BACKGROUND Little is known about the size and characteristics of the decision‐support networks of women newly diagnosed with breast cancer and whether their involvement improves breast cancer treatment decisions. METHODS A population‐based sample of patients newly diagnosed with breast cancer in 2014 and 2015, as reported to the Georgia and Los Angeles Surveillance, Epidemiology, and End Results registries, were surveyed approximately 7 months after diagnosis (N = 2502; response rate, 68%). Network size was estimated by asking women to list up to 3 of the most important decision‐support persons (DSPs) who helped them with locoregional therapy decisions. Decision deliberation was measured using 4 items assessing the degree to which patients thought through the decision, with higher scores reflecting more deliberative breast cancer treatment decisions. The size of the network (range, 0‐3 or more) was compared across patient‐level characteristics, and adjusted mean deliberation scores were estimated across levels of network size using multivariable linear regression. RESULTS Of the 2502 women included in this analysis, 51% reported having 3 or more DSPs, 20% reported 2, 18% reported 1, and 11% reported not having any DSPs. Married/partnered women, those younger than 45 years, and black women all were more likely to report larger network sizes (all P < .001). Larger support networks were associated with more deliberative surgical treatment decisions (P < .001). CONCLUSIONS Most women engaged multiple DSPs in their treatment decision making, and involving more DSPs was associated with more deliberative treatment decisions. Future initiatives to improve treatment decision making among women with breast cancer should acknowledge and engage informal DSPs. Cancer 2017;123:3895‐903. © 2017 American Cancer Society.
e18241 Background: Many women with breast cancer face job loss related to their diagnosis, but little is known about employment outcomes among their partners and other supporters. Moreover, virtually nothing is known about associations between patients’ quality of life and supporters’ employment status. Methods: Breast cancer patients reported to Georgia and LA SEER registries in 2014-15 (N = 2,502, 68% RR) and their key decision support person (DSP) were surveyed separately. 1234 DSPs responded (71% RR). Patients and DSPs were asked about employment impacts of the patient’s breast cancer. Patients’ quality of life (QOL) was measured with the PROMIS scale for global health. Descriptive analyses of employment outcomes (job loss, missed days due to cancer) were generated for patients and DSPs. Associations between patients’ QOL and employment status of patients and their DSPs were assessed using linear mixed model regression analyses stratified by dyad type (partner vs. non-partner DSP). Results: Among DSPs, 43% were partners. 57% were non-partners (daughters, other family, friends). 67% were employed at time of patient’s diagnosis. Among these, 11% were no longer employed at survey completion. 39% missed > 30 days work. Non-partner DSPs were as likely as partners to lose their job or miss work because of the patient’s cancer. 65% patients were employed at diagnosis. Compared to patients whose DSP was a partner, patients with non-partner DSP were more likely to lose their job (39% vs. 24%; p < 0.01) or miss > 30 days work (55% vs. 45%; p < 0.01). For patients with a partner DSP, both patient and DSP employment at diagnosis were associated with improved patient QOL (each associated with a QOL score 24% of 1 standard deviation higher; each p < 0.05). For patients with non-partner DSPs, only patient employment at diagnosis was associated with improved patient QOL (QOL score 51% of 1 standard deviation higher; p < 0.01). Conclusions: Both non-partner and partner DSPs faced negative employment impacts related to patients’ breast cancer. Job loss and > 30 days of missed work were more likely among patients with non-partner DSPs. Only the employment of partner DSPs at diagnosis positively contributed to patients’ QOL.
176 Background: Many women with breast cancer face job loss related to their diagnosis, but little is known about employment outcomes among their partners and other supporters. Moreover, virtually nothing is known about associations between patients’ quality of life and supporters’ employment outcomes. Methods: Breast cancer patients reported to Georgia and LA SEER registries in 2014-15 (N = 2,502, 68% RR) and their key decision support person (DSP) were surveyed separately. 1234 DSPs responded (71% RR). Patients and DSPs were asked about employment impacts of the patient’s breast cancer. Patients’ quality of life (QOL) was measured with the PROMIS scale for global health. Descriptive analyses of employment outcomes (job loss, missed days due to cancer) were generated for patients and DSPs. Associations between patients’ QOL and employment outcomes of patients and their DSPs were assessed using linear mixed model regression analyses stratified by dyad type (partner vs. non-partner DSP). Results: Among DSPs, 43% were partners. 57% were non-partners (daughters, other family, friends). 67% were employed at time of patient’s diagnosis. Among these, 11% were no longer employed at survey completion. 39% missed >30 days work. Non-partner DSPs were as likely as partners to lose their job or miss work because of the patient’s cancer. 65% patients were employed at diagnosis. Compared to patients whose DSP was a partner, patients with non-partner DSP were more likely to lose their job (39% vs. 24%; p<0.01) or miss >30 days work (55% vs. 45%; p<0.01). For patients with partner and non-partner DSPs, having an employed DSP at diagnosis and having an employed DSP who stays employed were associated with improved patient QOL after adjustment for DSP sociodemographic and patient clinical variables. Conclusions: Both non-partner and partner DSPs faced negative employment impacts related to patients’ breast cancer. Job loss and >30 days of missed work were more likely among patients with non-partner DSPs. Having an employed DSP and having an employed DSP who stays employed positively contributed to patients’ QOL.
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