Abstract
Background:
Genetic testing for hereditary breast cancer has implications for breast cancer decision-making. We examined genetic testing rates, factors associated with testing, and the relationship between genetic testing and contralateral prophylactic mastectomy (CPM).
Methods:
Patients with breast cancer (2000-2015) from The Health of Women Study® were identified and categorized as low, moderate, or high-likelihood of genetic mutation using a previously published scale[1],[2] based on period-relevant national guidelines incorporating age and family history. Genetic testing and CPM rates were compared using univariate and multivariate logistic regression.
Results:
Among 4,170 patients (median age 56-years), 38% were categorized as high-likelihood of having a genetic mutation. Among high-likelihood women, 67% underwent genetic testing, the odds of which were increased among women of higher-education and White-race (p<0.001). Among 2,028 patients reporting surgical treatment, 385 (19%) chose CPM. CPM rate was highest among mutation-positive women (41%), but 26% of women with negative tests still underwent CPM. Independent of test result, genetic testing increased the odds of CPM on multivariate analysis (adjusted-OR:1.69, 95%CI:1.29-2.22).
Conclusions:
Genetic testing rates were higher among women at high-likelihood of mutation carriage, but one-third of these women were not tested. Racial disparities persisted, highlighting the need to improve testing in non-White populations. CPM rates were associated with mutation-carriage and genetic testing, but many women chose CPM despite negative testing, suggesting that well-educated women consider factors other than cancer mortality in selecting CPM.
Keywords: Breast cancer, BRCA, genetic risk, genetic testing, contralateral prophylactic mastectomy, racial disparities
INTRODUCTION
Approximately 5-10% of all breast cancers can be linked to a known genetic mutation, of which >50% are pathogenic variants in the BRCA1 and BRCA2 genes[3]. Following a breast cancer diagnosis, women may elect to pursue testing for genetic breast cancer syndromes based on a clinician’s assessment of their likelihood of harboring a deleterious mutation. Mutation status has significant implications for management, including treatment choices, post-treatment surveillance, familial risk assessment, and prevention of and screening for future cancers.
While the scope of genetic testing has markedly increased in recent years, a significant fraction of patients at increased breast cancer risk still go untested. A persistent challenge is defining criteria for identifying the subgroup of patients who should be recommended to undergo genetic testing. Multiple organizations offer guidelines defining criteria that should prompt referral to genetic counseling and testing—i.e. clinical factors that increase the likelihood of genetic susceptibility to breast cancer. The American Society of Clinical Oncology[2],[3] and National Comprehensive Cancer Network (NCCN)[4],[5] recommend considering genetic testing for breast cancer in patients diagnosed at early age, bilateral breast cancer, ER-/PR-/Her2- disease status, Ashkenazi Jewish ancestry, strong family history of breast and/or ovarian cancer, or a combination of these characteristics. Most recently, the American Society of Breast Surgeons in 2019 published a consensus guideline advocating for much broader testing of all women with a personal history or new diagnosis of breast cancer[8]. Over the past decade, the availability and acceptance of genetic testing has increased with the development of commercial tests, establishment of practice guidelines, and increased insurance coverage. Genetic testing utilization increased by 37% immediately following Angelina Jolie’s revelation in 2013 that she underwent bilateral prophylactic mastectomy following her receipt of BRCA1/BRCA2 testing, but the use of post-testing follow-up services actually declined following Jolie’s disclosure, making it unclear how women have been applying that information in medical decision making[9].
Knowledge of mutation status can allow women with breast cancer to pursue risk-reducing measures in the contralateral breast, such as contralateral prophylactic mastectomy (CPM), chemoprevention, targeted biologic agents (e.g. PARP inhibitors[10]), and/or enhanced surveillance strategies. Rates of CPM in the United States have been increasing[11] and previous studies have begun to identify factors associated with this trend, including: a predisposing genetic mutation, physician recommendations, higher education status, White race, young age, breast MRI utilization, and post-mastectomy reconstruction[12]–[15]. Although the presence of a deleterious genetic mutation is known to increase rates of CPM, a significant fraction of women who chose to undergo CPM are gene-mutation negative, leading some to suggest that women may be inadequately informed about the actual risk of contralateral breast cancer when they are gene-mutation negative[14].
