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A combined approach to generate laboratory reference intervals using unbalanced longitudinal data

  • Mandy Vogel EMAIL logo , Toralf Kirsten , Jürgen Kratzsch , Christoph Engel and Wieland Kiess
Published/Copyright: June 6, 2017

Abstract

Background:

The interpretation of individual laboratory test results requires the availability of population-based reference intervals. In children, reference interval estimation has to consider frequently the strong age-dependency. Generally, for the construction of reference intervals, a sufficiently large number of independent measurement values is required. Data selections from hospitals or cohort studies often comprise dependencies violating the independence assumption.

Methods:

In this article, we propose a combination of LMS-like (mean, M; coefficient of variation, S; skewness, λ or L) and resampling methods to overcome this drawback. The former is recommended by the World Health Organization (WHO) for the construction of continuous reference intervals of anthropometric measurements in children. The approach allows the inclusion of dependent measurements, for example, repeated measurements per subject. It also provides pointwise confidence envelopes as a measure of reliability.

Results and conclusions:

The combination of LMS-type methods and resampling provides a feasible approach to estimate age-dependent percentiles and reference intervals using unbalanced longitudinal data.

Acknowledgments

We would like to thank David Petroff for his valuable comments during the writing process.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This publication is supported by the Leipzig Research Center for Civilization Diseases, University of Leipzig. LIFE is funded by means of the European Union, the European Regional Development Fund (ERDF), (Grant/Award Number: ‘LIFE-013: 100232872/713-3000634982’) and the Free State of Saxony within the framework of the excellence initiative.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

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Received: 2017-4-26
Accepted: 2017-4-26
Published Online: 2017-6-6
Published in Print: 2017-7-26

©2017 Walter de Gruyter GmbH, Berlin/Boston

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