Abstract
Objective:
As germline genetic referral becomes increasingly routine as part of the care of newly diagnosed breast cancer patients, it is important to understand the psychosocial impact of genetic counseling at the time of diagnosis. We examined the psychosocial and quality of life impact of providing proactive rapid genetic counseling and testing in the immediate aftermath of a breast cancer diagnosis.
Methods:
We randomized 330 patients in a 2:1 ratio to proactive rapid genetic counseling (RGCT; N=222) vs. usual care (UC; N=108). Participants completed a baseline telephone survey before randomization and definitive surgery and a follow-up survey at 1-month post-randomization. We evaluated the impact of RGCT vs. UC on breast cancer genetic knowledge, distress, quality of life (QOL), and decisional conflict. Given that 43% of UC participants and 86% of RGCT participants completed genetic counseling prior to the 1-month assessment, we also evaluated the impact of genetic counseling participation over and above group assignment.
Results:
The RGCT intervention led to increased breast cancer genetic knowledge relative to UC but did not differentially impact other study outcomes. Across groups patients who participated in genetic counseling had significantly increased knowledge and improved QOL compared to those who did not participate in genetic counseling.
Conclusions:
While prior research has documented the impact of genetic counseling and testing on surgical decisions, these results confirm that participation in genetic counseling at the time of diagnosis can yield improvements in knowledge and QOL in the short-term.
Keywords: BRCA1, BRCA2, Breast Cancer, Genetic Counseling, Genetic Testing, Psycho-Oncology Quality of Life
Since initial studies documented that access to germline genetic testing at the time of a breast cancer diagnosis can impact patient surgical decisions,1,2 genetic testing has become well-established for newly diagnosed breast cancer patients at high-risk for carrying a pathogenic variant (PV) in a breast cancer susceptibility gene. Studies in population-based and national commercially-insured samples have documented increased use of genetic testing at the time of diagnosis and that receiving a positive BRCA1/2 genetic test result is associated with increased use of bilateral mastectomy.3–5 In addition to informing surgical decisions, germline genetic testing can inform systemic treatment for metastatic breast cancer and for high-risk HER-2 negative early stage breast cancer; along with breast and ovarian cancer prevention and screening decisions in patients and their relatives.6,7
Recently expanded guidelines from the National Comprehensive Cancer Network (NCCN) recommend genetic testing for all breast cancer patients who are ≤ age 45; patients ≤ 50 with a close relative with breast, ovarian, pancreatic or prostate cancer; or any age with triple negative breast cancer, Ashkenazi Jewish ethnicity, high-risk family history or a range of additional risk factors.8 Given the importance of BRCA1/2 PV status for guiding surgical treatment and ongoing research regarding its role in systemic treatment, guidelines may expand further.
Expanding eligibility and increased demand for genetic testing have spurred development of new approaches for rapidly delivering genetic counseling and testing such as telegenetics, physician-delivered, and technology-based approaches.9–11 However, there is little research on the psychosocial impact of rapid genetic counseling and testing (RGCT) on newly diagnosed breast cancer patients, who may be experiencing high distress due to their diagnosis.12–14 To our knowledge, the only large-scale trial to examine this was a Dutch study of 265 newly diagnosed breast cancer patients. Patients receiving RGCT did not differ from usual care (UC) on distress or quality of life in the 6–12 months post-diagnosis.15,16 In an observational study, genetic counseling was associated with increased hereditary cancer knowledge, decreased distress and decisional conflict.17
To further investigate this issue, we developed a RGCT approach which included proactive identification and contact of newly diagnosed breast cancer patients immediately following a positive biopsy and rapid delivery of telephone or in-person genetic counseling and testing. We previously documented that patients randomized to RGCT were more likely to complete genetic counseling prior to surgery.18 However, RGCT and UC did not differ on use of pre-surgical genetic testing – which was primarily predicted by surgeons’ recommendation.19 In this paper, we report the impact of RGCT on distress, QOL, breast cancer genetic knowledge, and decisional conflict in the month following randomization. However, because 43% of the UC group obtained genetic counseling within that month, we also evaluate the impact of genetic counseling participation across both groups. We focused on the short-term because this is a highly stressful period when breast cancer patients face consequential treatment decisions.13,14 We hypothesized that participation in genetic counseling following a breast cancer diagnosis would yield improved breast cancer genetic knowledge and quality of life along with reduced decisional conflict and cancer-specific distress.
Materials and Methods
Participants
As outlined in prior reports, participants were newly diagnosed breast cancer patients enrolled in a parallel group, two-armed randomized trial comparing RGCT to UC.18 From 2006–2012, we enrolled women from breast surgery clinics at Georgetown University Medical Center (Washington, DC), The Icahn School of Medicine at Mount Sinai (New York, NY), Hackensack University Medical Center (Hackensack, NJ), and an affiliated private practice in Washington DC. Eligible women were aged 18–75, diagnosed with AJCC stage 0 to IIIa breast cancer within the previous 6-weeks, had not yet undergone definitive breast cancer surgery, and were at increased risk for carrying a BRCA PV based on their personal (diagnosed at <50 years of age) or family cancer history (a first- or second-degree relative diagnosed with breast cancer at <50, or ovarian cancer at any age, or male breast cancer at any age). Women were ineligible if they had a prior history of cancer; bilateral, inflammatory, or metastatic breast cancer; prior BRCA1/2 counseling or testing; or if they lacked the cognitive capacity for informed consent or could not communicate in English.