In this study, we sought to 1) characterize the rates of genetic testing among women with breast cancer in a unique and highly educated population, 2) identify factors associated with genetic testing among women with a high likelihood of a genetic predisposition to breast cancer, and 3) describe rates of CPM as they relate to genetic testing and genetic mutation status in this population.
MATERIALS AND METHODS
Study Population
The data source was the Health of Women (HOW) Study™—a multi-stage online cohort study led by the Dr. Susan Love Research Foundation with the goal of better understanding the causes of breast cancer[16]. This survey-based study, comprised of multiple sequentially released patient surveys from 2012 to 2019, tracked individuals over time including information on health, family history, lifestyle, and breast cancer diagnosis and treatment. Recruitment was done through the Dr. Susan Love Research Foundation and social media. There were no specific restrictions on geographic location, occupation, race/ethnicity, or breast cancer status, but participants must have had access to the internet. Our study received ethics approval from the University of Washington’s Internal Review Board (STUDY00002971) and from the HOW Program.
Our population included women ≥21 years of age diagnosed with unilateral breast cancer (all histologic subtypes) between 2000 and 2015.
Stratification of Likelihood of Harboring a Genetic Mutation
We classified all women into high-, moderate-, or low-likelihood of harboring a genetic mutation using a stratification schema adopted from previous publications on predictors of genetic testing among women with breast cancer (Figure 1)[1], [2]. This scale is largely based on NCCN 2007 guidelines for genetics referral[17] and includes factors such as age at diagnosis and family history of breast and ovarian cancer. The HOW Study® did not contain information on Ashkenazi Jewish ancestry, so we were unable to include this characteristic in our stratification. Similarly, triple negative receptor status was not considered in the risk stratification schema as this information may not have been readily available for women diagnosed in earlier years and due to lack of pathologic corroboration of histologic subtype in the dataset. This means that women with triple negative tumors were not automatically considered to be at high-likelihood of harboring a mutation but were categorized based on the factors in the mutation-likelihood stratification schema in Figure 1. Women with tumors of all histologic subtypes were stratified and included in the analyses. Our classification schema was designed to be conservative, meaning that women categorized as “high-likelihood” would have been clear candidates for genetic testing throughout the entire study period.
Figure 1.
Stratification of likelihood of harboring a genetic mutation
Legend: Stratification of likelihood of harboring a genetic mutation was derived from a previously published categorization scheme[1], [2] based on NCCN 2007 guidelines for genetic referral[17]
Data Analysis
Primary outcomes included: receipt of genetic testing and surgical treatment with mastectomy with CPM. The survey data did not specify whether a mutation was classified as deleterious versus a variant of uncertain significance. Demographic information, including race, ethnicity, education, marital status, health insurance type, and comorbidities was assessed. Given that our population was predominantly of White race, race was collapsed into “White” and “non-White” categories, the latter of which included Black, Asian, and Pacific Islander. Other relevant characteristics available in the dataset included: history of atypia on breast biopsy, parity, receipt of genetic counseling, and type of provider who relayed genetic testing results. Self-reported breast cancer-specific information such as age at diagnosis, tumor size, and stage, was also ascertained, though could not be corroborated by pathologic data.
We analyzed patient and disease characteristics, genetic testing rates, genetic test results, and CPM rates separately within mutation-likelihood categories using two-sample t-tests and chi-squared tests for continuous and categorical variables, respectively. Multivariable logistic regression was used to estimate the odds of obtaining genetic testing by various patient characteristics among women in the high likelihood category. In order to accomplish this, we performed a comprehensive literature review to select variables a priori which have been found to be associated with genetic testing. We then evaluated the association of each of these factors with genetic testing in our data and used these univariate analyses to construct our multivariable logistic regression model. The odds of CPM based on various patient characteristics was similarly estimated in a separate multivariable analysis. A sensitivity analysis of the factors associated with CPM was performed, examining the subpopulation of patients who underwent mastectomy. Of note, breast cancer pathologic stage at diagnosis was not included in the multivariable analyses as all data were self-reported and could not be corroborated. Given that family history forms the basis for the mutation-likelihood categorization, it was not included as a separate variable in the multivariable analysis, but we conducted an exploratory analysis including family history in place of mutation-likelihood category in a multivariable model of CPM.
