Cardiovascular disease risk in long-term breast cancer survivors: A population-based cohort study.

BACKGROUND: Breast cancer survival is increasing, making late effects such as cardiovascular disease (CVD) more relevant. The purpose of this study was to evaluate incident CVD following breast cancer diagnosis among long-term survivors and to investigate possible risk factors for CVD. METHODS: A population-based cohort of 6641 breast cancer survivors diagnosed between 1997 and 2009 who survived at least 10 years was identified within the Utah Cancer Registry. In addition, 36,612 cancer-free women from the general population, matched by birth year and state, were identified within the Utah Population Database. Cox proportional hazards models were used to calculate CVD hazard ratios (HRs) for >10 to 15 and >15 years. RESULTS: Long-term breast cancer survivors had an increased risk of newly diagnosed diseases of the circulatory system (HR, 1.32; 99% confidence interval [CI], 1.00-1.75) from 10 to 15 years following cancer diagnosis compared with the general population. No increased CVD risks were observed after 15 years. Breast cancer survivors with Charlson Comorbidity Index score ≥2 had a significantly higher risk of diseases of the circulatory system (HR, 2.64; 95% CI, 1.08-6.45) beyond 10 years following breast cancer diagnosis. Similarly, older age, obesity, lower education, and family history of CVD and breast cancer were risk factors for heart and circulatory system diseases among long-term breast cancer survivors. CONCLUSION: Risk of CVD compared to the general population was moderate among this cohort of long-term breast cancer survivors between 10 to 15 years since cancer diagnosis. Awareness of CVD risks is important for breast cancer survivors.

Generating Older Adult Multimorbidity Trajectories Using Various Comorbidity Indices and Calculation Methods.

Background and Objectives: Older adult multimorbidity trajectories are helpful for understanding the current and future health patterns of aging populations. The construction of multimorbidity trajectories from comorbidity index scores will help inform public health and clinical interventions targeting those individuals that are on unhealthy trajectories. Investigators have used many different techniques when creating multimorbidity trajectories in prior literature, and no standard way has emerged. This study compares and contrasts multimorbidity trajectories constructed from various methods. Research Design and Methods: We describe the difference between aging trajectories constructed with the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI). We also explore the differences between acute (single-year) and chronic (cumulative) derivations of CCI and ECI scores. Social determinants of health can affect disease burden over time; thus, our models include income, race/ethnicity, and sex differences. Results: We use group-based trajectory modeling (GBTM) to estimate multimorbidity trajectories for 86,909 individuals aged 66-75 in 1992 using Medicare claims data collected over the following 21 years. We identify low-chronic disease and high-chronic disease trajectories in all 8 generated trajectory models. Additionally, all 8 models satisfied prior established statistical diagnostic criteria for well-performing GBTM models. Discussion and Implications: Clinicians may use these trajectories to identify patients on an unhealthy path and prompt a possible intervention that may shift the patient to a healthier trajectory.