Randomization
Participants were randomized to RGCT or UC in a 2:1 ratio using a computer-generated random number stratified by study site.
Procedure
This study was registered with ClinicalTrials.Gov (NCT00262899) and approved by the institutional review boards at Georgetown University (2004–212) and Mount Sinai School of Medicine (GCO #20–0256). Research assistants (RA) reviewed clinic records to identify potentially eligible patients. At an initial phone call, the RA confirmed eligibility, obtained verbal consent and completed the baseline survey. If the baseline survey was not completed within 6-weeks of diagnosis, the participant was considered a study decliner. Participants were randomized following the baseline survey. The interventions are explained in detail in a prior report.18 Briefly, RGCT participants were contacted within 72 hours of randomization to schedule in-person or telephone genetic counseling. Of the RGCT participants who completed genetic counseling, 51% opted for in-person counseling and 49% opted for telephone. UC participants were not proactively contacted but could contact the genetic counseling program for an in-person appointment. All UC participants who opted for genetic counseling were required to have standard in-person genetic counseling. All genetic counseling was provided free of charge. Although we conducted follow-up surveys 1-, 6-, and 12-months post-randomization, here we focus on the 1-month survey to evaluate the short-term impact of genetic counseling.
Measures
Sociodemographics.
We assessed: age, education, employment, marital status, race/ethnicity.
Family/Personal Cancer History.
We used self-reported personal and family cancer history to calculate objective PV risk with the BRCAPRO model.20
Clinical Variables.
We abstracted cancer stage, receptor status, subsequent adjuvant chemotherapy and eligibility for breast conservation from medical and survey records. We were unable to obtain complete data for stage (n=59 missing) and receptor status (n=48 missing). For these variables we included a missing category in our models.
Knowledge.
At baseline and follow-up, we measured knowledge of breast cancer and BRCA1/2 risk with 10 true/false items developed for this study (α= 0.68). This unvalidated measure was developed using face-valid items based on genetic counseling content guidelines and from knowledge items used in our prior studies.1,21,22 This measure was not included for the first 23 participants.
Cancer-Specific Distress.
We measured cancer-specific distress with the 15-item Impact of Events Scale (α=.86 to .87).23
Quality of Life.
We measured health-related quality of life (QOL) with the total score on the 27-item Functional Assessment of Cancer Therapy-General (FACT-G; α=0.86).24
Decisional Conflict.
We assessed decisional conflict regarding breast cancer surgery using a 10-item subscale of the 16-item decisional-conflict scale (DCS; α=0.81).25,26
Statistical Analyses
Initial analyses focused on the randomized controlled comparisons of RGCT to UC. In bivariate analyses, we compared RGCT to UC on sociodemographic, clinical and psychosocial measures. Next, we compared RGCT to UC on change from baseline to 1-month using linear regression controlling for baseline scores on the outcome of interest. Because of the unexpectedly high genetic counseling uptake in UC, we conducted secondary analyses in which we evaluated the impact of genetic counseling across both arms. In bivariate analyses (χ2 and Pearson r) we identified baseline variables associated with each study outcome. We then conducted separate multiple linear regressions in which we entered the baseline confounders (model 1), group assignment (model 2), and a dummy coded variable reflecting genetic counseling and testing status at 1-month: no genetic counseling vs. genetic counseling vs. genetic counseling + receipt of test result (model 3). All analyses were conducted using SAS, v9.4 (Cary, NC).
Results
As displayed in Figure 1 and previously reported,18 of 717 potentially eligible women, 330 (46.0%) completed a baseline interview and were randomized in a 2:1 ratio to RGCT (N=222) vs. UC (N=108). The one-month follow-up was completed by 296 (89.7%; (RGCT = 195, UC = 101) randomized participants. The groups did not differ on attrition (RGCT: n=27 (12.2%); UC: n=7 (6.5%); (Γ2 (n=330, df=1)=2.54, p=0.11).
Figure 1.
Study Flow
Baseline Sample Characteristics
As displayed in Table 1, 96 (32.4%) participants identified as racial/ethnic minorities (20.6% Black; 7.8% Hispanic; 3.4% Asian; 0.6% mixed-race). The mean age was 46. About half the sample had stage 0/I breast cancer, about 30% had stage II/III, and about 20% were categorized as missing. The mean a priori likelihood of carrying a BRCA1/2 PV was 13.5%. The groups were comparable on all background sociodemographic and clinical variables.18,19,27 However, despite random assignment, at baseline, the RGCT group reported lower decisional conflict (t(291)=−2.63, p=0.009) and better QOL (t(293)=2.16, p=0.03) compared to UC.
Table 1.
