1) found no differences between BRCA1 mutation-positive patients ascertained from cancer-prone families and sporadic patients from cancer registries. In contrast, other small studies have suggested that BRCA1 and/or BRCA2 mutation carrier status affects survival time (5,6), but small study size, genetic tests in paraffin-embedded tumors, and potential screening biases complicate their interpretation.
Ovarian cancer survival has been difficult to assess, but two relatively small studies (1,7) have reported survival comparisons according to BRCA1 and/or BRCA2 mutation carrier status among patients with ovarian cancer. Johannsson et al. (1) reported an equal or worse survival for 33 patients with BRCA1 mutation-positive ovarian cancer identified from 21 Swedish breast cancer-prone families compared with 97 age- and stage-matched patients with ovarian cancer from the general population, a finding similar to ours. On the other hand, Rubin et al. (7) observed a survival advantage for patients with BRCA1 mutation-positive ovarian cancer compared with sporadic cancer control subjects.
The major limitation of this study was the lack of data about the cause of death in the affected first-degree relatives. If BRCA1 and/or BRCA2 mutations play an etiologic or a prognostic role in diseases other than breast or ovarian cancer that are prevalent in our cohort of first-degree relatives, competing risks may affect our survival comparisons. Mortality from causes other than breast or ovarian cancer after age 60 years appears higher among first-degree relatives of mutation carriers than among those of noncarriers. In addition, other non-BRCA mutations that may affect survival may be present in our study population. It was not possible to ascertain information on histopathologic factors and their effect on survival in our study.
A second limitation of our data is that diagnosis and vital status in the first-degree relatives were not confirmed, but it has been shown that research subjects accurately report family history of common cancers, including breast cancer (20). In addition, substantial bias from inaccurate reporting by participants about their first-degree relatives seems remote, since participants in our study were generally well educated (>57% had post-graduate education) (15). Furthermore, any inaccuracies are not likely to be related to the observed carrier status of participants or the inferred carrier status of their affected first-degree relatives. We adjusted for age at and year of diagnosis to avoid possible confounding from potential differences in cancer staging and treatment.
This study avoided several of the common sources of bias that can hamper survival studies that compare hereditary breast or ovarian cancer to patient groups ascertained from different sources. For example, comparing BRCA1 and/or BRCA2 mutation-positive patients from cancer-prone families (1,2,6,8) or hospitals (7) to sporadic cancer patients from cancer clinics (7) or cancer registry (1,2,6,8) offers potential for bias in estimating survival. Patients from cancer clinics or cancer-prone families selected for gene mapping studies may be more likely to be diagnosed earlier through more rigorous screening and to be alive for study involvement. Such screening biases could operate in the present study, but to a lesser extent since most carriers lacked extensive family history of cancer. Evaluating individuals from families selected for linkage analysis also may bias findings toward longer survival time among BRCA1 and/or BRCA2 mutation-positive patients because such families likely have multiple living affected members. Selecting sporadic cancer patients from cancer clinics or hospitals may underestimate survival time in the comparison group of possibly more advanced stages of cancer. In addition, ascertaining a control group of patients from such sources or from a cancer registry does not involve direct BRCA1 or BRCA2 mutation testing.
Other strengths of this study include the study subjects' lack of awareness of their mutation status, the large sample size, and relative genetic homogeneity. Our study population consisted of volunteer Ashkenazi Jews in the Washington, DC, area. More participants had a positive family history of breast or ovarian cancer than would be expected (15). We know of no reasons for volunteering to be related to both BRCA1 and/or BRCA2 mutation carrier status and survival time or for family history, timing of cancer detection, and treatment to favor one survival comparison group over the other in our study. Survival studies of heterogeneous populations include numerous BRCA1 and BRCA2 mutations; in contrast, this community-based study of Ashkenazi Jews compares survival among individuals who differ at one of only three specific BRCA1 and BRCA2 mutation sites.
