Oluwadamilola M Fayanju1,2,3,4,5, Yi Ren6, Ilona Stashko6, Steve Power7, Madeline J Thornton1, P Kelly Marcom2,8, Terry Hyslop6,9, E Shelley Hwang1,2. 1. Department of Surgery, Duke University Medical Center, Durham, North Carolina. 2. Women's Cancer Program, Duke Cancer Institute, Durham, North Carolina. 3. Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina. 4. Duke Forge, Duke University, Durham, North Carolina. 5. Department of Surgery, Durham VA Medical Center, Durham, North Carolina. 6. Biostatistics Shared Resource, Duke Cancer Institute, Durham, North Carolina. 7. Department of Quality and Outcomes, Duke Cancer Institute, Durham, North Carolina. 8. Department of Medicine, Duke University Medical Center, Durham, North Carolina. 9. Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina.
Abstract
BACKGROUND: We examined whether the National Comprehensive Cancer Network distress thermometer (DT), a patient-reported outcome measure, could be used to identify levels and causes of distress associated with racial/ethnic disparities in time to care among patients with breast cancer. METHODS: We identified women aged ≥18 years with stage 0-IV breast cancer who were diagnosed in a single health system between January 2014 and July 2016. The baseline visit was defined as the first postdiagnosis, pretreatment clinical evaluation. Zero-inflated negative binomial (ZINB) regression (modeling non-zero DT scores and DT scores = 0) and logistic regression (modeling DT score ≥ 4, threshold for social services referral) were used to examine associations between baseline score (0 = none to 10 = extreme) and types of stressors (emotional, familial, practical, physical, spiritual) after adjustment for race/ethnicity and other characteristics. Linear regression with log transformation was used to identify predictors of time to evaluation and time to treatment. RESULTS: A total of 1029 women were included (median baseline DT score = 4). Emotional, physical, and practical stressors were associated with distress in both the ZINB and logistic models (all P < .05). Black patients (n = 258) were more likely to report no distress than Whites (n = 675; ZINB zero model odds ratio, 2.72; 95% CI, 1.68-4.40; P < .001) despite reporting a similar number of stressors (P = .07). Higher DT scores were associated with shorter time to evaluation and time to treatment while being Black and having physical or practical stressors were associated with delays in both (all P < .05). CONCLUSIONS: Patient-reported stressors predicted delays in time to care, but patient-reported levels of distress did not, with Black patients having delayed time to care despite reporting low levels of distress. We describe anticipatory, culturally responsive strategies for using patient-reported outcomes to address observed disparities.
BACKGROUND: We examined whether the National Comprehensive Cancer Network distress thermometer (DT), a patient-reported outcome measure, could be used to identify levels and causes of distress associated with racial/ethnic disparities in time to care among patients with breast cancer. METHODS: We identified women aged ≥18 years with stage 0-IV breast cancer who were diagnosed in a single health system between January 2014 and July 2016. The baseline visit was defined as the first postdiagnosis, pretreatment clinical evaluation. Zero-inflated negative binomial (ZINB) regression (modeling non-zero DT scores and DT scores = 0) and logistic regression (modeling DT score ≥ 4, threshold for social services referral) were used to examine associations between baseline score (0 = none to 10 = extreme) and types of stressors (emotional, familial, practical, physical, spiritual) after adjustment for race/ethnicity and other characteristics. Linear regression with log transformation was used to identify predictors of time to evaluation and time to treatment. RESULTS: A total of 1029 women were included (median baseline DT score = 4). Emotional, physical, and practical stressors were associated with distress in both the ZINB and logistic models (all P < .05). Black patients (n = 258) were more likely to report no distress than Whites (n = 675; ZINB zero model odds ratio, 2.72; 95% CI, 1.68-4.40; P < .001) despite reporting a similar number of stressors (P = .07). Higher DT scores were associated with shorter time to evaluation and time to treatment while being Black and having physical or practical stressors were associated with delays in both (all P < .05). CONCLUSIONS: Patient-reported stressors predicted delays in time to care, but patient-reported levels of distress did not, with Black patients having delayed time to care despite reporting low levels of distress. We describe anticipatory, culturally responsive strategies for using patient-reported outcomes to address observed disparities.
Authors: William A Grobman; Corette B Parker; Marian Willinger; Deborah A Wing; Robert M Silver; Ronald J Wapner; Hyagriv N Simhan; Samuel Parry; Brian M Mercer; David M Haas; Alan M Peaceman; Shannon Hunter; Pathik Wadhwa; Michal A Elovitz; Tatiana Foroud; George Saade; Uma M Reddy Journal: Obstet Gynecol Date: 2018-02 Impact factor: 7.661
Authors: Vanessa B Sheppard; Bridget A Oppong; Regina Hampton; Felicia Snead; Sara Horton; Fikru Hirpa; Echo J Brathwaite; Kepher Makambi; S Onyewu; Marc Boisvert; Shawna Willey Journal: Ann Surg Oncol Date: 2015-02-05 Impact factor: 5.344
Authors: Amy C Polverini; Rebecca A Nelson; Emily Marcinkowski; Veronica C Jones; Lily Lai; Joanne E Mortimer; Lesley Taylor; Courtney Vito; John Yim; Laura Kruper Journal: Ann Surg Oncol Date: 2016-08-08 Impact factor: 5.344
Authors: Sage J Kim; Anne Elizabeth Glassgow; Karriem S Watson; Yamile Molina; Elizabeth A Calhoun Journal: Cancer Date: 2018-09-24 Impact factor: 6.860
Authors: Hadley W Reid; Gloria Broadwater; Mary Katherine Montes de Oca; Bharathi Selvan; Oluwadamilola Fayanju; Laura J Havrilesky; Brittany A Davidson Journal: Gynecol Oncol Date: 2022-01-10 Impact factor: 5.482
Authors: Urvish Jain; Bhav Jain; Oluwadamilola M Fayanju; Fumiko Chino; Edward Christopher Dee Journal: Am J Surg Date: 2022-01-22 Impact factor: 3.125
Authors: Ronnie J Zipkin; Andrew Schaefer; Changzhen Wang; Andrew P Loehrer; Nirav S Kapadia; Gabriel A Brooks; Tracy Onega; Fahui Wang; Alistair J O'Malley; Erika L Moen Journal: Ann Surg Oncol Date: 2022-05-24 Impact factor: 4.339
Authors: Sarah D Tait; Yi Ren; Cushanta C Horton; Sachiko M Oshima; Samantha M Thomas; Sherry Wright; Awanya Caesar; Jennifer K Plichta; E Shelley Hwang; Rachel A Greenup; Laura H Rosenberger; Gayle D DiLalla; Carolyn S Menendez; Lisa Tolnitch; Terry Hyslop; Debi Nelson; Oluwadamilola M Fayanju Journal: Cancer Date: 2021-04-07 Impact factor: 6.921
Authors: Xin Hu; Puneet K Chehal; Cameron Kaplan; Rebecca A Krukowski; Roy H Lan; Edward Stepanski; Lee Schwartzberg; Gregory Vidal; Ilana Graetz Journal: JAMA Netw Open Date: 2021-06-01