AbstractsMedical & Health Science

Cardiovascular disease in Type 1 diabetes: quantifying risk and addressing limitations in the analysis of longitudinal cohort studies

by Rachel G Miller




Institution: University of Pittsburgh
Department:
Year: 2016
Posted: 02/05/2017
Record ID: 2063819
Full text PDF: http://d-scholarship.pitt.edu/28541/1/MillerRG_2016_augETD.pdf


Abstract

Cardiovascular disease (CVD) has historically been increased in type 1 diabetes compared to the general population, but no contemporary estimates of risk are available in the United States. Additionally, the reasons for this increased risk are not fully understood, as the hyperglycemia that characterizes type 1 diabetes is itself an inconsistent predictor of CVD incidence. Thus, the objective of this dissertation is to quantify the contemporary incidence and excess risk of CVD in young adults <45 years old with type 1 diabetes and to utilize novel statistical methods to address limitations in the analyses of longitudinal cohort studies, in an effort to better understand the risk factor patterns that lead to CVD in this population. Data are from the Pittsburgh Epidemiology of Diabetes Complications study, a prospective cohort study of childhood-onset type 1 diabetes diagnosed at Children’s Hospital of Pittsburgh between 1950 and 1980. CVD data from the background Allegheny County, Pennsylvania population were used to calculate age- and sex-matched standardized mortality (SMR) and incidence rate ratios (IRR). Using tree-structured survival analysis (TSSA), formal subgroup analysis was performed to identify groups at varying levels of risk for CVD, based on threshold effects of continuous risk factors. Joint models were used to simultaneously model the longitudinal trajectory of HbA1c and time to CVD incidence. CVD risk was shown remain significantly increased in this type 1 diabetes cohort. TSSA identified a range of risk groups, which were defined by combinations of diabetes duration, non- HDL cholesterol, albumin excretion rate, and white blood cell count. The longitudinal trajectory of HbA1c was associated with CVD risk, similarly across all manifestations of CVD, including coronary artery disease, stroke, and lower extremity arterial disease, which is a new finding in this cohort. This work has important impacts on public health, as it confirms that individuals with type 1 diabetes continue to be at increased risk for CVD and demonstrates that novel statistical methods should be utilized as a complement to traditional methods to increase understanding of disease etiology.