Reducing Disparities in Receipt of Genetic Counseling for Underserved Women at Risk of Hereditary Breast and Ovarian Cancer

Abstract

Purpose: Genetic counseling (GC) provides critical risk prediction information to women at-risk of carrying a genetic alternation; yet racial/ethnic and socioeconomic disparities persist with regard to GC uptake. This study examined patterns of GC uptake after a referral in a racially diverse population.

Materials and Methods: In an urban academic medical center, medical records were reviewed between January 2016 and December 2017 for women who were referred to a genetic counselor for hereditary breast and ovarian cancer. Study outcomes were making an appointment (yes/no) and keeping an appointment. We assessed sociodemographic factors and clinical factors. Associations between factors and the outcomes were analyzed using chi square, and logistic regression was used for multivariable analysis.

Results: A total of 510 women were referred to GC and most made appointments. More than half were white (55.3%) and employed (53.1%). No significant associations were observed between sociodemographic factors and making an appointment. A total of 425 women made an appointment and 268 kept their appointment. Insurance status (p = 0.003), marital status (p = 0.000), and work status (p = 0.039) were associated with receiving GC. In the logistic model, being married (odds ratio [OR] 2.119 [95% confidence interval, CI 1.341–3.347] p = 0.001) and having insurance (OR 2.203 [95% CI 1.208–4.016] p = 0.021) increased the likelihood of receiving counseling.

Conclusions: Racial disparities in GC uptake were not observed in this sample. Unmarried women may need additional support to obtain GC. Financial assistance or other options need to be discussed during navigation as a way to lessen the disparity between women with insurance and those without.

Introduction

Germline pathogenic variants of the BRCA1/2 genes are associated with hereditary breast and ovarian cancer (HBOC). Mutations of these genes are present in ∼2%–7% of breast cancer patients and 20%–25% of epithelial ovarian cancer patients.^1–5 Owing to autosomal dominant inheritance, mutation carriers have a 50% chance of passing the pathogenic gene to their offspring. The National Comprehensive Cancer Network recommend GC and consideration of testing for women at-risk of hereditary breast cancer (e.g., ≤50 years of age at the time of breast cancer diagnosis, family member with BRCA1/2 mutation) and all women with a personal diagnosis or first-degree relative with ovarian cancer.⁶

Genetic counseling (GC) is a beneficial clinical service for individuals at-risk of developing hereditary disorders and diseases. In the case of HBOC, GC provides patients with invaluable information with regard to genetic testing (GT) that assesses one's risk of developing breast or ovarian cancer.⁷ For breast and ovarian cancer patients GC offers an opportunity to understand individual and familial risks as well as the likelihood of a second cancer diagnosis; the role of preventative medical and surgical therapies; and the availability of treatment options such as Poly (ADP-ribose) polymerase (PARP) inhibitors.^7–9 For mutation carriers identified before the development of a malignancy, risk reducing medical and surgical interventions can be pursued.

Although GC services are indeed integral to the prevention of HBOC and survivorship for those who are diagnosed, GC remains underutilized and disparities with regard to uptake exist.¹⁰ Data show that black women are less likely to seek GC than their white counterparts due to varying reasons (e.g., mistrust, impact on family).¹¹ Furthermore, insured and uninsured women express concerns with paying for GC and GT.^12–14 Underutilization has been attributed to a lack of referral by a provider,^15,16 but even after a referral, some women still refrain from GC uptake.^17,18 Therefore, there remains a need to understand barriers to receiving GC that at-risk women may face even after receiving a referral.

Patient navigation and care coordination have been shown to improve uptake of genetic services.¹⁹ Although processes differ with regard to how patients are navigated through a system (e.g., telephone, use of electronic health record), the overall goal is to ensure patients receive the care recommended by a provider.^18,20

The purpose of this study is to examine (i) patterns of GC uptake in women at-risk of HBOC and (ii) the association between sociodemographic and clinical factors with GC uptake.

