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BMC Medical Research Methodology

, 9:63

First Online: 10 September 2009Received: 31 March 2009Accepted: 10 September 2009


BackgroundEpidemiological and clinical studies, often including anthropometric measures, have established obesity as a major risk factor for the development of type 2 diabetes. Appropriate cut-off values for anthropometric parameters are necessary for prediction or decision purposes. The cut-off corresponding to the Youden-Index is often applied in epidemiology and biomedical literature for dichotomizing a continuous risk indicator.

MethodsUsing data from a representative large multistage longitudinal epidemiological study in a primary care setting in Germany, this paper explores a novel approach for estimating optimal cut-offs of anthropomorphic parameters for predicting type 2 diabetes based on a discontinuity of a regression function in a nonparametric regression framework.

ResultsThe resulting cut-off corresponded to values obtained by the Youden Index maximum of the sum of sensitivity and specificity, minus one, often considered the optimal cut-off in epidemiological and biomedical research. The nonparametric regression based estimator was compared to results obtained by the established methods of the Receiver Operating Characteristic plot in various simulation scenarios and based on bias and root mean square error, yielded excellent finite sample properties.

ConclusionIt is thus recommended that this nonparametric regression approach be considered as valuable alternative when a continuous indicator has to be dichotomized at the Youden Index for prediction or decision purposes.

Electronic supplementary materialThe online version of this article doi:10.1186-1471-2288-9-63 contains supplementary material, which is available to authorized users.

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Autor: Jens Klotsche - Dietmar Ferger - Lars Pieper - Jürgen Rehm - Hans-Ulrich Wittchen

Fuente: https://link.springer.com/

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