Reliable burden of disease (BOD) estimates are needed to support decision making in health care.
The objective of this study was to introduce an analysis approach based on individual-level longitudinal survey data that estimates the burden of diabetes in patients with coronary heart disease in terms of quality-adjusted life-years (QALYs) lost.
Data from two postal surveys (2006, N = 1022; 2010–2011, N = 716) of survivors from the KORA Myocardial Infarction Registry in Southern Germany were analyzed. Accumulated QALYs were calculated for each participant over a mean observation time of 4.1 years, considering the noninformative censoring structure of the follow-up study. Linear regression models were used to estimate the loss in (quality-unadjusted) life-years and QALYs between patients with and without diabetes, and generalized additive models were used to analyze the nonlinear association with age. The cross-sectional and longitudinal association with quality of life (QOL) and QOL change and the impact on mortality were analyzed to enhance the understanding of the observed results.
Diabetes was associated with a reduced QOL at baseline (cross-sectional: β = –0.069; P 0.001). Results from generalized additive models indicated that the burden of diabetes is less pronounced in older subjects.
The application of the proposed approach provides confounder-adjusted BOD estimates for the studied time horizon and can be used to compare the BOD across different chronic conditions. Curative efforts are needed to diminish the substantial diabetes-related QALY gap.