Materials and Methods

This study took place at an academic medical center in Richmond, Virginia, that provides care to many of the regions uninsured and underinsured, as it is a safety-net hospital. Furthermore, African Americans comprise ∼30% of the patient population. According to the standard process of care at this medical center, primary care providers and specialists (e.g., gynecologists, oncologists) may refer women to GC if they believe they are at-risk of HBOC. All referral requests are received by a patient coordinator. Providers can employ one of three methods to refer women. If the provider is internal, or practicing within the academic center, they can enter a referral order through the electronic health record. For external providers, they can fax a referral. Any provider, whether internal or external, can call the patient coordinator. The patient coordinator calls the patient to make an appointment and sends the patient an appointment letter, a map of the medical center, and a preappointment paper-based questionnaire. This questionnaire asks patients about their medical/family histories. Patients are also encouraged to identify goals and expectations for the GC appointment. Examples of patient goals include “I would like to learn more about my cancer risks,” “I want to see if I inherited the gene mutation from my [family member],” and “I want more information to guide surgical decisions.”

Women who were referred to GC between January 2016 and December 2017 for reasons pertaining to HBOC (e.g., personal history, family history) were selected for this study. This study only includes internal referral requests. That data set was cross-referenced with GC appointment data to capture the appointment outcome for all women represented in the referral data. Data were abstracted to March 2018 to account for women who were referred at the end of the year but were not scheduled to appear until later.

Data included the following sociodemographic factors: age of women at the time of the referral, race, insurance status, marital status, and employment status. We dichotomized insurance status (insured vs. noninsured); insured women had either private insurance, Medicare or Medicaid. Clinical factors included a referral due to personal history of breast cancer and/or a family history of breast cancer. Chi square testing assessed the relationship between sociodemographic factors and making and keeping an appointment. Logistic regression analyses identified factors that predict GC receipt. All study procedures were approved by the Virginia Commonwealth University Institutional Review Board.

Results

A total of 510 women were referred to GC from January 2016 to December 2017. Most women were white (55.3%) (vs. 39.8% black), unmarried (52.9%), and insured (83.1%) (Table 1). A majority of women were employed (53.1%). Most women had a family history of breast and/or ovarian cancer (69.8%).

Table 1.

Demographics and Appointment Decisions After a Referral

Demographic variables	N (%)	Made an appointment N = 510 N (%)		p-Value	Received counseling N = 268 N (%)		p-Value
		Yes	No		Yes	No
Age (years)				0.220			0.335
≤50	257 (50.4)	209 (81.3)	48 (18.7)		127 (60.8)	82 (39.2)
>50	253 (49.6)	216 (85.4)	37 (14.6)		141 (65.3)	75 (34.7)
Race				0.093			0.181
Black	203 (39.8)	173 (85.2)	30 (14.8)		104 (60.1)	69 (39.9)
White	282 (55.3)	235 (83.3)	47 (16.7)		150 (63.8)	85 (36.2)
Other	25 (4.9)	17 (68.0)	8 (32.0)		14 (82.4)	3 (17.6)
Insurance status				0.347			0.003**
Insurance	424 (83.1)	358 (84.4)	66 (15.6)		236 (65.9)	122 (34.1)
No insurance	79 (15.5)	63 (79.7)	16 (20.3)		29 (46.0)	34 (54.0)
Marital status				0.341			0.000***
Married	240 (47.1)	204 (85.0)	36 (15.0)		148 (72.5)	56 (27.5)
Not married	270 (52.9)	221 (81.9)	49 (18.1)		120 (54.3)	101 (45.7)
Employment status				0.165			0.039*
Employed	271 (53.1)	220 (81.2)	51 (18.8)		149 (67.7)	71 (32.3)
Not employed	239 (46.9)	205 (85.8)	34 (14.2)		119 (58.0)	86 (42.0)
Personal history				0.169			0.276
Yes		78 (79.6)	20 (20.4)		52 (66.7)	26 (33.3)
No		347 (84.2)	65 (15.8)		216 (62.2)	131 (37.8)
Family history				0.207			0.177
Yes		293 (82.3)	63 (17.7)		180 (61.4)	113 (38.6)
No		132 (85.7)	22 (14.3)		88 (66.7)	44 (33.3)

^*p < 0.05; ^**p < 0.01; ^***p < 0.001.

Eighty-three percent of women made an appointment after a referral (Fig. 1). The mean number of days between a referral and an appointment was 42.5 days (standard deviation = 75.9).Of the women who made an appointment, a majority (63.1%) received counseling. Of the 510 total women who were referred to GC, 268 (53%) received counseling.

FIG. 1.

Study schema.