Baseline Sociodemographic and Clinical Variables
| VARIABLES | OVERALL, N (%) | UC, N (%) | RGCT, N (%) | p-Value |
|---|---|---|---|---|
| Race | ||||
| Racial/Ethnic Minority | 96 (32.4) | 39 (38.6) | 57 (29.2) | 0.10 |
| Non–Hispanic White | 200 (67.6) | 62 (61.4) | 138 (70.8) | |
| Marital Status | ||||
| Unmarried/Widow | 105 (35.5) | 41 (40.6) | 64 (32.8) | 0.19 |
| Married/Partner | 191 (67.6) | 60 (59.4) | 131 (67.2) | |
| Educational Status | ||||
| Less than College Graduate | 69 (23.3) | 29 (28.7) | 40 (20.5) | 0.11 |
| College Graduate | 227 (76.7) | 72 (71.3) | 155 (79.5) | |
| Employment Status | ||||
| Employed < Full Time | 81 (27.4) | 23 (22.8) | 58 (29.7) | 0.20 |
| Employed Full Time | 215 (72.6) | 78 (77.2) | 137 (70.3) | |
| Prior Breast Biopsy | ||||
| No | 212 (73.1) | 70 (70.7) | 142 (74.4) | 0.51 |
| Yes | 78 (26.9) | 29 (29.3) | 49 (25.7) | |
| Chemotherapy | ||||
| No | 135 (46.2) | 40 (40.0) | 95 (49.5) | 0.12 |
| Yes | 157 (53.8) | 60 (60.0) | 97 (50.5) | |
| Candidate for Breast Conservation | ||||
| No | 83 (28.2) | 32 (32.0) | 51 (26.3) | 0.29 |
| Yes | 203 (69.1) | 67 (67.0) | 136 (70.1) | |
| Not Sure | 8 (2.7) | 1 (1.0) | 7 (3.6) | |
| STAGE | ||||
| 0/1 | 144 (48.7) | 43 (42.6) | 101 (51.8) | 0.28 |
| 2/3 | 93 (31.4) | 37 (36.6) | 56 (28.7) | |
| Missing | 59 (19.9) | 21 (20.8) | 38 (19.5) | |
| ER/ PR Status | ||||
| Negative | 48 (16.2) | 13 (12.9) | 35 (18.0) | 0.32 |
| Positive | 200 (67.6) | 68 (67.3) | 132 (67.7) | |
| 48 (16.2) | 20 (19.8) | 28 (14.4) | ||
| OVERALL, Mean (SD) | UC, Mean (SD) | RGCT, Mean (SD) | p-value | |
| Age | 46.0 (8.4) | 46.9 (8.9) | 45.6 (8.0) | 0.23 |
| BRCA mutation risk (%) | 13.5 (21.3) | 13.3 (20.0) | 13.6 (22.1) | 0.90 |
| Knowledge (% correct) | 55.1 (19.5) | 52.3 (19.6) | 56.6 (19.3) | 0.09 |
| Decision Conflict | 18.2 (23.4) | 23.1 (27.6) | 15.6 (20.5) | 0.01 |
| Quality of Life | 85.4 (11.8) | 83.3 (13.3) | 86.5 (10.9) | 0.03 |
| Cancer Distress | 33.2 (16.9) | 32.6 (17.3) | 33.6 (16.7) | 0.63 |
Randomized Controlled Trial: Impact of RGCT vs. UC on Psychosocial and QOL Outcomes
Knowledge.
RGCT (Baseline = 55.5 (19.4), 1-Month = 71.0 (15.9); t(178)=10.9, p<.0001) and UC (Baseline = 52.6 (19.5), 1-Month = 60.8 (21.4); t(90)= 4.2, p<.0001) participants had increased knowledge at 1-month. A linear regression controlling for baseline knowledge indicated that RGCT led to significantly a greater increase in knowledge compared to UC (β=0.21, p<.0001).
QOL.
Scores on the FACT-G declined in the RGCT (Baseline = 86.4 (10.9), 1-Month = 83.2 (14.5); t(191)=−3.5, p=.0006) but not the UC arm (Baseline = 83.4 (13.4), 1-Month = 82.2 (16.3); t(98)=−0.9, p=.37). However, a regression controlling for baseline FACT-G scores indicated that the groups did not differ in QOL at 1-month (β=−0.04, p=.46).
Decisional Conflict.
Decisional conflict increased in the RGCT arm (Baseline = 15.6 (20.5), 1-Month = 24.9 (3.4); t(191)=−6.2, p<.0001) but not the UC arm (Baseline = 21.9 (27.2), 1-Month = 24.8 (2.8); t(97)=−1.0, p=.30). However, after controlling for baseline decisional conflict, the groups did not differ at 1-month (β=0.01, p=.89).
Cancer-Specific Distress.
Both groups reported decreased distress (RGCT: Baseline = 33.6 (16.7), 1-Month = 26.7 (16.0); t(193)=6.4, p<.0001) and UC (Baseline = 32.5 (17.2), 1-Month = 28.2 (17.2); t(99)=3.0, p=.003). After controlling for baseline cancer-specific distress, the groups did not differ at 1-month (β=−0.06, p=.18).
Secondary Analyses: Impact of Genetic Counseling on Psychosocial and QOL Outcomes
Given the unexpectedly high rate of genetic counseling in the UC group (43% had received genetic counseling and 32% received genetic test results prior to the one-month follow-up), we conducted secondary analyses to evaluate the impact of genetic counseling participation by comparing participants who had received genetic counseling and testing to those who had not on each of our outcomes.