A p-value less 0.05 was used as the statistical significance level. Statistical analyses were performed using STATA/IC version 14[18].
RESULTS
A total of 4,170 women with breast cancer were included in this study (Table 1). Median age at diagnosis was 56 years. Median time from cancer diagnosis to survey completion was 57 months. The majority of the study population was White (97%) and had attained higher-education degrees (77% university or graduate school). Eighty-five percent (n=3,484) of women reported early-stage disease at diagnosis, 12% (n=515) stage III disease, and 2.3% (n=97) stage IV disease. In our cohort, 672 (16%), 1,922 (36%), and 1,576 (48%) women were stratified into low, moderate, and high likelihood of mutation carriage, respectively, based on the previously outlined schema (Figure 1). There were no significant differences in self-reported cancer stage, history of atypia, and education between mutation-likelihood category.
Table 1.
Cohort characteristics
| All (n= 4,170) | Low likelihood (n= 672) | Moderate likelihood (n= 1,922) | High likelihood (n= 1,576) | |
| Female Sex | 4,156 (100%) | 672 (100%) | 1,922 (100%) | 1,562 (99%) |
| Age at breast cancer diagnosis (%) | ||||
| 21-39 | 689 (17%) | 0 (0%) | 0 (0%) | 689 (44%) |
| 40-49 | 1,208 (29%) | 0 (0%) | 880 (46%) | 328 (21%) |
| 50-59 | 1,373 (33%) | 401 (60%) | 637 (33%) | 335 (21%) |
| ≥60 | 900 (22%) | 271 (40%) | 405 (21%) | 224 (14%) |
| Highest level of education | ||||
| Less than college | 917 (22%) | 158 (24%) | 434 (23%) | 325 (21%) |
| 4-year college | 1,299 (31%) | 185 (28%) | 601 (31%) | 513 (33%) |
| Graduate or professional school | 1,719 (41%) | 296 (44%) | 764 (40%) | 659 (42%) |
| Not specified | 235 (5.6%) | 33 (4.9%) | 123 (6.4%) | 79 (5.0%) |
| Race | ||||
| White race | 4,014 (96%) | 656 (98%) | 1,864 (97%) | 1,494 (95%) |
| Black race | 69 (1.7%) | 7 (1.0%) | 27 (1.4%) | 35 (2.2%) |
| Other | 87 (2.1%) | 9 (1.3%) | 31 (1.6%) | 47 (3.0%) |
| Hispanic ethnicity | 108 (2.6%) | 14 (2.1%) | 41 (2.1%) | 53 (3.4%) |
| Parous | 3,128 (75%) | 539 (17%) | 1,489 (48%) | 1,100 (35%) |
| History of atypia | 649 (21%) | 85 (13%) | 301 (46%) | 263 (41%) |
| Marital status | ||||
| Married or partnered | 3,177 (76%) | 513 (76%) | 1,472 (77%) | 1,192 (76%) |
| Divorced | 440 (11%) | 80 (12%) | 214 (11%) | 146 (9.3%) |
| Widowed | 139 (3.3%) | 28 (4.2%) | 67 (3.5%) | 44 (2.8%) |
| Never married | 385 (9.2%) | 45 (6.7%) | 158 (8.2%) | 182 (12%) |
| Not specified | 29 (0.7%) | 6 (0.9%) | 11 (0.6%) | 12 (0.8%) |
| Breast cancer pathologic stage | ||||
| Carcinoma in situ | 818 (20%) | 137 (20%) | 367 (19%) | 314 (20%) |
| I | 1,325 (32%) | 213 (32%) | 622 (32%) | 490 (31%) |
| II | 1,341 (32%) | 207 (31%) | 623 (32%) | 511 (32%) |
| III | 515 (12%) | 77 (12%) | 242 (13%) | 196 (12%) |
| IV | 97 (2.3%) | 18 (2.7%) | 43 (2.2%) | 36 (2.3%) |
| Not specified | 74 (1.8%) | 20 (3.0%) | 25 (1.3%) | 29 (1.8%) |
Overall, 47% of women in our cohort underwent genetic testing: 67% (n=1,055; 95% CI 65%-69%) of women in the high likelihood category, 42% (n=808; 95% CI 40%-44%) in moderate likelihood, and 16% (n=110; 95% CI 14%-19%) in the low likelihood category underwent genetic testing (p<0.001). Genetic testing rates did not vary significantly over time (data not shown). Of women in the high likelihood category who underwent genetic testing, 13% (n=141; 95% CI 11%-16%) had a positive test result, compared to 6.9% (n=56; 95% CI 5.3%-8.9%) and 7.3% (n=8; 95% CI 3.2%-14%) of moderate and low likelihood women, respectively (p<0.001). Among all women tested, 67% (n=1,313) reported meeting with a genetic counselor. Women in the high mutation-likelihood category were significantly more likely to have met with a genetic counselor, compared to those in the moderate and low likelihood categories (70% vs. 65% and 49%, respectively, p<0.001). Sixty percent of all women tested received their test results from a genetic counselor, with oncologists (19%), surgeons (11%), and primary care providers (5%) being the next most common providers disclosing test results. Among women in the low likelihood category, 5.5% learned their test results from a lab report and not a provider. The proportion of test results conveyed by a genetic counselor did not significantly change throughout the study period.
