Jihoon J Choi1, Tsion Fikre1, Alexandra Fischman2, Anne K Buck1,2, Naomi Y Ko1,3. 1. Boston Medical Center, Boston, MA, USA. 2. Graduate Medical Sciences, Boston University School of Medicine, Boston, MA, USA. 3. Department of Medicine, Section of Hematology Oncology, Boston University School of Medicine, Boston, MA, USA.
Abstract
PURPOSE: The role of germline genetic testing in breast cancer patients is crucial, especially in the setting of the recent trials showing the benefit of PARP inhibitors. The goal of this study was to identify racial disparities in genetic counseling and testing in patients with high-risk breast cancer. METHODS: Patients with 2 unique breast cancer diagnoses were examined to understand demographics, insurance coverage, characteristics of breast cancer, and whether they were recommended for and received genetic counseling and testing. RESULTS: A total of 69 patients with a dual diagnosis of breast cancer between the years 2000 and 2017 were identified (42% identified as White compared to 58% that identified as non-White). White patients were more likely to be recommended for genetic counseling (OR = 2.85; 95% CI, 1.07-7.93, P < .05), be referred for genetic counseling (OR = 3.17; 95% CI, 1.19-8.86, P < .05), receive counseling (OR = 3.82; 95% CI, 1.42-10.83, P < .01), and undergo genetic testing (OR = 2.88; 95% CI, 0.97-9.09, P = .056) compared to non-White patients. Patients with private insurance were significantly more likely to be recommended for genetic counseling (OR 5.63, P < .005), referred (OR 6.11, P < .005), receive counseling (OR 4.21, P < .05), and undergo testing (OR 4.10, P < .05). When controlled for insurance, there was no significant racial differences in the rates of GC recommendation, referral, counseling, or testing. CONCLUSION: The findings of this study suggest that disparities in genetic counseling and testing are largely driven by differences in health insurance.
PURPOSE: The role of germline genetic testing in breast cancer patients is crucial, especially in the setting of the recent trials showing the benefit of PARP inhibitors. The goal of this study was to identify racial disparities in genetic counseling and testing in patients with high-risk breast cancer. METHODS: Patients with 2 unique breast cancer diagnoses were examined to understand demographics, insurance coverage, characteristics of breast cancer, and whether they were recommended for and received genetic counseling and testing. RESULTS: A total of 69 patients with a dual diagnosis of breast cancer between the years 2000 and 2017 were identified (42% identified as White compared to 58% that identified as non-White). White patients were more likely to be recommended for genetic counseling (OR = 2.85; 95% CI, 1.07-7.93, P < .05), be referred for genetic counseling (OR = 3.17; 95% CI, 1.19-8.86, P < .05), receive counseling (OR = 3.82; 95% CI, 1.42-10.83, P < .01), and undergo genetic testing (OR = 2.88; 95% CI, 0.97-9.09, P = .056) compared to non-White patients. Patients with private insurance were significantly more likely to be recommended for genetic counseling (OR 5.63, P < .005), referred (OR 6.11, P < .005), receive counseling (OR 4.21, P < .05), and undergo testing (OR 4.10, P < .05). When controlled for insurance, there was no significant racial differences in the rates of GC recommendation, referral, counseling, or testing. CONCLUSION: The findings of this study suggest that disparities in genetic counseling and testing are largely driven by differences in health insurance.
Authors: Lisa R Susswein; Cécile Skrzynia; Leslie A Lange; Jessica K Booker; Mark L Graham; James P Evans Journal: J Clin Oncol Date: 2008-01-01 Impact factor: 44.544
Authors: Douglas K Owens; Karina W Davidson; Alex H Krist; Michael J Barry; Michael Cabana; Aaron B Caughey; Chyke A Doubeni; John W Epling; Martha Kubik; C Seth Landefeld; Carol M Mangione; Lori Pbert; Michael Silverstein; Melissa A Simon; Chien-Wen Tseng; John B Wong Journal: JAMA Date: 2019-08-20 Impact factor: 56.272
Authors: Deborah Cragun; Anne Weidner; Courtney Lewis; Devon Bonner; Jongphil Kim; Susan T Vadaparampil; Tuya Pal Journal: Cancer Date: 2017-02-09 Impact factor: 6.860
Authors: Christopher P Childers; Kimberly K Childers; Melinda Maggard-Gibbons; James Macinko Journal: J Clin Oncol Date: 2017-08-18 Impact factor: 44.544
Authors: Mark Robson; Seock-Ah Im; Elżbieta Senkus; Binghe Xu; Susan M Domchek; Norikazu Masuda; Suzette Delaloge; Wei Li; Nadine Tung; Anne Armstrong; Wenting Wu; Carsten Goessl; Sarah Runswick; Pierfranco Conte Journal: N Engl J Med Date: 2017-06-04 Impact factor: 91.245
Authors: Judy C Boughey; Deanna J Attai; Steven L Chen; Hiram S Cody; Jill R Dietz; Sheldon M Feldman; Caprice C Greenberg; Rena B Kass; Jeffrey Landercasper; Valerie Lemaine; Fiona MacNeill; David H Song; Alicia C Staley; Lee G Wilke; Shawna C Willey; Katharine A Yao; Julie A Margenthaler Journal: Ann Surg Oncol Date: 2016-07-28 Impact factor: 5.344
Authors: Yazmin San Miguel; Scarlett Lin Gomez; James D Murphy; Richard B Schwab; Corinne McDaniels-Davidson; Alison J Canchola; Alfredo A Molinolo; Jesse N Nodora; Maria Elena Martinez Journal: BMC Cancer Date: 2020-03-17 Impact factor: 4.430