Utility Decrements Associated With Diabetes and Related Complications: Estimates From a Population-Based Study in Germany.

OBJECTIVES: Health utility decrement estimates for diabetes and complications are needed for parametrization of simulation models that aim to assess the cost-utility of diabetes prevention and care strategies. This study estimates health utility decrements associated with diabetes and cardiovascular and microvascular complications from a population-based German study. METHODS: Data were obtained from the population based cross-sectional KORA (Cooperative Health Research in the Augsburg Region) health questionnaire 2016 and comprised n = 1072 individuals with type 2 diabetes and n = 7879 individuals without diabetes. Health utility was assessed through the EQ-5D-5L. We used linear regression models with interaction terms between type 2 diabetes and different cardiovascular and microvascular complications while adjusting for demographic and socio-economic factors and other comorbidities. RESULTS: Type 2 diabetes (ß = -0.028, standard error [SE] = 0.014), stroke (ß = -0.070, SE = 0.010), cardiac arrhythmia (ß = -0.031, SE = 0.006), heart failure (ß = -0.073, SE = 0.009), coronary heart disease (ß = -0.028, SE = 0.010), myocardial infarction (ß = -0.020, SE = 0.011, estimates of main effect), and neuropathy (ß = -0.067, SE = 0.020), diabetic foot (ß = -0.042, SE = 0.030), nephropathy (ß = -0.032, SE = 0.025), and blindness (ß = -0.094, SE = 0.056, estimates of interaction terms) were negatively associated with health utility. The interaction term for diabetes x stroke (ß = -0.052, SE = 0.021) showed that the utility decrement for stroke is significantly larger in people with type 2 diabetes than in people without diabetes. CONCLUSIONS: Diabetes, cardiovascular, and microvascular conditions are associated with significant health utility decrements. Utility decrements for some conditions differ between people with and without type 2 diabetes. These results are of high relevance for the parametrization of decision analytic simulation models and applied health economic evaluations in the field of prevention and management of type 2 diabetes in Germany.

Performance of the UKPDS Outcomes Model 2 for Predicting Death and Cardiovascular Events in Patients with Type 2 Diabetes Mellitus from a German Population-Based Cohort.

BACKGROUND AND OBJECTIVE: Accurate prediction of relevant outcomes is important for targeting therapies and to support health economic evaluations of healthcare interventions in patients with diabetes. The United Kingdom Prospective Diabetes Study (UKPDS) risk equations are some of the most frequently used risk equations. This study aims to analyze the calibration and discrimination of the updated UKPDS risk equations as implemented in the UKPDS Outcomes Model 2 (UKPDS-OM2) for predicting cardiovascular (CV) events and death in patients with type 2 diabetes mellitus (T2DM) from population-based German samples. METHODS: Analyses are based on data of 456 individuals diagnosed with T2DM who participated in two population-based studies in southern Germany (KORA (Cooperative Health Research in the Region of Augsburg)-A: 1997/1998, n = 178; KORA-S4: 1999-2001, n = 278). We compared the participants' 10-year observed incidence of mortality, CV mortality, myocardial infarction (MI), and stroke with the predicted event rate of the UKPDS-OM2. The model's calibration was evaluated by Greenwood-Nam-D'Agostino tests and discrimination was evaluated by C-statistics. RESULTS: Of the 456 participants with T2DM (mean age 65 years, mean diabetes duration 8 years, 56% male), over the 10-year follow-up time 129 died (61 due to CV events), 64 experienced an MI, and 46 a stroke. The UKPDS-OM2 significantly over-predicted mortality and CV mortality by 25% and 28%, respectively (Greenwood-Nam-D'Agostino tests: p < 0.01), but there was no significant difference between predicted and observed MI and stroke risk. The model poorly discriminated for death (C-statistic [95% confidence interval] = 0.64 [0.60-0.69]), CV death (0.64 [0.58-0.71]), and MI (0.58 [0.52-0.66]), and failed to discriminate for stroke (0.57 [0.47-0.66]). CONCLUSIONS: The study results demonstrate acceptable calibration and poor discrimination of the UKPDS-OM2 for predicting death and CV events in this population-based German sample. Those limitations should be considered when using the UKPDS-OM2 for economic evaluations of healthcare strategies or using the risk equations for clinical decision-making.

Exploring Different Strategies of Assessing the Economic Impact of Multiple Diabetes-Associated Complications and Their Interactions: A Large Claims-Based Study in Germany.

BACKGROUND: In the context of an aging population with increasing diabetes prevalence, people are living longer with diabetes, which leads to increased multimorbidity and economic burden. OBJECTIVE: The primary aim was to explore different strategies that address the economic impact of multiple type 2 diabetes-related complications and their interactions. METHODS: We used a generalized estimating equations approach based on nationwide statutory health insurance data from 316,220 patients with type 2 diabetes (baseline year 2012, 3 years of follow-up). We estimated annual total costs (in 2015 euros) for type 2 diabetes-related complications and, in addition, explored different strategies to assess diabetes-related multimorbidity: number of prevalent complications, co-occurrence of micro- and macrovascular complications, disease-disease interactions of prevalent complications, and interactions between prevalent/incident complications. RESULTS: The increased number of complications was significantly associated with higher total costs. Further assessment of interactions showed that macrovascular complications (e.g., chronic heart failure) and high-cost complications (e.g., end-stage renal disease, amputation) led to significant positive effects of interactions on costs, whereas early microvascular complications (e.g., retinopathy) caused negative interactions. The chronology of the onset of these complications turned out to have an additional impact on the interactions and their effect on total costs. CONCLUSIONS: Health economic diabetes models and evaluations of interventions in patients with diabetes-related complications should pay more attention to the economic effect of specific disease interactions. Politically, our findings support the development of more integrated diabetes care programs that take better account of multimorbidity. Further observational studies are needed to elucidate the shared pathogenic mechanisms of diabetes complications.

Health Care Costs Associated With Incident Complications in Patients With Type 2 Diabetes in Germany.

OBJECTIVE: The aim of this study is to provide reliable regression-based estimates of costs associated with different type 2 diabetes complications. RESEARCH DESIGN AND METHODS: We used nationwide statutory health insurance (SHI) data from 316,220 patients with type 2 diabetes. Costs for inpatient and outpatient care, pharmaceuticals, rehabilitation, and nonmedical aids and appliances were assessed in the years 2013-2015. Quarterly observations are available for each year. We estimated costs (in 2015 euro) for complications using a generalized estimating equations model with a normal distribution adjusted for age, sex, occurrence of different complications, and history of complications at baseline, 2012. Two- and threefold interactions were included in an extended model. RESULTS: The base case model estimated total costs in the quarter of event for the example of a 60- to 69-year-old man as follows: diabetic foot €1,293, amputation €14,284, retinopathy €671, blindness €2,933, nephropathy €3,353, end-stage renal disease (ESRD) €22,691, nonfatal stroke €9,769, fatal stroke €11,176, nonfatal myocardial infarction (MI)/cardiac arrest (CA) €8,035, fatal MI/CA €8,700, nonfatal ischemic heart disease (IHD) €6,548, fatal IHD €20,942, chronic heart failure €3,912, and angina pectoris €2,695. In the subsequent quarters, costs ranged from €681 for retinopathy to €6,130 for ESRD. CONCLUSIONS: Type 2 diabetes complications have a significant impact on total health care costs in the SHI system, not only in the quarter of event but also in subsequent years. Men and women from different age-groups differ in their costs for complications. Our comprehensive estimates may support the parametrization of diabetes models and help clinicians and policy makers to quantify the economic burden of diabetes complications in the context of new prevention and treatment programs.