There was variability in rates of genetic testing among women in the high mutation-likelihood category by patient characteristics (Table 2). In a multivariable logistic regression model of factors associated with genetic testing in women in the high likelihood category, higher level of education, White race (compared to non-White race), and younger age at diagnosis were significantly associated with testing (Table 3). Marital status and parity were evaluated but found not to be significantly associated with genetic testing on multivariable analysis. Hispanic ethnicity (compared to non-Hispanic ethnicity) and history of atypia were also not associated with genetic testing in univariate or multivariable analyses.
Table 2.
Rates of genetic testing in women at high mutation-likelihooda by patient characteristics
| All women at high mutation-likelihooda n= 1,576 | |||
| Genetic testing | No genetic testing | p-value | |
| Total (% of all high-risk) | 1,055 (67%) | 521 (33%) | <0.001 |
| Age category | <0.001 | ||
| 21-39 years | 578 (55%) | 111 (21%) | |
| 40-49 years | 231 (22%) | 97 (19%) | |
| 50-59 years | 168 (16%) | 167 (32%) | |
| >60 years | 78 (7.4%) | 146 (28%) | |
| Highest level of education | 0.001 | ||
| Less than college | 189 (18%) | 136 (26%) | |
| College | 357 (34%) | 156 (30%) | |
| More than college | 462 (44%) | 197 (38%) | |
| Not reported | 47 (4.5%) | 47 (6.1%) | |
| White race | 1,003 (95%) | 491 (94%) | 0.743 |
| Hispanic ethnicity | 33 (62%) | 20 (38%) | 0.459 |
| Parous | 727 (66%) | 373 (34%) | 0.294 |
| History of Atypia | 187 (71%) | 76 (29%) | 0.544 |
| Marital status | 0.014 | ||
| Married or partnered | 821 (78%) | 371 (71%) | |
| Never married, divorced, widowed. | 227 (22%) | 145 (28%) | |
| Not reported | 7 (0.7%) | 5 (1%) | |
Women were stratified as high mutation-likelihood if they met one of the following criteria: Age ≤40y, ≥1 primary breast cancer, ≥1 1st degree relative with ovarian cancer, ≥2 1st degree relatives with breast cancer, or ≥1 male relative with breast cancer
Table 3.
Multivariable analysis of factors associated with genetic testing among women in the high mutation-likelihood categorya
| Odds Ratio | 95% Confidence Interval | p value | |
| Highest level of education | |||
| Less than college | Reference category | - | - |
| College | 1.27 | 0.92 – 1.74 | 0.146 |
| More than college | 1.49 | 1.10 – 2.01 | 0.010 |
| White race | 1.75 | 1.01 – 3.02 | 0.045 |
| Younger ageb | 1.07 | 1.06 – 1.08 | <0.001 |
| Married or partnered | 1.31 | 0.99 – 1.72 | 0.056 |
Women were stratified as high mutation-likelihood if they met one of the following criteria: Age ≤40y, ≥1 primary breast cancer, ≥1 1st degree relative with ovarian cancer, ≥2 1st degree relatives with breast cancer, or ≥1 male relative with breast cancer
Age was included in the model as a continuous variable. Odds ratio represents higher odds of testing for those of younger age at diagnosis.