Table 2 displays baseline bivariate predictors of 1-month psychosocial outcomes. In subsequent modeling, we adjusted for variables with significant bivariate associations with the outcome of interest.
Table 2.
Baseline Predictors of Study Outcomes
| VARIABLES | Decision Conflict, M (SD) | QOL, M (SD) | Cancer Distress, M (SD) | Knowledge, M (SD) |
|---|---|---|---|---|
| Race | ||||
| Racial/Ethnic Minority | 24.5 (3.7) | 83.4 (16.6) | 25.4 (16.9) | 57.9 (17.5) |
| NHW | 25.0 (3.0) | 82.6 (14.3) | 28.1 (16.1) | 72.1 (17.2) *** |
| Marital Status | ||||
| Married/Partner | 24.9 (2.6) | 84.5 (14.2) * | 27.4 (15.6) | 69.5 (18.9) * |
| Not Married | 24.7 (4.0) | 79.9 (16.2) | 26.9 (17.7) | 64.2 (17.5) |
| Employment | ||||
| Employed Full Time | 24.8 (3.3) | 83.0 (14.6) | 27.8 (16.6) | 67.7 (18.1) |
| Employed < Full Time | 25.0 (3.0) | 82.6 (16.5) | 25.5 (15.8) | 67.0 (19.9) |
| Education | ||||
| College Grad | 24.9 (3.3) | 83.7 (13.9) + | 27.4 (16.1) | 71.2 (16.2) *** |
| < College Grad | 24.5 (3.0) | 80.0 (18.2) | 26.8 (17.3) | 55.3 (20.8) |
| Prior Breast Biopsy | ||||
| No | 24.9 (3.1) | 82.3 (15.0) | 27.6 (16.3) | 68.2 (17.2) |
| Yes | 24.7 (3.5) | 84.3 (15.4) | 26.4 (16.4) | 65.3 (21.9) |
| Receive Chemotherapy | ||||
| No | 25.1 (3.3) | 87.2 (13.0)*** | 24.3 (16.1) | 69.0 (17.5) |
| Yes | 24.6 (3.1) | 79.2 (15.9) | 29.8 (16.3)** | 66.2 (19.4) |
| Stage | ||||
| 0–1 | 25.2 (3.2) | 84.2 (14.5) | 25.0 (16.1) | 69.1 (18.0) |
| 2/3 | 24.6 (3.4) | 80.5 (14.6) | 30.0 (16.6) | 68.2 (17.2) |
| Missing | 24.5 (2.9) | 83.4 (16.8) | 28.1 (16.2) | 62.9 (21.2) |
| Br Conserving Surgery Candidate | ||||
| No | 24.7 (3.2) | 77.0 (15.8)*** | 30.5 (16.3)* | 68.3 (19.0) |
| Yes | 24.9 (3.2) | 85.2 (14.2) | 25.9 (16.3) | 67.3 (18.4) |
| ER/PR Status | ||||
| Negative | 25.3 (3.7) | 73.9 (17.1)*** | 30.7 (15.5) | 63.7 (18.9) |
| Positive | 24.8 (3.2) | 84.8 (13.3) | 25.9 (16.1) | 68.6 (17.9) |
| Missing | 24.4 (2.4) | 83.6 (17.1) | 29.0 (17.9) | 66.5 (20.5) |
| Age (Pearson R) | −0.10 | 0.23** | −0.15** | −0.20** |
| Objective Risk (Pearson R) | −0.00 | −0.11+ | 0.02 | 0.06 |
| Baseline Decision Conflict | −0.08 | −0.06 | 0.07 | −0.05 |
| Baseline Quality of Life | 0.00 | 0.58*** | −0.41*** | −0.02 |
| Baseline Cancer Distress | −0.04 | −0.43*** | 0.62*** | 0.02 |
| Baseline Knowledge | 0.01 | 0.04 | −0.05 | 0.54*** |
Knowledge.
Group assignment was significantly independently associated with knowledge after accounting for confounders (Table 3; β=0.18, p<.001). Our composite genetic counseling/testing variable was significantly associated with knowledge (ΔR2=.042, F(2,261)=10.2, p<.0001). When counseling/testing is included in the model, group is no longer independent predictor of knowledge (β=0.08, p=.13). Additional predictors of knowledge in the full model were education (β=0.18, p<.001) and non-Hispanic white race/ethnicity (β=0.16, p=.001)
Table 3a.
Association of Genetic Counseling Participation with Knowledge
| Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|
| Variables | Beta (SE) | β | Beta (SE) | β | Beta (SE) | β |
| Baseline Knowledge | 0.40 (0.05) | 0.42*** | 0.39 (0.05) | 0.41*** | 0.36 (0.05) | 0.38*** |
| Race | 7.80 (2.02) | 0.20*** | 7.46 (1.97) | 0.19** | 6.36 (1.93) | 0.16** |
| Marital Status | 1.47 (1.89) | 0.04 | 1.16 (1.84) | 0.03 | 1.14 (1.78) | 0.03 |
| Education | 8.70 (2.29) | 0.20*** | 8.20 (2.18) | 0.19** | 7.59 (2.11) | 0.17** |
| Age | −0.20 (0.11) | −0.09+ | −0.19 (0.10) | −0.08+ | −0.15 (0.10) | −0.07 |
| Group | 7.10 (1.85) | 0.18** | 3.11 (2.05) | 0.08 | ||
| Counsel + Test vs. No Counsel | 10.24 (2.36) | 0.27*** | ||||
| R2 | 0.39 | 0.42 | 0.465 | |||
| F for change in R2 | F (5, 264) = 33.9*** | F (1, 263) = 14.7** | F (2, 261) = 10.2*** | |||
QOL.
