Patient-reported causes of distress predict disparities in time to evaluation and time to treatment after breast cancer diagnosis.
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.
Fayanju, Oluwadamilola M., Yi Ren, Ilona Stashko, Steve Power, Madeline J. Thornton, P Kelly Marcom, Terry Hyslop, and E Shelley Hwang. “Patient-reported causes of distress predict disparities in time to evaluation and time to treatment after breast cancer diagnosis.” Cancer 127, no. 5 (March 1, 2021): 757–68. https://doi.org/10.1002/cncr.33310.