Modeling conditional reference regions: application to glycemic markers
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Título: | Modeling conditional reference regions: application to glycemic markers |
Autor/a: | Lado Baleato, Óscar Roca Pardiñas, Javier Cadarso Suárez, Carmen María Gude Sampedro, Francisco |
Centro/Departamento: | Universidade de Santiago de Compostela. Departamento de Estatística, Análise Matemática e Optimización |
Palabras chave: | Conditional reference regions | Diabetes | Flexible additive predictors | Kernel smoothing | Regression | |
Data: | 2021 |
Editor: | Wiley |
Cita bibliográfica: | Statistics in Medicine. 2021;40:5926–5946. https://doi.org/10.1002/sim.9163 |
Resumo: | Many clinical decisions are taken based on the results of continuous diagnostic tests. Usually, only the results of one single test is taken into consideration, the interpretation of which requires a reference range for the healthy population. However, the use of two different tests, can be necessary in the diagnosis of certain diseases. This obliges a bivariate reference region be available for their interpretation. It should also be remembered that reference regions may depend on patient variables (eg, age and sex) independent of the suspected disease. However, few proposals have been made regarding the statistical modeling of such reference regions, and those put forward have always assumed a Gaussian distribution, which can be rather restrictive. The present work describes a new statistical method that allows such reference regions to be estimated with no insistence on the results being normally distributed. The proposed method is based on a bivariate location-scale model that provides probabilistic regions covering a specific percentage of the bivariate data, dependent on certain covariates. The reference region is estimated nonparametrically and the nonlinear effects of continuous covariates via polynomial kernel smoothers in additive models. The bivariate model is estimated using a backfitting algorithm, and the optimal smoothing parameters of the kernel smoothers selected by cross-validation. The model performed satisfactorily in simulation studies under the assumption of non-Gaussian conditions. Finally, the proposed methodology was found to be useful in estimating a reference region for two continuous diagnostic tests for diabetes (fasting plasma glucose and glycated hemoglobin), taking into account the age of the patient |
Versión do editor: | https://doi.org/10.1002/sim.9163 |
URI: | http://hdl.handle.net/10347/29093 |
DOI: | 10.1002/sim.9163 |
E-ISSN: | 1097-0258 |
Dereitos: | © 2021 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made |
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© 2021 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made
© 2021 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made