Annika Hoyer

The Prevalence and Incidence of Diabetes in Germany: An Analysis of Statutory Health Insurance Data on 65 Million Individuals From the Years 2009 and 2010

BACKGROUND The database of the German Institute of Medical Documentation and Information makes it possible for the first time to compute statistics on diabetes for all insurees of the statutory health insurance scheme in Germany. Data from this comprehensive source are less likely to be biased by differences in the membership structures of individual insurance carriers or by the underrepresentation of persons over age 80 that is seen in most population-based studies. METHODS International Classification of Diseases (ICD)-coded diagnosis data from the inpatient and outpatient sectors were used to define persons as having diabetes. Incidences were estimated from differences in prevalence from one year to the next and the expected mortality of persons with and without diabetes. RESULTS A diabetes diagnosis was present in 6.4 million out of a total of 65.6 million insurees in 2009 and in 6.7 million out of 64.9 million insures in 2010. The corresponding age and sex standardized prevalences of diabetes were 9.7% in 2009 and 9.9% in 2010, respectively. The number of persons with type 2 diabetes was 4.6 million in 2009 and 4.7 million in 2010. The prevalence and incidence of type 2 diabetes rose steeply from age 50 to age 80. Peak incidence was at age 85, with 24 newly diagnosed cases of diabetes per 1000 person-years. CONCLUSION On the basis of these data, we estimate that 5.8 million persons with type 2 diabetes are living in Germany today. The database used in this study is a valuable complement to population-based studies for monitoring the prevalence of diabetes, particularly in persons over age 80.

Prävalenz und Inzidenz von Diabetes mellitus in Deutschland

BACKGROUND The database of the German Institute of Medical Documentation and Information makes it possible for the first time to compute statistics on diabetes for all insurees of the statutory health insurance scheme in Germany. Data from this comprehensive source are less likely to be biased by differences in the membership structures of individual insurance carriers or by the underrepresentation of persons over age 80 that is seen in most population-based studies. METHODS International Classification of Diseases (ICD)-coded diagnosis data from the inpatient and outpatient sectors were used to define persons as having diabetes. Incidences were estimated from differences in prevalence from one year to the next and the expected mortality of persons with and without diabetes. RESULTS A diabetes diagnosis was present in 6.4 million out of a total of 65.6 million insurees in 2009 and in 6.7 million out of 64.9 million insures in 2010. The corresponding age and sex standardized prevalences of diabetes were 9.7% in 2009 and 9.9% in 2010, respectively. The number of persons with type 2 diabetes was 4.6 million in 2009 and 4.7 million in 2010. The prevalence and incidence of type 2 diabetes rose steeply from age 50 to age 80. Peak incidence was at age 85, with 24 newly diagnosed cases of diabetes per 1000 person-years. CONCLUSION On the basis of these data, we estimate that 5.8 million persons with type 2 diabetes are living in Germany today. The database used in this study is a valuable complement to population-based studies for monitoring the prevalence of diabetes, particularly in persons over age 80.

Burden of Mortality Attributable to Diagnosed Diabetes: A Nationwide Analysis Based on Claims Data From 65 Million People in Germany

OBJECTIVE In Germany, as in many other countries, nationwide data on mortality attributable to diagnosed diabetes are not available. This study estimated the absolute number of excess deaths associated with diabetes (all types) and type 2 diabetes in Germany. RESEARCH DESIGN AND METHODS A prevalence approach that included nationwide routine data from 64.9 million people insured in the German statutory health insurance system in 2010 was used for the calculation. Because nationwide data on diabetes mortality are lacking in Germany, the mortality rate ratio from the Danish National Diabetes Register was used. The absolute number of excess deaths associated with diabetes was calculated as the number of deaths due to diabetes minus the number of deaths due to diabetes with a mortality that was as high as in the population without diabetes. Furthermore, the mortality population-attributable fraction was calculated. RESULTS A total of 174,627 excess deaths were due to diabetes in 2010, including 137,950 due to type 2 diabetes. Overall, 21% of all deaths in Germany were attributable to diabetes and 16% were attributable to type 2 diabetes. Most of the excess deaths (34% each) occurred in the 70- to 89-year-old age-group. CONCLUSIONS In this first nationwide calculation of excess deaths related to diabetes in Germany, the results suggest that the official German estimates that rely on information from death certificates are grossly underestimated. Countries without national cohorts or diabetes registries could easily use this method to estimate the number of excess deaths due to diabetes.

Healthcare costs of Type 2 diabetes in Germany

To describe for the first time the direct costs of Type 2 diabetes treatment by analysing nationwide routine data from statutory health insurance in Germany.

Development and demonstration of a state model for the estimation of incidence of partly undetected chronic diseases.