While the exact functions of the BRCA1 and BRCA2 genes remain elusive (21), the potential effect of mutations in these genes on survival among cancer patients has important clinical and screening implications. Our results from a community-based study suggest that BRCA1 and/or BRCA2 mutation carrier status does not have a major impact on overall survival time among patients with breast or ovarian cancer. Thus, screening for BRCA1 and/or BRCA2 mutations does not contribute prognostic information about survival among women with breast or ovarian cancer.
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Notes |
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APPENDIX |
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This is the same basic approach we took in estimating penetrance in other reports from this study (15,18). The main difference is that the outcomes in those studies were incidence of cancer so the (retrospective) follow-up in those cohorts began at birth; therefore, the weights depended only on the Mendelian probabilities. Here, on the other hand, the outcome is death after diagnosis with breast cancer. Therefore, the weights are the fractions of carriers in the two cohorts of affected relatives (that is, those of carriers and those of noncarriers) who were diagnosed during the age interval ti - 1to ti. By applying rules of conditional probability, we calculated the weights as the product of the probability of the relative being born a carrier, given the participant's genotype, obtained from Mendelian principles (15,18), and the probability of the relative developing cancer during age interval ti-1 to ti, given the participant's genotype (bi+ for carriers or bi- for noncarriers). Here, bi+ can be calculated as bi+= Bi+- B+i-1, where Bi+ is cumulative probability of developing cancer through interval i in carriers (15); bi- can be obtained analogously. By assuming that censoring due to death from other causes before the diagnosis of cancer is independent of carrier status, we can calculate the proportion of carriers among the carrier participants' first-degree relatives diagnosed during interval i as
![]() | (1) |
and, analogously the weight for affected carriers among the noncarrier participants' first-degree relatives diagnosed during interval i as
![]() | (2) |
where p is the mutant allele frequency in the study population.
The probability of survival through year j, after diagnosis during interval i, among affected first-degree relatives of carriers can be expressed as
![]() | (3) |
where Sij+ and Sij-are the probabilities of survival through year j among affected carriers and noncarriers, respectively, who were diagnosed during interval i. Similarly, the probability of survival through year j, after diagnosis during interval i, among affected first-degree relatives of noncarriers can be expressed as
![]() | (4) |
By solving Equations 3 and 4 for two unknowns, we can express Sij+ and Sij- for fixed j as
![]() | (5) |
and
![]() | (6) |
in terms of quantities estimable from our data.
We assumed a frequency P = .0112 for any of the three
specific alleles in our study in order to estimate
Ci+
and Ci-. To
estimate Aij+ and
Aij- from Equations 5
and 6, we used Kaplan-Meier estimates for probability of survival
after diagnosis among the affected relatives of carriers and of
noncarriers, respectively, based on our data (Fig. 1).
The 5- and 10-year survival probabilities for carriers and noncarriers for all ages at diagnosis were approximated using binomial regression. The two binomial variables for each interval i corresponded to the groups of affected relatives of carriers and noncarriers, respectively. The binomial numerators were the numbers of deaths during interval j; the denominators were the differences between the number of women in the groups during the interval j and half the number of censored in the groups during the interval j. A model with identity link (19) was fitted with regression variables Aij- and Aij+ for relatives of carriers and noncarriers, respectively, and unknown regression coefficients Sij+ and Sij-.
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REFERENCES |
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1 Johannsson OT, Ranstam J, Borg A, Olsson H. Survival of BRCA1 breast and ovarian cancer patients: a population-based study from southern Sweden. J Clin Oncol 1998;16:397-404.[Abstract]
2 Verhoog LC, Brekelmans C, Seynaeve C, van den Bosch L, Dahmen G, van Geel AN, et al. Survival and tumour characteristics of breast-cancer patients with germline mutations of BRCA1. Lancet 1998;351:316-21.[Medline]
3 Haas B, Robson M, Rajan P, Rosen PP, Borgen P, Brown K, et al. BRCA-associated breast cancer: absence of a characteristic immunophenotype [abstract 360]. Proceedings of the ASHG; 1997.
4 Robson M, Gilewski T, Haas B, Levine D, Lesser M, Borgen P, et al. BRCA-associated breast cancer among young Jewish women [abstract 437A]. Proceedings of the ASHG; 1997.