After controlling for baseline confounders and group assignment, genetic counseling participation was independently associated with improved QOL at 1-month (Table 3; ΔR2=.017, F(2,274)=4.3, p=.01). Receipt of chemotherapy (β=−0.15, p=.002) and baseline cancer-specific distress (β=−0.13, p=0.02) were associated with poorer QOL while being a candidate for breast conservation (β=0.09, p=0.05) and positive ER/PR status (β=0.16, p=.007) were associated with better QOL.
Table 3b.
Association of Genetic Counseling Participation with Quality of Life
| Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|
| Variables | Beta (SE) | β | Beta (SE) | β | Beta (SE) | β |
| Baseline QOL | 0.54 (0.07) | 0.43*** | 0.55 (0.07) | 0.43*** | 0.54 (0.07) | 0.42*** |
| Marital Status | 2.51 (1.46) | 0.08+ | 2.55 (1.46) | 0.08+ | 2.25 (1.45) | 0.07 |
| Age | 0.13 (0.09) | 0.07 | 0.12 (0.09) | 0.07 | 0.12 (0.09) | 0.07 |
| Chemotherapy | −4.24 (1.46) | −0.15** | −4.55 (1.48) | −0.15** | −4.50 (1.46) | −0.15** |
| Breast Conserving Surgery Candidate | 3.60 (1.57) | 0.11* | 3.65 (1.57) | 0.11* | 3.14 (1.60) | 0.09 |
| Cancer Distress | −0.12 (0.05) | −0.13* | −0.11 (0.05) | −0.13* | −0.12 (0.05) | −0.13* |
| Missing vs. Neg | 4.10 (2.49) | 0.10 | 3.93 (2.51) | 0.09 | 4.31 (2.48) | 0.10 |
| Group | −0.93 (1.51) | −0.03 | −2.86 (1.67) | −0.09 | ||
| Counsel + Test vs. No Counsel | 1.64 (1.88) | 0.05 | ||||
| R2 | 0.432 | 0.433 | 0.450 | |||
| F for change in R2 | F (8, 277) = 26.3*** | F (1, 276) = 0.4 | F (2, 274) = 4.32* | |||
Decisional Conflict and Cancer-Specific Distress.
Neither decisional conflict nor cancer-specific distress was independently predicted by group (Decisional Conflict: β=0.008, p=0.89; Cancer Distress: β=−0.04, p=0.36) or genetic counseling/testing participation (Decisional Conflict: ΔR2=.004, F(2,285)=0.58, p=0.56; Cancer-Specific Distress: ΔR2=.0002, F(2,280)=0.05, p=0.95).
Discussion
Despite evidence supporting the impact of germline testing on surgical decision making,28 less is known about the psychosocial implications of genetic counseling and testing among newly diagnosed breast cancer patients. Given expanding genetic referral guidelines,8 understanding the psychosocial impact of rapid genetic counseling is critical to inform evolving guidelines. We found that patients randomized to receive proactive rapid genetic counseling exhibited increased knowledge and improved with no evidence of decrements in psychosocial outcomes.
These results align with our reports showing that RGCT led to increased pre-surgical genetic counseling, but did not impact testing or surgical decisions.18 This was due to the substantial proportion of UC participants opting for genetic counseling through usual clinical care. Thus, we focused on whether genetic counseling and testing were associated with patient-reported outcomes independent of group assignment. Consistent with limited prior research,16,29 we found that genetic counseling participation -- alone or with testing -- was not associated with adverse outcomes. To the contrary, genetic counseling was associated with improved breast cancer genetic knowledge and QOL.
Across groups, participation in genetic counseling was associated with higher breast cancer genetic knowledge. Given that knowledge is a key component of informed decision-making,30 this is consistent with the premise of genetic counseling as a facilitator of informed decision-making for high-risk breast cancer patients. However, given that knowledge is but one component of informed choice and our use of an unvalidated measure of knowledge, future studies should more rigorously evaluate informed choice as an outcome following pre-surgical genetic counseling. Further, as demand for these services increases, it will be important to explore alternative approaches for delivering genetic education to ensure that all patients have access to the information needed to make informed decisions. For example, evidence-based educational materials delivered via the Web could streamline delivery and make the information more widely and readily available.31,32
Genetic counseling was also associated with better QOL after controlling for baseline QOL, adjuvant chemotherapy, and hormone receptor status. While this finding suggests that genetic counseling at the time of diagnosis may benefit patients, it is also possible that sicker patients, those with declining QOL, or those without the option for breast conservation (and therefore could delay genetic counseling and testing) were less likely to participate in genetic counseling. Indeed, patients who were candidates for breast conserving surgery reported better QOL at 1-month, although this association was attenuated when genetic counseling participation was added to the model.
Clinical Implications.
