A dynamic reference change value model applied to ongoing assessment of the steady state of a biomarker using more than two serial results

Flemming Lund, Per Hyltoft Petersen, Callum G. Fraser

Research output: Contribution to journalArticle

Abstract

Background: Reference change values are used to assess the significance of a difference in two consecutive results from an individual. Reference change value calculations provide the limits for significant differences between two results due to analytical and inherent biological variations. Often more than two serial results are available. Using the reference change value concept on more than two measurements results in an increased number of false-positive results. This problem has been solved for both uni- and bidirectional differences through use of wider limits when additional results are included.

Methods: Based on normally (Gaussianly) distributed simulated data, a dynamic reference change value model was developed using more than two results and total coefficients of variation. The dynamic reference change value model includes validation of a set-point as the mean of the four first serial results and additional results are assessed for compliance to the steady state with the same set-point. Furthermore, the dynamic reference change value model compensates for increasing false-positive results with subsequent results. The dynamic reference change value model was designed to calculate significant limits for bidirectional differences.

Results: Reference change factors were calculated for multiplication of the mean of previous results to create the limits for significant differences. The reference change factors are provided as a function of number of results and total coefficients of variation both in tables and in figures.

Conclusions: The dynamic reference change value model is appropriate for ongoing assessment of the steady state of a biomarker using more than two serial results.

Original languageEnglish
Pages (from-to)283-294
Number of pages12
JournalAnnals of Clinical Biochemistry
Volume56
Issue number2
Early online date25 Feb 2019
DOIs
Publication statusPublished - 25 Feb 2019

Fingerprint

Biomarkers
Reference Values

Keywords

  • Assessment of steady state
  • assessment of homeostatic set-point
  • false-positive results
  • monitoring
  • normal (Gaussian) distribution
  • reference change value
  • several serial results

Cite this

@article{433e10d1ade04305855ad90abdb5c8c7,
title = "A dynamic reference change value model applied to ongoing assessment of the steady state of a biomarker using more than two serial results",
abstract = "Background: Reference change values are used to assess the significance of a difference in two consecutive results from an individual. Reference change value calculations provide the limits for significant differences between two results due to analytical and inherent biological variations. Often more than two serial results are available. Using the reference change value concept on more than two measurements results in an increased number of false-positive results. This problem has been solved for both uni- and bidirectional differences through use of wider limits when additional results are included.Methods: Based on normally (Gaussianly) distributed simulated data, a dynamic reference change value model was developed using more than two results and total coefficients of variation. The dynamic reference change value model includes validation of a set-point as the mean of the four first serial results and additional results are assessed for compliance to the steady state with the same set-point. Furthermore, the dynamic reference change value model compensates for increasing false-positive results with subsequent results. The dynamic reference change value model was designed to calculate significant limits for bidirectional differences.Results: Reference change factors were calculated for multiplication of the mean of previous results to create the limits for significant differences. The reference change factors are provided as a function of number of results and total coefficients of variation both in tables and in figures.Conclusions: The dynamic reference change value model is appropriate for ongoing assessment of the steady state of a biomarker using more than two serial results.",
keywords = "Assessment of steady state, assessment of homeostatic set-point, false-positive results, monitoring, normal (Gaussian) distribution, reference change value, several serial results",
author = "Flemming Lund and {Hyltoft Petersen}, Per and Fraser, {Callum G.}",
year = "2019",
month = "2",
day = "25",
doi = "10.1177/0004563219826168",
language = "English",
volume = "56",
pages = "283--294",
journal = "Annals of Clinical Biochemistry",
issn = "0004-5632",
publisher = "SAGE Publications",
number = "2",

}

A dynamic reference change value model applied to ongoing assessment of the steady state of a biomarker using more than two serial results. / Lund, Flemming; Hyltoft Petersen, Per; Fraser, Callum G.

In: Annals of Clinical Biochemistry, Vol. 56, No. 2, 25.02.2019, p. 283-294.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A dynamic reference change value model applied to ongoing assessment of the steady state of a biomarker using more than two serial results

AU - Lund, Flemming

AU - Hyltoft Petersen, Per

AU - Fraser, Callum G.

PY - 2019/2/25

Y1 - 2019/2/25

N2 - Background: Reference change values are used to assess the significance of a difference in two consecutive results from an individual. Reference change value calculations provide the limits for significant differences between two results due to analytical and inherent biological variations. Often more than two serial results are available. Using the reference change value concept on more than two measurements results in an increased number of false-positive results. This problem has been solved for both uni- and bidirectional differences through use of wider limits when additional results are included.Methods: Based on normally (Gaussianly) distributed simulated data, a dynamic reference change value model was developed using more than two results and total coefficients of variation. The dynamic reference change value model includes validation of a set-point as the mean of the four first serial results and additional results are assessed for compliance to the steady state with the same set-point. Furthermore, the dynamic reference change value model compensates for increasing false-positive results with subsequent results. The dynamic reference change value model was designed to calculate significant limits for bidirectional differences.Results: Reference change factors were calculated for multiplication of the mean of previous results to create the limits for significant differences. The reference change factors are provided as a function of number of results and total coefficients of variation both in tables and in figures.Conclusions: The dynamic reference change value model is appropriate for ongoing assessment of the steady state of a biomarker using more than two serial results.

AB - Background: Reference change values are used to assess the significance of a difference in two consecutive results from an individual. Reference change value calculations provide the limits for significant differences between two results due to analytical and inherent biological variations. Often more than two serial results are available. Using the reference change value concept on more than two measurements results in an increased number of false-positive results. This problem has been solved for both uni- and bidirectional differences through use of wider limits when additional results are included.Methods: Based on normally (Gaussianly) distributed simulated data, a dynamic reference change value model was developed using more than two results and total coefficients of variation. The dynamic reference change value model includes validation of a set-point as the mean of the four first serial results and additional results are assessed for compliance to the steady state with the same set-point. Furthermore, the dynamic reference change value model compensates for increasing false-positive results with subsequent results. The dynamic reference change value model was designed to calculate significant limits for bidirectional differences.Results: Reference change factors were calculated for multiplication of the mean of previous results to create the limits for significant differences. The reference change factors are provided as a function of number of results and total coefficients of variation both in tables and in figures.Conclusions: The dynamic reference change value model is appropriate for ongoing assessment of the steady state of a biomarker using more than two serial results.

KW - Assessment of steady state

KW - assessment of homeostatic set-point

KW - false-positive results

KW - monitoring

KW - normal (Gaussian) distribution

KW - reference change value

KW - several serial results

U2 - 10.1177/0004563219826168

DO - 10.1177/0004563219826168

M3 - Article

VL - 56

SP - 283

EP - 294

JO - Annals of Clinical Biochemistry

JF - Annals of Clinical Biochemistry

SN - 0004-5632

IS - 2

ER -