In bivariate analysis, race and age were not associated with making a GC appointment (Table 1). Marital status (p < 0.001), employment status (p = 0.039), and insurance status (p = 0.003) were significantly associated with receipt of counseling.

In the multivariable logistic regression model, married women had 2.05 (95% confidence interval [CI]: 1.350–3.098) higher odds of receiving counseling compared with unmarried women (Table 2). Women who had insurance were also more likely to receive counseling than women without insurance (odds ratio 1.924, 95% CI: 1.205–3.350).

Table 2.

Logistic Regression Model of Receiving Counseling

Demographic variables	Estimate	Odds ratio (95% confidence interval)	p-Value
Marital status
Married	0.716	2.046 (1.350–3.098)	0.001**
Not married	Ref.
Insurance status
Insurance	0.654	1.924 (1.205–3.350)	0.021*
No insurance	Ref.

^*p < 0.05; ^**p < 0.01.

Discussion

We found that more than half of women (53%) referred to GC actually received it. Our findings were similar to those of other studies^21–23; however, this completion rate to referrals is concerning. Factors related to the system of care may contribute to these findings. Our data indicate a 24–48 hour turnaround time between a referral and a phone call from the patient coordinator. Although results are mixed, recent reports support the use of navigators and coordinators to increase GC uptake.¹⁸ There is still a need to improve GC rates in women who do not have insurance.

Unmarried women were found to be less likely to receive GC than married women. Although not a proxy for having children, married women may have more concern with inheritance or passing BRCA1/2 pathogenic variants to children.²⁴ Furthermore, male partners of women at-risk of HBOC have reported distress about the results and the risks for their children.^25–27 Shared decision making may also provide additional motivation for married women. Future studies should examine women's decision-making processes and the roles of support systems when deciding to seek GC.

Insurance status also predicted women's receipt of GC. This finding is similar to those reported by similar studies.^14,15,28 Furthermore, in a recent study of women in our system where we examined their willingness to pay for universal screening for BRCA 1/2, women who had higher interest in universal testing were more likely to pay out of pocket for testing than those who were not.²⁹ This particular finding is of importance given the unique payment structure of this medical center. In our data, uninsured women are in the Virginia Coordinated Care (VCC) program, a mechanism that provides health care services to uninsured individuals.³⁰ This program covers GC. Moreover, special programs are available to provide assistance with payment for GT, but individuals who are uninsured or underinsured may perceive cost as a barrier to GT. Although VCC helps with the cost of the appointment there are other financial barriers to consider, such as transportation costs, childcare costs, and time away from work. Although the VCC program is specific to this health care center, other entities may have similar programs; however, those that do not may serve as an organizational barrier to women who may want to receive GT. Furthermore, women may benefit from additional education on the differences between GC and GT during navigation.

Interestingly we did not see a disparity in GC by race in this study. Previous studies have shown black women to be less likely to receive GC and GT.³¹ It is possible that care coordination attenuates this relationship; however, further investigation and analyses are required to prove this assertion.

Study limitations

Although the study fills a gap in knowledge about potential impediments to receiving GC, several limitations should be noted. We did not have information that would allow us to determine if all women who were eligible for GC actually received a referral. These data may have been useful, as other studies have found disparities in receipt of GC referrals. We also did not have access to GT data; these data would also allow further investigation into disparities. Lastly, the retrospective nature of our data is subject to bias and data were limited to demographic and clinical. We were, therefore, unable to test the roles of other factors (e.g., psychosocial) and receipt of GC.

Conclusions

Navigation, particularly within a system of care, appears successful with regard to getting at-risk women to make an appointment; however, there may be opportunities to tailor navigation by educating and training navigators to provide additional information that would motivate more women to receive counseling.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This project was supported by the National Cancer Institute Center to Reduce Cancer Health Disparities, Award No. P30CA177558-05S3. Services and products in support of the research project were generated by the Virginia Commonwealth University Massey Cancer Center Cancer Informatics Core Shared Resource, supported, in part, with funding from National Institutes of Health-National Cancer Institute Cancer Center Support Grant (P30 CA016059). This project was also supported by NCI (2T32 CA093423; V.B.S., CoPI); Georgetown-Howard Universities Center for Clinical and Translational Science by Federal Funds; the National Center for Advancing Translational Sciences; and the National Institutes of Health, through the Clinical and Translational Science Awards Program (KL2TR001432; A.H.-d.-M., PI).