Abstract
Background: Social factors and physical pain are related bidirectionally and as a function of temperament and disease processes, but the relevance of this to population research is unknown. We developed social-pain clusters, or groups that were similar with regard to social and pain characteristics, in a large, population-based cohort of women with breast cancer, evaluating associations of resulting clusters with sociodemographic factors and mortality.
Methods: The study population included 4,279 women from the Pathways Study, a prospective cohort study of women diagnosed from 2006-2013 with stages I-IV breast cancer in Kaiser Permanente Northern California, who provided data on social (social integration, social well-being, loneliness, social well-being) and bodily pain measures at study baseline. Measures included the Medical Outcomes Study Social Support survey, the Functional Assessment of Cancer Therapy, a single-item measure of loneliness from the Center for Epidemiologic Studies-Depression measure, and a previously derived measure of social integration (Kroenke et al.). We used latent class analysis to develop social-pain clusters and used BIC criteria to select the optimal number of clusters. We further evaluated associations of age, race/ethnicity, education, and income with clusters in multivariate-adjusted logistic regression analyses, with adjustment for depressive symptoms, and also evaluated associations of clusters with mortality using Cox models.
Results: Cluster analysis produced three clusters including a “resilient” cluster characterized by low social and pain symptomatology (including 30% of study participants), a “distressed” cluster characterized by high symptomatology (20% of participants), and an intermediate cluster characterized by high pain and compromised social function but otherwise high support (50% of participants). Sociodemographic factors associated with higher odds of categorization in the distressed (vs. resilient) cluster included age (OR=1.04, 95% CI: 1.02-1.05), income <$25K (OR=9.30, 95% CI: 5.72-15.13), API race/ethnicity (OR=2.51, 95% CI: 1.72-3.67), and graduate-level education (OR=1.60, 95% CI: 1.16-2.22). Age, low income, and API race/ethnicity were also related to higher odds of categorization in the intermediate (vs. resilient) cluster. However, those in the distressed (HR=1.38, 95% CI: 1.06-1.80), but not intermediate (HR=1.05, CI: 0.83-1.33), cluster had a higher risk of overall mortality.
Conclusions: Age, low income, and API race/ethnicity predicted higher social and pain symptomatology in a population-based breast cancer cohort, independent of depressive symptoms. The clustering of these symptoms was related to higher overall mortality.
Reference: Kroenke CH, Kwan ML, Neugut AI, Ergas IJ, Wright JD, Caan BJ, Hershman D, Kushi LH. Social networks, social support mechanisms, and quality of life after breast cancer diagnosis. Breast Cancer Res Treat 2013;139(2):515-27.
Citation Format: Candyce H. Kroenke, Stacey Alexeeff, Scarlett Lin Gomez, Marilyn L. Kwan, Lawrence H. Kushi. Social-pain clusters in diverse women with breast cancer, and associations with sociodemographic factors and mortality [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr A079.