The survey module on type of surgical treatment received was completed and reported by 49% of all women (n=2,028). Nineteen percent of these women (n=385) underwent mastectomy plus CPM, 50% (n=1,009) underwent breast conservation, and 31% (n=634) underwent unilateral mastectomy. Odds of CPM was significantly greater among patients who underwent genetic testing versus those who did not. Twenty-eight percent (n=239) of women who had genetic testing (n= 860) underwent CPM, whereas only 13% (n=146) of women who did not undergo genetic testing (n=1,168) had this procedure (p<0.001). Among women who tested positive for a mutation (n=95), 41% (n=39) underwent CPM (vs. not tested, p<0.001), compared to a rate of CPM of 26% (n=192) among women who tested negative for a mutation (n=737, vs not tested p<0.001). This association persisted after adjusting for race, age, level of education, and pre-test mutation-likelihood category (OR 1.69, 95% CI 1.29–2.22, p<0.001). On multivariable analysis, both positive (OR 2.79, 95% CI 1.70-4.56, p<0.001) and negative (OR 1.56, 95% CI 1.17-2.06, p<0.002) genetic test results had higher odds of CPM compared to those not tested (Table 4). Younger age was also associated with higher odds of CPM on multivariable analysis (Table 4). Marital status, receipt of genetic counseling, and provider communicating genetic test results were evaluated but found not to be associated with CPM on multivariable analysis and were not included in the model. A sensitivity analysis was repeated in the subgroup of women who underwent mastectomy (unilateral or CPM) with similar findings, whereby the magnitude and direction of all associations persisted (Table 5).
Table 4.
Multivariable analysis of factors associated with contralateral prophylactic mastectomy
| Odds Ratio | 95% Confidence Interval | p value | |
|---|---|---|---|
| Mutation-likelihood | |||
| Low | Reference | - | - |
| Moderate | 1.47 | 0.96 – 2.42 | 0.078 |
| High | 1.46 | 0.92 – 2.32 | 0.111 |
| Genetic testing | |||
| Not tested | Reference | - | - |
| Positive test | 2.79 | 1.70-4.56 | <0.001 |
| Negative test | 1.56 | 1.17-2.06 | 0.002 |
| Highest level of education | |||
| Less than college | Reference category | - | - |
| College | 0.71 | 0.52 – 0.98 | 0.035 |
| More than college | 0.78 | 0.58 – 1.05 | 0.097 |
| White race | 2.15 | 0.94 – 4.91 | 0.069 |
| Younger agea | 1.04 | 1.03– 1.06 | <0.001 |
Age was included in the model as a continuous variable. Odds ratio represents higher odds of contralateral prophylactic mastectomy for those of younger age at diagnosis.
Table 5.
Multivariable analysis of factors associated with contralateral prophylactic mastectomy, among all patients who underwent mastectomy
| Odds Ratio | 95% Confidence Interval | p value | |
|---|---|---|---|
| Mutation-likelihood | |||
| Low | Reference | - | - |
| Moderate | 1.46 | 0.92 – 2.33 | 0.113 |
| High | 1.16 | 0.70 – 1.94 | 0.563 |
| Genetic testing | |||
| Not tested | Reference | - | - |
| Positive test | 2.93 | 1.59-5.41 | <0.001 |
| Negative test | 1.96 | 1.26-2.38 | <0.001 |
| Highest level of education | |||
| Less than college | Reference category | - | - |
| College | 0.78 | 0.54 – 1.12 | 0.174 |
| More than college | 0.85 | 0.60 – 1.20 | 0.350 |
| White race | 2.45 | 0.99 – 6.08 | 0.054 |
| Younger agea | 1.04 | 1.03– 1.06 | <0.001 |
Age was included in the model as a continuous variable. Odds ratio represents higher odds of contralateral prophylactic mastectomy for those of younger age at diagnosis.
As an exploratory analysis, we tested whether the association between genetic testing and CPM persisted with inclusion of family history of breast and ovarian cancer, separate from mutation likelihood category, in a multivariable model. In this model, after adjusting for family history of breast cancer, family history of ovarian cancer, education, white race, and age, the odds of CPM remained significantly higher with genetic testing (positive test: OR 2.11, 95% CI 1.17-3.82, p=0.013; negative test: OR 1.55, 95% CI 1.10-2.18, p<0.011) compared to no genetic testing. Family history of ovarian cancer was not significantly associated with CPM. Family history of 1 or more 1st degree relatives with breast cancer increased odds of CPM in this multivariable analysis (Table 6).
