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Derivation of level-specific reference change values (RCV) from a health screening database and optimization of their thresholds based on clinical utility

  • Reo Kawano , Kiyoshi Ichihara EMAIL logo and Takashi Wada
Published/Copyright: February 17, 2016
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Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 54 Issue 9

Abstract

Background: Reference change values (RCV) are used for judging the significance of changes between any two measurements. Based on the within-individual CV (CVI), RCV is conventionally computed as the 95% confidence limit (CL) of the changes: RCV=1.96×2CVI. However, the appropriateness of assuming a constant CVI and using the 95% CL for RCV remains controversial.

Methods:

The level-specific CVI and RCV were estimated for 20 screening tests using a database composed of results from 13,545 health-screening attendees over a 17-year period, after preliminary exclusion of individuals taking medications or having unusual changes in body mass index (BMI). A rational CL for RCV was explored in reference to a clinical score for the metabolic syndrome, sMS, which was derived based on a logistic regression model consisting of tests related to metabolic syndrome. The effect of adjusting CL for the RCV on diagnostic efficacies of detecting between-year change in sMS was evaluated.

Results:

Test level dependency of CVI was apparent for some screening tests which have distributions with prominent skewing. The use of level-specific RCV was thus essential for them. The sensitivity for detecting a critical change in sMS based on the RCV set at 95%CL was extremely low in the majority of tests. However, by lowering CL stepwise from 95 to 75%, the sensitivity improved greatly without much change in specificity and positive predictive value. Loss-and-gain analysis showed that CL for RCV set around 80% gave the lowest loss, assuming a policy of reducing false negative judgment.

Conclusions:

Level specific CVI and RCV were necessary in tests with skewed distributions. RCV using 80%–90% CL is suitable in health screening for diseases that require early intervention for changes.

Keywords: biological variation; data mining; metabolic syndrome; multiple logistic regression analysis; reference change value
Corresponding author: Kiyoshi Ichihara, MD, PhD, Faculty of Health Sciences, Department of Clinical Laboratory Sciences, Yamaguchi University Graduate School of Medicine Minami-Kogushi 1-1-1, Ube 755 8505, Japan, E-mail:

Acknowledgments

The data analyses and secretarial works required for this research were kindly supported by Mr. Keisuke Takada, Mr. Shogo Kimura, and Miss Mio Nagai, who belong to Ichihara Research Laboratory in Yamaguchi University Graduate School of Medicine. We are indebted to Prof. Myron A. Johnson of University of North Carolina for his generous support for scientific editing of this manuscript.

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

  2. Research funding: None declared.

  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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Supplemental Material:

The online version of this article (DOI: 10.1515/cclm-2015-1004) offers supplementary material, available to authorized users.

Received: 2015-10-14
Accepted: 2015-12-16
Published Online: 2016-2-17
Published in Print: 2016-9-1

©2016 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/cclm-2015-1004
Keywords for this article
biological variation; data mining; metabolic syndrome; multiple logistic regression analysis; reference change value

Articles in the same Issue

  1. Frontmatter
  2. Editorials
  3. The Theranos phenomenon, scientific transparency and freedom of speech
  4. Holotranscobalamin: in the middle of difficultly lies opportunity
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  9. Genetics and Molecular Diagnostics
  10. Hybrid minigene splicing assay verified the pathogenicity of a novel splice site variant in the dystrophin gene of a Chinese patient with typical Duchenne muscular dystrophy phenotype
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