These results are broadly consistent with, and expand upon, prior research demonstrating that genetic counseling for newly diagnosed breast cancer patients who meet genetic referral criteria, does not cause adverse psychosocial outcomes.15,29 Our data add to the literature by focusing on the highly stressful month following diagnosis and documenting that genetic counseling may have psychosocial benefits. Given recent reports of low rates of genetic testing in breast cancer patients,5,33 our results should reassure patients and clinicians of the potential benefits of genetic referral at the time of diagnosis.
However, the clinical implications of these results must be considered in light of evolving genetic counseling and testing practices. Since our study predates the emergence of multigene panel testing, the counseling provided in the study focused solely on the implications of BRCA1/BRCA2 testing. Genetic counseling for multigene testing must address the implications of PVs in dozens of genes with varying levels of penetrance and unclear surgical and treatment implications. Multigene genetic counseling must also address the increased likelihood of detecting a variant of uncertain clinical significance. While the increased complexity and uncertainty associated with multigene testing could adversely impact patient responses to genetic counseling, initial studies on outcomes of multigene counseling and testing have reported comparable outcomes to traditional single gene counseling and testing.34–36
The expansion of genetic referral guidelines and concomitant increased demand, have fostered alternative approaches to pre-test genetic counseling.37 While our study incorporated telephone-based genetic counseling, the impact of more recent technology-based approaches (e.g., chatbots), physician-delivered counseling, and post-test only counseling remain to be evaluated.9–11 While our results do not directly address these novel counseling strategies, the documented benefits of counseling identified in our study can serve as a point of comparison for considering the risks and benefits of more streamlined counseling approaches.
Study Limitations.
As discussed above, this study was completed prior to the emergence of multigene panel testing and alternative genetic counseling approaches. The high rate (43%) of genetic counseling in the UC arm coupled with the 46% study participation rate also limits conclusions that can be drawn from the study. These factors could reflect a participation bias. Along with the fact that genetic counseling was provided free of charge, such a bias could yield more positive psychosocial outcomes than seen outside of the study. However, it is important to note that study participants and decliners were comparable on all background variables with the exception of education.18 Further, our participation rate was only slightly lower than the median participation rate across cancer control trials in a recent meta-analysis.38 As a secondary analysis, caution must be applied in drawing causal inferences from our results. Although we did not correct for multiple comparisons, applying a Bonferroni correction to our post-hoc analyses does not substantively change the results. Another limitation is that we did not employ a standardized and validated measure of knowledge. While such a measure would have been preferable, our face-valid measure was sensitive to both our randomization and to genetic counseling participation - providing some evidence of criterion-validity. Finally, we are missing data on several key clinical variables - most notably staging and receptor status.
Conclusions.
These results reinforce the potential psychosocial benefit of proactively providing genetic counseling at the time of breast cancer diagnosis to inform treatment decisions. While prior research has documented the impact of genetic counseling and testing on surgical decision-making, this study demonstrates that genetic counseling may also provide added value in fostering improved psychosocial outcomes. As genetic testing becomes increasingly integrated into the care of breast cancer patients, research must explore more streamlined and proactive approaches to provide patients with the information they need to understand the personal and familial implications of germline genetic testing.
Acknowledgements:
This study was supported by NCI Grants R01 CA74861 and P30 CA051008. The authors are grateful to all the women who participated in this study. The authors would like to acknowledge contributions of Dr. Colette Magnant, Dr. Elizabeth Feldman, Ms. Tamara Drazin and Ms. Aliza Zidell in providing access to their patients. We would also like to acknowledge the contributions of Dr. Kara-Grace Leventhal for conducting study telephone surveys.
Data Availability Statement:
The data that support the findings of this study are available upon reasonable request from the corresponding author [MDS]. The data are not publicly available due to the inclusion of information that could compromise research participant privacy/consent.