Table 6.
Exploratory multivariable analysis of factors associated with contralateral prophylactic mastectomy (CPM)
| Odds Ratio | 95% Confidence Interval | p value | |
|---|---|---|---|
| Family history of breast cancer | |||
| None | Reference | - | - |
| ≥1 2nd degree relative | 1.12 | 0.74 – 1.70 | 0.584 |
| 1 1st degree relative | 1.63 | 1.17 – 2.29 | 0.004 |
| ≥2 1st degree relative | 2.15 | 1.20 – 3.86 | 0.10 |
| Any family history of ovarian cancer | 0.95 | 0.63 – 1.43 | 0.812 |
| Genetic testing | |||
| Not tested | Reference | - | - |
| Positive test | 2.11 | 1.17-3.82 | 0.013 |
| Negative test | 1.55 | 1.10-2.18 | 0.011 |
| Highest level of education | |||
| Less than college | Reference | - | - |
| College | 0.53 | 0.36 – 0.78 | 0.001 |
| More than college | 0.70 | 0.49 – 0.99 | 0.045 |
| White race | 3.57 | 1.23 – 10.36 | 0.019 |
| Younger agea | 1.05 | 0.036 – 0.066 | <0.001 |
Age was included in the model as a continuous variable. Odds ratio represents higher odds of contralateral prophylactic mastectomy for those of younger age at diagnosis.
DISCUSSION
In a national cohort of women with breast cancer, 47% of women underwent genetic testing, and testing rates were significantly higher in those at increased likelihood of mutation carriage based on family history and age at diagnosis. White race, younger age at diagnosis, and higher level of education were associated with increased rates of genetic testing among women stratified as high likelihood of mutation carriage. In this study, women who underwent CPM were more likely to have undergone genetic testing, and this association persisted even in cases of a negative test result.
The overall rate of genetic testing in our study is higher than previously reported[6],[9],[20]. In two survey studies of over 1,000 women diagnosed with early-onset breast cancer published in 2005 and 2006, fewer than 15% of women reported undergoing genetic testing, in an era when testing was more restrictive and costly[6],[7]. In a single-institution 2016 study, 34% of women with breast cancer who met NCCN guidelines for genetic testing were referred for genetic counseling and of those referred, approximately three-fourths underwent genetic testing[21]. Differences are partially explained by changes over time in the awareness and availability of genetic testing. Specifically, the combination of the 2014 Supreme Court ruling against gene patents, heightened public awareness of genetic testing, and the increased availability and affordability of multigene panels likely explain large differences in genetic testing rates among breast cancer patients in our own versus historical studies[21],[22]. In addition, our study population was largely White, highly educated, and given their voluntary participation in an online research study, likely to be more informed and motivated to seek out genetic testing, all of which contributed to our findings of greater overall rates of genetic testing. In a study of concordance of BRCA 1/2 testing with NCCN guidelines in a cohort of The HOW study® participants, 31% of whom had a personal history of breast cancer, 18.8% of women reported undergoing BRCA 1/2 testing[25]. The authors do not explicitly report the rate of testing in the subset of women with breast cancer or in women with breast cancer who met NCCN guidelines for testing, making it difficult to compare their rate of genetic testing with that of our study. It is notable, however, that the reported rate of testing in this cohort is high, likely also reflective of the characteristics of The HOW Study® participants.
We found that genetic testing was significantly associated with the pre-test likelihood of harboring a genetic mutation (i.e. mutation-likelihood category) and testing rates were appropriately much higher (67%) among those at highest mutation-likelihood based on family history and age at diagnosis. These results suggest providers are appropriately triaging patients to genetic counseling and/or testing based on known risk factors. It is worth noting that while the stratification schema[1], [2] used in this study is supported by our results, it is not the same method used by clinicians when assessing risk in an individual patient. It is based primarily on age at diagnosis and family history, but fails to incorporate important risk factors, such as Ashkenazi Jewish ancestry and receptor status, as well as other patient or provider factors that may impact the decision to refer for testing. In our study, the majority of patients who underwent testing (67%) appropriately received genetic counseling, with genetic counselors being the provider most likely to convey testing results, followed by oncologists as the second most likely provider. To our knowledge, this is the first study to elucidate which members of the care teams convey genetic testing results.
