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Cardiovascular-Related Death Among Women With Breast Cancer in the United States: Do We Need a Better Approach for
Nguyen Le1, Yan Liu2, Chanhyun Park1
1Health Outcomes Division, College of Pharmacy, The University of Texas at Austin, Austin, TX, USA.
None:
Breast cancer is the most common cancer among women in the United States, and cardiovascular disease (CVD) is a leading cause of death in this population. Understanding CVD-related death among breast cancer survivors is critical to inform policies. Previous studies calculating CVD-related death rates in this population used data from the Centers for Disease Control and Prevention (CDC) Wide-ranging ONline Data for Epidemiologic Research (WONDER) with the general US female population as the denominator, which may have produced misleading comparisons. For example, age-adjusted CVD-related death rates have appeared lower among women with breast cancer than in the general US female population, despite survivors facing an elevated CVD risk, understating the need for CVD-focused survivorship care. We demonstrated 2 methodologically appropriate approaches for estimating CVD-related death rates among US women with breast cancer from 1999 through 2020, using a denominator restricted to the breast cancer survivor population, derived from Surveillance, Epidemiology, and End Results (SEER) and Projected Prevalence (ProjPrev) data. We found trends in CVD-related death rates that were broadly consistent with previous studies, with an average annual percentage change of -1.8 (95% CI, -2.0 to -1.6). Our estimates were more intuitive than those from previous studies because they correctly reflected an elevated, rather than reduced, risk relative to the general population: the age-adjusted CVD-related death rate per 100 000 women with breast cancer was 1078.1 in 1999 and 733.1 in 2020. These findings suggest that our approaches can be applied to future research on cause-specific mortality among patients with cancer using CDC WONDER data. Future studies may improve generalizability and identify strategies for linking databases to generate more accessible evidence for public health decision-making.
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