Arica White1, Lisa C Richardson, Helen Krontiras, Maria Pisu. 1. 1 Division of Cancer Prevention and Control, National Center for Chronic Disease and Health Promotion, Centers for Disease Control and Prevention , Atlanta, Georgia .
Abstract
BACKGROUND: Racial disparities in breast cancer treatment among Medicare beneficiaries have been documented. This study aimed to determine whether racial disparities exist among white and black female Medicare beneficiaries in Alabama, an economically disadvantaged U.S. state. METHODS: From a linked dataset of breast cancer cases from the Alabama Statewide Cancer Registry and fee-for-service claims from Medicare, we identified 2,097 white and black females, aged 66 years and older, who were diagnosed with stages 1-3 breast cancer from January 1, 2000, to December 31, 2002. Generalized estimating equation (GEE) models were used to determine whether there were racial differences in initiating and completing National Comprehensive Cancer Network Clinical Practice guideline-specific treatment. RESULTS: Sixty-two percent of whites and 64.7% of blacks had mastectomy (p=0.27); 34.6% of whites and 30.2% of blacks had breast conserving surgery (BCS) (p=0.12). Among those who had BCS, 76.8% of whites and 83.3% of blacks started adjuvant radiation therapy (p=0.33) and they equally completed adjuvant radiation therapy (p=0.29). For women with tumors over 1 centimeter, whites and blacks were equally likely to start (16.1% of whites and 18.3% of black; p=0.34) and complete (50.6% of whites and 46.3% of black; p=0.87) adjuvant chemotherapy. There were still no differences after adjusting for confounders using GEE. However, differences were observed by area-level socioeconomic status (SES), with lower SES residents more likely to receive a mastectomy (odds ratio [OR]=1.26; 95% confidence interval [CI]: 1.01-1.57) and initiate radiation after BCS (OR=2.24; 95% CI: 1.28-3.93). CONCLUSIONS: No racial differences were found in guideline-specific breast cancer treatment or treatment completion, but there were differences by SES. Future studies should explore reasons for SES differences and whether similar results hold in other economically disadvantaged U.S. states.
BACKGROUND: Racial disparities in breast cancer treatment among Medicare beneficiaries have been documented. This study aimed to determine whether racial disparities exist among white and black female Medicare beneficiaries in Alabama, an economically disadvantaged U.S. state. METHODS: From a linked dataset of breast cancer cases from the Alabama Statewide Cancer Registry and fee-for-service claims from Medicare, we identified 2,097 white and black females, aged 66 years and older, who were diagnosed with stages 1-3 breast cancer from January 1, 2000, to December 31, 2002. Generalized estimating equation (GEE) models were used to determine whether there were racial differences in initiating and completing National Comprehensive Cancer Network Clinical Practice guideline-specific treatment. RESULTS: Sixty-two percent of whites and 64.7% of blacks had mastectomy (p=0.27); 34.6% of whites and 30.2% of blacks had breast conserving surgery (BCS) (p=0.12). Among those who had BCS, 76.8% of whites and 83.3% of blacks started adjuvant radiation therapy (p=0.33) and they equally completed adjuvant radiation therapy (p=0.29). For women with tumors over 1 centimeter, whites and blacks were equally likely to start (16.1% of whites and 18.3% of black; p=0.34) and complete (50.6% of whites and 46.3% of black; p=0.87) adjuvant chemotherapy. There were still no differences after adjusting for confounders using GEE. However, differences were observed by area-level socioeconomic status (SES), with lower SES residents more likely to receive a mastectomy (odds ratio [OR]=1.26; 95% confidence interval [CI]: 1.01-1.57) and initiate radiation after BCS (OR=2.24; 95% CI: 1.28-3.93). CONCLUSIONS: No racial differences were found in guideline-specific breast cancer treatment or treatment completion, but there were differences by SES. Future studies should explore reasons for SES differences and whether similar results hold in other economically disadvantaged U.S. states.
Authors: Paula M Lantz; Nancy K Janz; Angela Fagerlin; Kendra Schwartz; Lihua Liu; Indu Lakhani; Barbara Salem; Steven J Katz Journal: Health Serv Res Date: 2005-06 Impact factor: 3.402
Authors: Brenda K Edwards; Martin L Brown; Phyllis A Wingo; Holly L Howe; Elizabeth Ward; Lynn A G Ries; Deborah Schrag; Patricia M Jamison; Ahmedin Jemal; Xiao Cheng Wu; Carol Friedman; Linda Harlan; Joan Warren; Robert N Anderson; Linda W Pickle Journal: J Natl Cancer Inst Date: 2005-10-05 Impact factor: 13.506
Authors: Lydia Voti; Lisa C Richardson; Isildinha M Reis; Lora E Fleming; Jill Mackinnon; Jan Willem W Coebergh Journal: Cancer Date: 2006-01-01 Impact factor: 6.860
Authors: Jie Zhang; Zhi-Wei Ye; Danyelle M Townsend; Chanita Hughes-Halbert; Kenneth D Tew Journal: Adv Cancer Res Date: 2019-04-23 Impact factor: 6.242
Authors: Stephen R Grant; Gary V Walker; B Ashleigh Guadagnolo; Matthew Koshy; Pamela K Allen; Usama Mahmood Journal: Cancer Date: 2015-04-27 Impact factor: 6.860
Authors: Jessica L Krok-Schoen; James L Fisher; Ryan D Baltic; Electra D Paskett Journal: Cancer Epidemiol Biomarkers Prev Date: 2016-08-15 Impact factor: 4.254
Authors: Shearwood McClelland; Brandi R Page; Jerry J Jaboin; Christina H Chapman; Curtiland Deville; Charles R Thomas Journal: Adv Radiat Oncol Date: 2017-08-03