Of concern, however, is the sizeable fraction of women at high likelihood of mutation carriage (33%) who are not undergoing genetic testing despite clear potential benefit, especially in light of the 13% yield of diagnosing a genetic mutation in such women. Recent studies have shown that both physician recommendations[17],[23] and patient attitudes towards risks (e.g. cost, health insurance discrimination) and benefits (e.g. chemoprophylaxis, prophylactic oophorectomy) of genetic testing correlate significantly with testing uptake[20]. One prior population-based study by McCarthy et al showed that only 53% of breast cancer patients at high risk of mutation carriage reported that their physician recommended genetic testing[1]. In our study, none of the women who were stratified as high mutation-likelihood and did not undergo genetic testing received genetic counseling. This suggests that a missed opportunity by providers not referring to genetic counseling and/or limited availability of these services may contribute to our findings.
In this population, we also found that White race, younger age at diagnosis, and higher level of education were significantly associated with higher rates of testing, despite the homogeneity of this study population. We have confirmed data from smaller convenience-sample survey studies showing that genetic testing is more prevalent among younger, White, and high-risk patients as defined by a strong family history[7],[24],[25]. Despite higher percentages of non-White women in the high mutation-likelihood group, non-White race was associated with lower rates of testing, after adjusting for potential confounders. Racial inequality in genetic testing has been described previously[26],[27], dating back to when BRCA1/2 testing became commercially available[30]. A 2005 study found that rates of genetic counseling were more than 72% lower among Black women[27]. A 2017 survey-based study showed that among 945 Black women treated for breast cancer between 2007–2009, only 27% had BRCA 1/2 testing[2]. This disparity is felt to be multifactorial, including factors such as awareness and attitudes towards testing as well as inferior access to genetic counseling and testing services[31]. Our results reiterate the importance of focused efforts to raise awareness and availability of genetic testing among minority populations, especially given the finding that non-White women with breast cancer may also be at high-risk of mutation carriage[32].
This study is novel because we were able to assess the association between surgical treatment and receipt of genetic testing and test results across a unique cohort. Rates of CPM among patients with unilateral breast cancer have been on the rise nationally, with a three-fold increase in incidence from 2000-2011[33], [34]. Factors associated with this trend include higher education, young age at diagnosis, White race, post-mastectomy reconstruction, and breast MRI. Our overall observed rate of CPM was 19% in a largely White, educated, and highly motivated population. This rate mirrors that observed in an earlier survey study of 2,500 women which showed a 20% rate of CPM among White women treated for early-stage breast cancer, who were significantly more likely to choose CPM compared to non-White women[35].
We observed that rates of CPM varied significantly with genetic testing result and with receipt of genetic testing itself. Not surprisingly, the highest rate of CPM was observed among women who tested positive for a mutation (41%). Other studies examining the impact of BRCA status on surgical treatment for breast cancer have similarly shown that rates of CPM are significantly higher in gene-positive women as compared to gene-negative women[12], [36]. In our study population, rates of CPM were also significantly greater (28% vs. 13%) among women who had testing versus those who did not, and the association persisted after adjusting for age at diagnosis, level of education, race, mutation-likelihood category, family history of breast cancer, family history of ovarian cancer, and genetic test result. There are several possible explanations for this, including fear of developing a second breast cancer even in absence of a predisposing genetic mutation, desire to avoid surveillance, and improved symmetry and cosmetic outcomes, among others. It is possible that those women with breast cancer who are most proactive in seeking genetic risk assessment are also proactive in pursuing risk-reducing surgery through CPM. These findings may also be reflective our highly educated cohort. The high rate of CPM noted in our study population and the finding in other studies that higher education confers a 5-fold higher risk of undergoing CPM[37] suggest that other factors aside from knowledge gaps about risks and benefits of CPM may affect a woman’s decision to proceed with CPM. While our survey-based study cannot elucidate the factors underlying this relationship, the decisions of this group of highly educated and motivated women suggest that well-informed women may choose CPM for reasons that go beyond quantitative risk assessment. Qualitative studies providing a better understanding of the nuances of this decision, which go beyond consideration of the potential oncologic benefit and surgical risk, can inform and improve counseling and value-consistent decisions for all patients.
