The impact of sociodemographic, treatment, and work support on missed work after breast cancer diagnosis

Abstract

Work loss is a potential adverse consequence of cancer. There is limited research on patterns and correlates of paid work after diagnosis of breast cancer, especially among ethnic minorities. Women with non-metastatic breast cancer diagnosed from June 2005 to May 2006 who reported to the Los Angeles County SEER registry were identified and asked to complete the survey after initial treatment (median time from diagnosis = 8.9 months). Latina and African American women were over-sampled. Analyses were restricted to women working at the time of diagnosis, <65 years of age, and who had complete covariate information (N = 589). The outcome of the study was missed paid work (<or=1 month, >1 month, stopped all together). Approximately 44, 24, and 32% of women missed <or=1 month, >1 month, or stopped working, respectively. African Americans and Latinas were more likely to stop working when compared with Whites [OR for stop working vs. missed <or=1 month: 3.0, 3.4, (P < 0.001), respectively]. Women receiving mastectomy and those receiving chemotherapy were also more likely to stop working, independent of sociodemographic and treatment factors [ORs for stopped working vs. missed <or=1 month: 4.2, P < 0.001; 7.9, P < 0.001, respectively]. Not having a flexible work schedule available through work was detrimental to working [ORs for stopped working 18.9, P < 0.001 after adjusting for sociodemographic and treatment factors]. Many women stop working altogether after a diagnosis of breast cancer, particularly if they are racial/ethnic minorities, receive chemotherapy, or those who are employed in an unsupportive work settings. Health care providers need to be aware of these adverse consequences of breast cancer diagnosis and initial treatment.

Fig. 1

Enrollment of breast cancer patients and patterns of missed work

Fig. 2

Adjusted odds for missing more work or stopping work by race/ethnicity and acculturation (N = 589). Model adjusts for age, education, family income, number supported by family income, marital status, time from breast cancer diagnosis, number of co-morbidities, surgical procedure, receipt of radiation and chemotherapy, paid sick leave, and flexible work schedule, and full-time employment. P-value for test of overall significance 0.004