The informative error: A framework for the construction of individualized phenotypes.

For the goal of individualized medicine, it is critical to have clinical phenotypes at hand which represent the individual pathophysiology. However, for most of the utilized phenotypes, two individuals with the same phenotype assignment may differ strongly in their underlying biological traits. In t...

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Publicado en:Statistical Methods in Medical Research Vol. 28; no. 5; pp. 1427 - 1439
Autores principales: Hertel, Johannes, Frenzel, Stefan, König, Johanna, Wittfeld, Katharina, Fuellen, Georg, Holtfreter, Birte, Pietzner, Maik, Friedrich, Nele, Nauck, Matthias, Völzke, Henry, Kocher, Thomas, Grabe, Hans J
Formato: research Journal Article
Publicado: Sage Publications Inc. May2019
Acceso en línea:Ver este registro en EBSCOhost
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        atl: The informative error: A framework for the construction of individualized phenotypes.
      aug:
        au:
          Hertel, Johannes
          Frenzel, Stefan
          König, Johanna
          Wittfeld, Katharina
          Fuellen, Georg
          Holtfreter, Birte
          Pietzner, Maik
          Friedrich, Nele
          Nauck, Matthias
          Völzke, Henry
          Kocher, Thomas
          Grabe, Hans J
        affil: Department of Psychiatry and Psychotherapy, 60634 -->University Medicine Greifswald, --> Germany
      sug:
        subj:
          Obesity Epidemiology
          Epidemiological Research
          Models, Statistical
          Phenotype
          Study Design
          Germany
          Human
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Scales
      ab: For the goal of individualized medicine, it is critical to have clinical phenotypes at hand which represent the individual pathophysiology. However, for most of the utilized phenotypes, two individuals with the same phenotype assignment may differ strongly in their underlying biological traits. In this paper, we propose a definition for individualization and a corresponding statistical operationalization, delivering thereby a statistical framework in which the usefulness of a variable in the meaningful differentiation of individuals with the same phenotype can be assessed. Based on this framework, we develop a statistical workflow to derive individualized phenotypes, demonstrating that under specific statistical constraints the prediction error of prediction scores contains information about hidden biological traits not represented in the modeled phenotype of interest, allowing thereby internal differentiation of individuals with the same assigned phenotypic manifestation. We applied our procedure to data of the population-based Study of Health in Pomerania to construct a refined definition of obesity, demonstrating the utility of the definition in prospective survival analyses. Summarizing, we propose a framework for the individualization of phenotypes aiding personalized medicine by shifting the focus in the assessment of prediction models from the model fit to the informational content of the prediction error.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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