There are important limitations of this study. The homogeneity of our study population—97% White and highly-educated—restricts generalizability. Our results provide insight into genetic testing rates and surgical treatment choices among this population of well-informed women and can inform how we counsel patients on these complex decisions. However, it will be important in future studies to examine these questions among a more racially and sociodemographically diverse cohort. Racial disparities in genetic testing are evident even in this highly homogenous cohort of educated and motivated women, highlighting the need for focused efforts to increase testing in minority populations. Additionally, we were unable to assess underlying provider or patient decision factors for genetic testing and CPM, only what action was taken. For CPM, for example, we were unable to assess the relationship between CPM and MRI utilization or availability of breast reconstruction, both of which could play a role in the decision to undergo CPM. Lastly, given that enrollment into The HOW Study® is voluntary and can occur at any time relative to breast cancer diagnosis, there is the potential for selection and recall bias. A few studies have assessed the concordance between self-report of breast cancer treatment and prognostic factors and medical record data, demonstrating high concordance, particularly for general treatment categories, such as breast surgery type [38]–[42]. In a recent study of accuracy of self-reported data in a population of young, predominantly White, and highly-educated women recruited from the Dr. Susan Love Research Foundation Army of Women, patient-reported receipt of systemic therapy was found to be highly accurate more than 5 years after diagnosis[42]. Accuracy of self-reported surgery type was not specially evaluated in this study, but their results, along with prior studies, support the use of patient-reported data to elucidate associations that can be further tested in more generalizable populations with corroborated data.
This study is one of the first to utilize this unique dataset—a collaboration between researchers, clinicians, and advocates—which provides an opportunity to study breast cancer treatment patterns. The HOW Study® was recruited from the Army of Women, a program of the Dr. Susan Love Research Foundation. It is a group of highly educated, informed, and motivated women that can shed a different perspective on the multifaceted decisions of undergoing genetic testing and CPM. The HOW Study® incorporates the perspectives of all stakeholders to design research questions and measures that are important to members of the breast cancer community and allows for patient centered research studying a diverse set of topics related to breast cancer.
CONCLUSIONS
In summary, rates of genetic testing among women with breast cancer in our study are higher than previously reported and appear appropriately correlated with the likelihood of harboring a genetic mutation, as outlined by national guidelines during the study period. This is encouraging in the modern era, when we are working towards identifying and diagnosing more women with genetic susceptibility to breast cancer, as evidenced by more recent broadening of guidelines. However, racial disparities in genetic testing persist, highlighting the need to improve awareness of and access to genetic testing in minority populations. Surgical treatment patterns, and in particular rates of CPM, are also associated with genetic testing, although given the limitations of our study we cannot infer causality. Rather, we encourage future evaluation in qualitative studies of more demographically diverse populations.
SYNOPSIS.
Genetic testing for hereditary breast cancer has implications for breast cancer decision-making. In a national cohort of highly-educated and well-informed women with breast cancer, rates of genetic testing were higher among women at increased likelihood of carrying a genetic mutation based on family history and age at diagnosis, but there remained a large fraction (33%) of women at high-likelihood of mutation carriage who were not tested, particularly among non-White cohorts. Rates of contralateral prophylactic mastectomy (CPM) were associated with mutation carriage and genetic testing, but highly educated women appeared to consider factors other than cancer mortality in selecting CPM.
ACKNOWLEDGEMENTS
Dr. Verdial and Dr. Bartek were supported by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under Award Number T32DK070555. The content is solely the responsibility of the authors and does not represent the views of the National Institutes of Health.
Data for this project were collected and provided for our use by the Dr. Susan Love Foundation.
DISCLOSURES AND FUNDING SOURCES:
All authors have nothing to disclose.
ABBREVIATIONS
- CPM
Contralateral prophylactic mastectomy
- HOW
Health of Women Study
- NCCN
National Comprehensive Cancer Network
Footnotes
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the Dr. Susan Love Research Foundation. Restrictions apply to the availability of these data, which were used under license for this study. Data are available from the authors with the permission of the Dr. Susan Love Research Foundation.
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