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Background: Robust and reliable prognosis prediction models have not been developed and validated for Asian patients with breast cancer, a rapidly growing yet understudied population in the United States.Methods: We used longitudinal data from the Shanghai Breast Cancer Survival Study, a population-based prospective cohort study (n = 5042), to develop prediction models for 5- and 10-year disease-free survival (DFS) and overall survival (OS). The initial models considered age at diagnosis, tumor grade, tumor size, number of positive nodes, TNM stage, chemotherapy, tamoxifen therapy, and estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status. We then evaluated whether the addition of modifiable lifestyle factors (physical activity, soy isoflavones intake, and postdiagnostic weight change) improved the models. All final models have been validated internally and externally in the National Cancer Database when applicable.Results: Our final models included age at diagnosis, tumor grade, tumor size, number of positive nodes, TNM stage, chemotherapy, tamoxifen therapy, ER status, PR status, 6-month postdiagnostic weight change, interaction between ER status and tamoxifen therapy, and interaction between age and TNM stage. The internal validation yielded C-statistics of 0.76, 0.74, 0.78, and 0.75 for 5-year DFS, 10-year DFS, 5-year OS, and 10-year OS, respectively. The external validation yielded C-statistics of 5- and 10-year OS both at 0.78 for Chinese ethnicity, 0.79 for East Asian ethnicity, and 0.75 and 0.76 for all ethnic groups combined.Conclusion: We developed prediction models for breast cancer prognosis from a large prospective study. Our prognostic models performed very well in women from the United States-particularly in Asian American women-and demonstrated high prediction accuracy and generalizability. [ABSTRACT FROM AUTHOR]

Depression is a leading cause of disability in the United States, but its impact on mortality rates among racially diverse populations of low socioeconomic status is largely unknown. Using data from the Southern Community Cohort Study, 2002–2015, we prospectively evaluated the associations of depressive symptoms with all-cause and cause-specific mortality in 67,781 Black (72.3%) and White (27.7%) adults, a population predominantly with a low socioeconomic status. Baseline depressive symptoms were assessed using the 10-item Center for Epidemiological Studies Depression Scale. The median follow-up time was 10.0 years. Multivariate Cox regression was used to estimate hazard ratios and 95% confidence intervals for death in association with depressive symptoms. Mild, moderate, and severe depressive symptoms were associated with increased all-cause (hazard ratio (HR) = 1.12, 95% confidence interval (CI): 1.03, 1.22; HR = 1.17, 95% CI: 1.06, 1.29; HR = 1.15, 95% CI: 1.03, 1.28, respectively) and cardiovascular disease–associated death (HR = 1.23, 95% CI: 1.05, 1.44; HR = 1.18, 95% CI: 0.98, 1.42; HR = 1.43, 95% CI: 1.17, 1.75, respectively) in Whites but not in Blacks (P for interaction < 0.001, for both). Mild, moderate, or severe depressive symptoms were associated with increased rates of external-cause mortality in both races (HR = 1.24, 95% CI: 1.05, 1.46; HR = 1.31, 95% CI: 1.06, 1.61; HR = 1.42, 95% CI: 1.11, 1.81, respectively; for all study subjects, P for interaction = 0.48). No association was observed for cancer-associated deaths. Our study showed that the association between depression and death differed by race and cause of death in individuals with a low socioeconomic status. [ABSTRACT FROM AUTHOR]