References
- 1.Schwartz MD, Lerman C, Brogan B, et al. Impact of BRCA1/BRCA2 counseling and testing on newly diagnosed breast cancer patients. J Clin Oncol. 2004;22(10):1823–1829. doi: 10.1200/JCO.2004.04.086 [DOI] [PubMed] [Google Scholar]
- 2.Weitzel JN, McCaffrey SM, Nedelcu R, MacDonald DJ, Blazer KR, Cullinane CA. Effect of genetic cancer risk assessment on surgical decisions at breast cancer diagnosis. Arch Surg. 2003;138(12):1323–1328; discussion 1329. doi: 10.1001/archsurg.138.12.1323 [DOI] [PubMed] [Google Scholar]
- 3.Armstrong J, Lynch K, Virgo KS, et al. Utilization, Timing, and Outcomes of BRCA Genetic Testing Among Women With Newly Diagnosed Breast Cancer From a National Commercially Insured Population: The ABOARD Study. JCO Oncol Pract. 2021;17(2):e226–e235. doi: 10.1200/OP.20.00571 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Armstrong J, Toscano M, Kotchko N, et al. Utilization and Outcomes of BRCA Genetic Testing and Counseling in a National Commercially Insured Population: The ABOUT Study. JAMA Oncol. 2015;1(9):1251–1260. doi: 10.1001/jamaoncol.2015.3048 [DOI] [PubMed] [Google Scholar]
- 5.Kurian AW, Ward KC, Abrahamse P, et al. Time Trends in Receipt of Germline Genetic Testing and Results for Women Diagnosed With Breast Cancer or Ovarian Cancer, 2012–2019. J Clin Oncol. Published online February 9, 2021:JCO2002785. doi: 10.1200/JCO.20.02785 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Robson M, Im SA, Senkus E, et al. Olaparib for Metastatic Breast Cancer in Patients with a Germline BRCA Mutation. N Engl J Med. 2017;377(6):523–533. doi: 10.1056/NEJMoa1706450 [DOI] [PubMed] [Google Scholar]
- 7.Tutt ANJ, Garber JE, Kaufman B, et al. Adjuvant Olaparib for Patients with BRCA1- or BRCA2-Mutated Breast Cancer. N Engl J Med. Published online June 3, 2021. doi: 10.1056/NEJMoa2105215 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.National Comprehensive Cancer Network. Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic. NCCN. Accessed October 29, 2021. https://www.nccn.org/guidelines/guidelines-detail [Google Scholar]
- 9.Kurian AW, Li Y, Hamilton AS, et al. Gaps in Incorporating Germline Genetic Testing Into Treatment Decision-Making for Early-Stage Breast Cancer. J Clin Oncol. 2017;35(20):2232–2239. doi: 10.1200/JCO.2016.71.6480 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Rayes N, Bowen DJ, Coffin T, et al. MAGENTA (Making Genetic testing accessible): a prospective randomized controlled trial comparing online genetic education and telephone genetic counseling for hereditary cancer genetic testing. BMC Cancer. 2019;19(1):648. doi: 10.1186/s12885-019-5868-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Schmidlen T, Schwartz M, DiLoreto K, Kirchner HL, Sturm AC. Patient assessment of chatbots for the scalable delivery of genetic counseling. J Genet Couns. 2019;28(6):1166–1177. doi: 10.1002/jgc4.1169 [DOI] [PubMed] [Google Scholar]
- 12.Wevers MR, Schou-Bredal I, Verhoef S, et al. Psychological distress in newly diagnosed breast cancer patients: an observational study comparing those at high risk of hereditary cancer with those of unknown risk. Journal of Psychosocial Oncology Research and Practice. 2020;2(1). https://journals.lww.com/jporp/Fulltext/2020/01000/Psychological_distress_in_newly_diagnosed_breast.1.aspx [Google Scholar]
- 13.Ludwigson A, Huynh V, Bronsert M, et al. A screening tool identifies high distress in newly diagnosed breast cancer patients. Surgery. 2020;168(5):935–941. doi: 10.1016/j.surg.2020.04.051 [DOI] [PubMed] [Google Scholar]
- 14.Wang WT, Tu PC, Liu TJ, Yeh DC, Hsu WY. Mental adjustment at different phases in breast cancer trajectory: re-examination of factor structure of the Mini-MAC and its correlation with distress. Psychooncology. 2013;22(4):768–774. doi: 10.1002/pon.3065 [DOI] [PubMed] [Google Scholar]
- 15.Wevers MR, Aaronson NK, Bleiker EMA, et al. Rapid genetic counseling and testing in newly diagnosed breast cancer: Patients’ and health professionals’ attitudes, experiences, and evaluation of effects on treatment decision making. Journal of Surgical Oncology. 2017;116(8):1029–1039. doi: 10.1002/jso.24763 [DOI] [PubMed] [Google Scholar]
- 16.Wevers MR, Ausems MGEM, Verhoef S, et al. Does rapid genetic counseling and testing in newly diagnosed breast cancer patients cause additional psychosocial distress? results from a randomized clinical trial. Genet Med. 2016;18(2):137–144. doi: 10.1038/gim.2015.50 [DOI] [PubMed] [Google Scholar]
- 17.Christie J, Quinn GP, Malo T, et al. Cognitive and Psychological Impact of BRCA Genetic Counseling in Before and After Definitive Surgery Breast Cancer Patients. Ann Surg Oncol. 2012;19(13):4003–4011. doi: 10.1245/s10434-012-2460-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Schwartz MD, Peshkin BN, Isaacs C, et al. Randomized trial of proactive rapid genetic counseling versus usual care for newly diagnosed breast cancer patients. Breast Cancer Res Treat. 2018;170(3):517–524. doi: 10.1007/s10549-018-4773-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Ladd MK, Peshkin BN, Isaacs C, et al. Predictors of genetic testing uptake in newly diagnosed breast cancer patients. J Surg Oncol. Published online April 28, 2020. doi: 10.1002/jso.25956 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Mazzola E, Blackford A, Parmigiani G, Biswas S. Recent Enhancements to the Genetic Risk Prediction Model BRCAPRO. Cancer Inform. 2015;14(Suppl 2):147–157. doi: 10.4137/CIN.S17292 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Berliner JL, Fay AM, Practice Issues Subcommittee of the National Society of Genetic Counselors’ Familial Cancer Risk Counseling Special Interest Group. Risk assessment and genetic counseling for hereditary breast and ovarian cancer: recommendations of the National Society of Genetic Counselors. J Genet Couns. 2007;16(3):241–260. doi: 10.1007/s10897-007-9090-7 [DOI] [PubMed] [Google Scholar]
