Showing papers by "Annika Hoyer published in 2015"

Nonparametric meta‐analysis for diagnostic accuracy studies

Abstract: 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. Copyright © 2015 John Wiley & Sons, Ltd.

Years of life lost.

Abstract: Among the limitations of their study, the authors list the unavailability of German health data of sufficiently high quality (1). Indeed, the precise data sources for Germany remain largely unmentioned. The methods of the Global Burden of Disease (GBD) Study comprise the possibility to transfer data from other countries to Germany while considering national risk factors, which may lead to erroneous estimates. For this reason, in a comparison calculation we estimated the years of life lost (YLL) due to diabetes on the basis of the KORA-S4/F4 study. KORA is a population based, prospective cohort study that includes undiagnosed diabetes in addition to patients with diagnosed type 2 diabetes (2). When extrapolating the YLL which result from the KORA data for 2007 by means of an epidemiological model (3) to the age structure in Germany in 2010, the calculation shows 166 000 (95% CI 81 000–278 000) YLL due to diabetes for men and 137 000 (55 000 to 243 000) YLL for women. This tallies very well in the sex ratio as well as in the magnitude of the GBD estimates of 140 000 YLL and 110 000 YLL, respectively (1). These data and the prognoses from (3) stress the enormous individual and societal burden of diabetes in Germany

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

Abstract: 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.

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

Abstract: Estimation 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. We 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). A 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. We 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.

Projected Effect of Increased Active Travel in German Urban Regions on the Risk of Type 2 Diabetes

Abstract: Background Future transportation policy is likely to reduce emissions in the cities and urban regions by strengthening active travel. Increased walking and cycling are known to have positive effects on health outcomes. This work estimates effects of increased active travel on type 2 diabetes in Germany, where 64% of the population live in urban regions. Methods Based on the effect size of an increased active travel scenario reported from a recent meta-analysis, we project the change in the life time risk, the proportion of prevented cases and the change in diabetes free life time in a German birth cohort (born 1985) compared to business as usual. Results The absolute risk reduction of developing type 2 diabetes before the age of 80 is 6.4% [95% confidence interval: 3.7-9.7%] for men and 4.7% [2.2-7.7%] for women, respectively. Compared to business as usual, the increased active travel scenario prevents 14.0% [8.1-21.2%] of the future cases of diabetes in men and 15.8% [9.3-23.1%] in women. Diabetes free survival increases by 1.7 [1.0-2.7] years in men and 1.4 [0.6-2.3] in women. Conclusions Our projection predicts a substantial impact of increased active travel on the future burden of type 2 diabetes. The most striking effect may be seen in the number of prevented cases. In all urban regions with an increased active travel transport policy, about one out of seven male and one out of six female cases can be prevented.

SAT0415 Performance of Anti-Nuclear Antibodies (ANA) for Classifying Systemic Lupus Erythematosus (SLE): A Systematic Literature Review and Meta-Regression of Diagnostic Data

Abstract: Background EULAR and ACR have jointly funded a project to improve existing SLE classification criteria, aiming at earlier and more accurate classification of the disease. This abstract reports on an early phase of that project. ANA constitute the immunological hallmark of SLE, and ANA testing is widely used for SLE diagnosis based on its reportedly high sensitivity. Although indirect immunofluorescence on Hep-2 cells (IIF-Hep2) is considered the gold standard of ANA testing (1), the performance of different ANA titers and the possibility to include ANA as entry criterion for the classification of SLE have not been systematically evaluated. Objectives To review the published literature on the performance of IIF-Hep2 ANA testing for the classification/diagnosis of SLE. Methods A systematic literature search was conducted in MEDLINE and EMBASE for articles published between January 1990 and March 2014. The research question was structured according to PICO (Population, Intervention, Comparator, Outcome) format rules, and PRISMA recommendations were followed where appropriate. Meta-regression analysis for diagnostic tests was performed using the ANA titer as independent variable and sensitivity and specificity as dependent variables. Results A total of 3,919 publications were screened in abstract and title and 623 articles were evaluated in full-text. Of these, 60 matched the eligibility criteria and were included in the analysis. The included studies comprised 10,089 SLE patients in total, of whom 9,587 (95.0%) were reported to be ANA positive at various titers. For ANA at titers of 1:40, 1:80 and 1:160, meta-regression gave sensitivity values of 98.8% (95% confidence interval [CI] 98.0-99.3%), 98.1% (CI 97.1-98.8%) and 95.4% (CI 93.0–97.0%), respectively. The corresponding specificities were 75.1% (CI 64.3-83.5%), 83.3% (CI 74.9-89.3%) and 93.2% (CI 88.6-96.0%), respectively. Conclusions The results of this systematic literature search and meta-regression confirm the high sensitivity of a positive ANA test for SLE. While no decision has so far been made, these data suggest that ANA at a titer of 1:80 could be a reasonable entry criterion for SLE classification criteria. References Agmon-Levin et al, Ann Rheum Dis 2014; 73: 17ff Disclosure of Interest None declared

Statistical methods for the meta-analysis of full ROC curves

Abstract: Meta-analyses and systematic reviews are the cornerstones of evidence based medicine and inform treatment, diagnosis, or prevention of individual patients as well as policy decisions in health care. Statistical methods for the meta-analysis of intervention studies are well established today. Metaanalysis for diagnostic accuracy trials, however, has been a vivid research area in recent years which is especially due to the increased complexity of diagnostic studies with their bivariate outcome of sensitivity and specificity. An even more increased complexity arises when single studies do not only report a single pair of sensitivity and specificity, but a full ROC curve with several pairs of sensitivity and specificity, each pair for a different threshold. Researchers frequently ignore this information and use only one pair of sensitivity and specificity from each study to arrive at meta-analytic estimates. Although methods to deal with the full information have been proposed [15], these are not without problems, e.g., they are two-step approaches where estimation uncertainty from the first step is ignored in the second step, the number of thresholds has to be identical across studies, or the concrete values of thresholds are ignored thus making impossible clinically relevant inference on sensitivity and specificity at given thresholds. We propose two approaches for the meta-analysis of full ROC curves that use the information from all thresholds. The first approach simply expands the standard bivariate random effects model to a meta-regression model. The second approach uses the interpretation of an ROC curve as a bivariate time-to-event model for interval-censored data. This work is motivated by two systematic reviews on population-based screening for type 2 diabetes mellitus [6,7] which report on 38 single studies to assess the HbA1c as a diagnostic marker. Both reviews report only single pairs of sensitivity and specificity from each single study, but an intensified search yields 124 pairs of sensitivity and specificity for 26 different HbA1c thresholds from the 38 single studies.