BackgroundEstimation of incidence of the state of undiagnosed chronic disease provides a crucial missing link for the monitoring of chronic disease epidemics and determining the degree to which changes in prevalence are affected or biased by detection.MethodsWe developed a four-part compartment model for undiagnosed cases of irreversible chronic diseases with a preclinical state that precedes the diagnosis. Applicability of the model is tested in a simulation study of a hypothetical chronic disease and using diabetes data from the Health and Retirement Study (HRS).ResultsA two dimensional system of partial differential equations forms the basis for estimating incidence of the undiagnosed and diagnosed disease states from the prevalence of the associated states. In the simulation study we reach very good agreement between the estimates and the true values. Application to the HRS data demonstrates practical relevance of the methods.DiscussionWe have demonstrated the applicability of the modeling framework in a simulation study and in the analysis of the Health and Retirement Study. The model provides insight into the epidemiology of undiagnosed chronic diseases.

Performance of Antinuclear Antibodies for Classifying Systemic Lupus Erythematosus: A Systematic Literature Review and Meta-Regression of Diagnostic Data

To review the published literature on the performance of indirect immunofluorescence (IIF)–HEp‐2 antinuclear antibody (ANA) testing for classification of systemic lupus erythematosus (SLE).

Nonparametric meta‐analysis for diagnostic accuracy studies

Summarizing the information of many studies using a meta-analysis becomes more and more important, also in the field of diagnostic studies. The special challenge in meta-analysis of diagnostic accuracy studies is that in general sensitivity and specificity are co-primary endpoints. Across the studies both endpoints are correlated, and this correlation has to be considered in the analysis. The standard approach for such a meta-analysis is the bivariate logistic random effects model. An alternative approach is to use marginal beta-binomial distributions for the true positives and the true negatives, linked by copula distributions. In this article, we propose a new, nonparametric approach of analysis, which has greater flexibility with respect to the correlation structure, and always converges. In a simulation study, it becomes apparent that the empirical coverage of all three approaches is in general below the nominal level. Regarding bias, empirical coverage, and mean squared error the nonparametric model is often superior to the standard model, and comparable with the copula model. The three approaches are also applied to two example meta-analyses.

Meta-analysis of diagnostic tests accounting for disease prevalence: a new model using trivariate copulas

In real life and somewhat contrary to biostatistical textbook knowledge, sensitivity and specificity (and not only predictive values) of diagnostic tests can vary with the underlying prevalence of disease. In meta-analysis of diagnostic studies, accounting for this fact naturally leads to a trivariate expansion of the traditional bivariate logistic regression model with random study effects. In this paper, a new model is proposed using trivariate copulas and beta-binomial marginal distributions for sensitivity, specificity, and prevalence as an expansion of the bivariate model. Two different copulas are used, the trivariate Gaussian copula and a trivariate vine copula based on the bivariate Plackett copula. This model has a closed-form likelihood, so standard software (e.g., SAS PROC NLMIXED) can be used. The results of a simulation study have shown that the copula models perform at least as good but frequently better than the standard model. The methods are illustrated by two examples.

Meta-analysis for the comparison of two diagnostic tests to a common gold standard: A generalized linear mixed model approach

Meta-analysis of diagnostic studies is still a rapidly developing area of biostatistical research. Especially, there is an increasing interest in methods to compare different diagnostic tests to a common gold standard. Restricting to the case of two diagnostic tests, in these meta-analyses the parameters of interest are the differences of sensitivities and specificities (with their corresponding confidence intervals) between the two diagnostic tests while accounting for the various associations across single studies and between the two tests. We propose statistical models with a quadrivariate response (where sensitivity of test 1, specificity of test 1, sensitivity of test 2, and specificity of test 2 are the four responses) as a sensible approach to this task. Using a quadrivariate generalized linear mixed model naturally generalizes the common standard bivariate model of meta-analysis for a single diagnostic test. If information on several thresholds of the tests is available, the quadrivariate model can be further generalized to yield a comparison of full receiver operating characteristic (ROC) curves. We illustrate our model by an example where two screening methods for the diagnosis of type 2 diabetes are compared.

Age-specific and sex-specific incidence of systemic lupus erythematosus: an estimate from cross-sectional claims data of 2.3 million people in the German statutory health insurance 2002

Objective To provide an estimate of age-specific incidence rate of physician-diagnosed systemic lupus erythematosus (SLE) for German men and women. Methods The age-specific and sex-specific prevalence of diagnosed SLE in claims data is used to estimate the incidence in the German male and female population. The claims data set stems from a representative sample of the statutory health insurance in 2002 and comprises 2.3 million people. The statutory health insurance covers >85% of the German population. Results The estimated incidence rates are 0.9 (95% CI 0.7 to 1.1) per 100 000 person-years for men and 1.9 (95% CI 1.7 to 2.2) per 100 000 person-years for women. The age-specific incidence rate of SLE in the male population has a maximum of 2.2 (95% CI 1.0 to 3.4) per 100 000 person-years at the age of 65–70 years. In women, the incidence is peaking at the rate of 3.6 (95% CI 2.9 to 4.3) cases per 100 000 person-years at the age of 20–25 years, but has a second local maximum (2.6, 95% CI 1.5 to 3.8) at menopausal age. Conclusions For the first time, representative data on the incidence of SLE in Germany are provided. The estimated incidence rates of SLE for men and women in Germany are at the lower end of other estimates from comparable European countries.