- 22.Schwartz MD, Benkendorf J, Lerman C, Isaacs C, Ryan-Robertson A, Johnson L. Impact of educational print materials on knowledge, attitudes, and interest in BRCA1/BRCA2: testing among Ashkenazi Jewish women. Cancer. 2001;92(4):932–940. doi: 10.1002/1097-0142(20010815)92:4<932::aid-cncr1403>3.0.co;2-q [DOI] [PubMed] [Google Scholar]
- 23.Horowitz M, Wilner N, Alvarez W. Impact of Event Scale: a measure of subjective stress. Psychosom Med. 1979;41(3):209–218. doi: 10.1097/00006842-197905000-00004 [DOI] [PubMed] [Google Scholar]
- 24.Cella DF, Tulsky DS, Gray G, et al. The Functional Assessment of Cancer Therapy scale: development and validation of the general measure. J Clin Oncol. 1993;11(3):570–579. doi: 10.1200/JCO.1993.11.3.570 [DOI] [PubMed] [Google Scholar]
- 25.O’Connor AM. Validation of a decisional conflict scale. Med Decis Making. 1995;15(1):25–30. doi: 10.1177/0272989X9501500105 [DOI] [PubMed] [Google Scholar]
- 26.King L, O’Neill SC, Spellman E, et al. Intentions for bilateral mastectomy among newly diagnosed breast cancer patients. J Surg Oncol. 2013;107(7):772–776. doi: 10.1002/jso.23307 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Tynan M, Peshkin BN, Isaacs C, et al. Predictors of contralateral prophylactic mastectomy in genetically high risk newly diagnosed breast cancer patients. Breast Cancer Res Treat. 2020;180(1):177–185. doi: 10.1007/s10549-019-05515-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Yadav S, Jinna S, Pereira-Rodrigues O, et al. Impact of preoperative BRCA1/2 testing on surgical decision making in patients with newly diagnosed breast cancer. Breast J. 2018;24(4):541–548. doi: 10.1111/tbj.13007 [DOI] [PubMed] [Google Scholar]
- 29.Schlich-Bakker KJ, Ausems MGEM, Schipper M, Ten Kroode HFJ, Wárlám-Rodenhuis CC, van den Bout J. BRCA1/2 mutation testing in breast cancer patients: a prospective study of the long-term psychological impact of approach during adjuvant radiotherapy. Breast Cancer Res Treat. 2008;109(3):507–514. doi: 10.1007/s10549-007-9680-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Michie S, Dormandy E, Marteau TM. The multi-dimensional measure of informed choice: a validation study. Patient Educ Couns. 2002;48(1):87–91. doi: 10.1016/s0738-3991(02)00089-7 [DOI] [PubMed] [Google Scholar]
- 31.Cragun D, Weidner A, Tezak A, Zuniga B, Wiesner GL, Pal T. A Web-Based Tool to Automate Portions of Pretest Genetic Counseling for Inherited Cancer. J Natl Compr Canc Netw. 2020;18(7):841–847. doi: 10.6004/jnccn.2020.7546 [DOI] [PubMed] [Google Scholar]
- 32.Peshkin BN, Ladd MK, Isaacs C, et al. The Genetic Education for Men (GEM) Trial: Development of Web-Based Education for Untested Men in BRCA1/2-Positive Families. J Cancer Educ. Published online August 11, 2019. doi: 10.1007/s13187-019-01599-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Knerr S, Bowles EJA, Leppig KA, Buist DSM, Gao H, Wernli KJ. Trends in BRCA Test Utilization in an Integrated Health System, 2005–2015. J Natl Cancer Inst. 2019;111(8):795–802. doi: 10.1093/jnci/djz008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Pozzar RA, Hong F, Xiong N, Stopfer JE, Nayak MM, Underhill-Blazey M. Knowledge and psychosocial impact of genetic counseling and multigene panel testing among individuals with ovarian cancer. Fam Cancer. Published online March 10, 2021. doi: 10.1007/s10689-021-00240-6 [DOI] [PubMed] [Google Scholar]
- 35.Culver JO, Ricker CN, Bonner J, et al. Psychosocial outcomes following germline multigene panel testing in an ethnically and economically diverse cohort of patients. Cancer. 2021;127(8):1275–1285. doi: 10.1002/cncr.33357 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Underhill-Blazey M, Blonquist T, Chittenden A, et al. Informing models of cancer genetics care in the era of multigene panel testing with patient-led recommendations. J Genet Couns. 2021;30(1):268–282. doi: 10.1002/jgc4.1317 [DOI] [PubMed] [Google Scholar]
- 37.McCuaig JM, Armel SR, Care M, Volenik A, Kim RH, Metcalfe KA. Next-Generation Service Delivery: A Scoping Review of Patient Outcomes Associated with Alternative Models of Genetic Counseling and Genetic Testing for Hereditary Cancer. Cancers (Basel). 2018;10(11):E435. doi: 10.3390/cancers10110435 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Unger JM, Hershman DL, Till C, et al. “When Offered to Participate”: A Systematic Review and Meta-Analysis of Patient Agreement to Participate in Cancer Clinical Trials. J Natl Cancer Inst. 2021;113(3):244–257. doi: 10.1093/jnci/djaa155 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available upon reasonable request from the corresponding author [MDS]. The data are not publicly available due to the inclusion of information that could compromise research participant privacy/consent.