5 Foulkes WD, Wong N, Brunet JS, Begin LR, Zhang JC, Martinez JJ, et al. Germ-line BRCA1 mutation is an adverse prognostic factor in Ashkenazi Jewish women with breast cancer. Clin Cancer Res 1997;3:2465-9.[Abstract]
6 Porter DE, Cohen BB, Wallace MR, Smyth E, Chetty U, Dixon JM, et al. Breast cancer incidence, penetrance and survival in probable carriers of BRCA1 gene mutation in families linked to BRCA1 on chromosome 17q12-21. Br J Surg 1994;81:1512-5.[Medline]
7
Rubin SC, Benjamin I, Behbakht K, Takahashi H, Morgan MA,
LiVolsi VA, et al. Clinical and pathological features of ovarian cancer in women with germ-line
mutations of BRCA1. N Engl J Med 1996;335:1413-6.
8 Marcus JN, Watson P, Page DL, Narod SA, Lenoir GM, Tonin P, et al. Hereditary breast cancer: pathobiology, prognosis, and BRCA1 and BRCA2 gene linkage. Cancer 1996;77:697-709.[Medline]
9 Karp SE, Tonin PN, Begin LR, Martinez JJ, Zhang JC, Pollak MN, et al. Influence of BRCA1 mutations on nuclear grade and estrogen receptor status of breast carcinoma in Ashkenazi Jewish women. Cancer 1997;80:435-41.[Medline]
10 Breast Cancer Linkage Consortium. Pathology of familial breast cancer: differences between breast cancers in carriers of BRCA1 and BRCA2 mutations and sporadic cases. Lancet 1997;349:1505-10.[Medline]
11 Eisinger F, Stoppa-Lyonnet D, Longy M, Kerangueven F, Noguchi T, Bailly C, et al. Germ line mutation at BRCA1 affects the histoprognostic grade in hereditary breast cancer. Cancer Res 1996;56:471-4.[Abstract]
12 Struewing JP, Abeliovich D, Peretz T, Avishai N, Kaback MM, Collins FS, et al. The carrier frequency of the BRCA1185delAG mutation is approximately 1 percent in Ashkenazi Jewish individuals [published erratum appears in Nat Genet 1996;12:110]. Nat Genet 1995;11:198-200.[Medline]
13 Oddoux C, Struewing JP, Clayton CM, Neuhausen S, Brody LC, Kaback M, et al. The carrier frequency of the BRCA2 6174delT mutation among Ashkenazi Jewish individuals is approximately 1%. Nat Genet 1996;14:188-90.[Medline]
14 Roa BB, Boyd AA, Volcik K, Richards CS. Ashkenazi Jewish population frequencies for common mutations in BRCA1 and BRCA2. Nat Genet 1996;14:185-7.[Medline]
15
Struewing JP, Hartge P, Wacholder S, Baker SM, Berlin M,
McAdams M, et al. The risk of cancer associated with specific mutations of BRCA1 and BRCA2
among Ashkenazi Jews. N Engl J Med 1997;336:1401-8.
16 Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc 1958;53:457-81.
17 Mantel N. Evaluation of survival data and two new rank order statistics arising in its consideration. Cancer Chemother Rep 1966;50:163-70.[Medline]
18 Wacholder S, Hartge P, Struewing JP, Pee D, McAdams M, Brody L, et al. The kin-cohort study for estimating penetrance. Am J Epidemiol 1998;148:623-30.[Abstract]
19 Wacholder S. Binomial regression in GLIM: estimating risk ratios and risk differences. Am J Epidemiol 1986;123:174-84.[Abstract]
20 Kerber RA, Slattery ML. Comparison of self-reported and database-linked family history of cancer data in a case-control study. Am J Epidemiol 1997;146:244-8.[Abstract]
21 Zhang H, Tombline G, Weber BL. BRCA1, BRCA2, and DNA damage response: collision or collusion? Cell 1998;92:433-6.[Medline]
Manuscript received May 7, 1998; revised October 30, 1998; accepted November 28, 1998.
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