Healthcare Utilization and Costs after Receiving a Positive BRCA1/2 Result from a Genomic Screening Program

Abstract

Population genomic screening has been demonstrated to detect at-risk individuals who would not be clinically identified otherwise. However, there are concerns about the increased utilization of unnecessary services and the associated increase in costs. The objectives of this study are twofold: (1) determine whether there is a difference in healthcare utilization and costs following disclosure of a pathogenic/likely pathogenic (P/LP) BRCA1/2 variant via a genomic screening program, and (2) measure the post-disclosure uptake of National Comprehensive Cancer Network (NCCN) guideline-recommended risk management. We retrospectively reviewed electronic health record (EHR) and billing data from a female population of BRCA1/2 P/LP variant carriers without a personal history of breast or ovarian cancer enrolled in Geisinger’s MyCode genomic screening program with at least a one-year post-disclosure observation period. We identified 59 women for the study cohort out of 50,726 MyCode participants. We found no statistically significant differences in inpatient and outpatient utilization and average total costs between one-year pre- and one-year post-disclosure periods ($18,821 vs. $19,359, p = 0.76). During the first year post-disclosure, 49.2% of women had a genetic counseling visit, 45.8% had a mammography and 32.2% had an MRI. The uptake of mastectomy and oophorectomy was 3.5% and 11.8%, respectively, and 5% of patients received chemoprevention.

Penetrance of Breast Cancer Susceptibility Genes From the eMERGE III Network

“…Among 147 women with at least 1 P/LP variant in the 7 breast cancer susceptibility genes, 56 (0.38%, 95% CI = 0.30% to 0.46%) unselected individuals had BRCA1/2 P/LP variants. This prevalence of 0.38% is consistent with the 0.2%-0.7% prevalence of BRCA1/2 P/LP variants reported in previous studies ( 9 , 15 , 30 , 31 ). The frequency of BRCA1/2 P/LP variants differs across race and ethnicity: 41.7% in the 108 European-ancestry individuals, 30.4% in the 23 African Americans, 15.4% in the 13 Latina, and 50.0% in the 4 Asians.…”

Cost-effectiveness of Population-Wide Genomic Screening for Hereditary Breast and Ovarian Cancer in the United States

“…The PROSE consortium findings were supported by a small sample of RRM and RRSO uptake data from the Geisinger MyCode Community Health Initiative, which found that the RRM uptake during the first year of follow-up was 3.5% (2 of 57) and that the RRSO uptake was 11.8% (6 of 51) among known pathogenic BRCA1/2 carriers. 33 We did not identify comparable prophylactic surgery uptake data for non- BRCA1/2 variants, so we assumed RRM and RRSO uptake rates of 50% of the averaged uptakes of BRCA1 and BRCA2 carriers.…”

Leveraging population‐based exome screening to impact clinical care: The evolution of variant assessment in the Geisinger MyCode research project

“…Furthermore, EHR access also enables correlation of clinically relevant results with personal and family history of disease leading to more informed clinical care. Lastly, implementation of population genomic screening in an integrated, learning healthcare system allows longitudinal analyses of outcomes data and can inform future guidance on the personal, medical, and financial utility of such programs (Buchanan et al, 2020; Haggerty et al, 2017; Hao et al, 2020; Jones et al, 2018; Patel et al, 2019; Savatt et al, 2020) and facilitate expansion beyond what most programs are reporting at this time (Martin et al, 2020; Savatt et al, 2020).…”

“…While population‐scale genomic screening poses new challenges compared to current patient‐level approaches in the diagnostic setting, much of the literature on population‐scale screening has focused on recruitment, consent, clinical utility, and results disclosure (Buchanan et al, 2020; Grzymski et al, 2020; Hao et al, 2020; Ilori et al, 2020; Murray et al, 2018; Schwartz et al, 2018). Little attention has been given to the operational challenges of evaluating genomic data at a population‐scale.…”