Reference interval studies: What is the maximum number of samples recommended?

Robert C. Hawkins, Tony Badrick

Research output: Contribution to journalArticleResearchpeer-review

4 Citations (Scopus)

Abstract

Background: Little attention has been paid to the maximum number of specimens for reference interval calculation, i.e., the number of specimens beyond which there is no further benefit in reference interval calculation. We present a model for the estimation of the maximum number of specimens for reference interval studies based on setting the 90% confidence interval of the reference limits to be equal to the analyte reporting interval. Methods: Equations describing the bounds on the upper and lower 90% confidence intervals for logarithmically transformed and untransformed data were derived and applied to determine the maximum number of specimens required to calculate a reference interval for 12 common chemistry and hematology analytes. Results: Maximum sample sizes ranged from 126 to 18,171 and depended on the standard deviation of the population, any transformation involved and on the chosen reporting interval. Conclusions: This paper demonstrates the importance of the influence of reporting interval on reference intervals. Using this technique can reduce the cost of determining a reference interval by identifying the maximum number of specimens required.

Original languageEnglish
Pages (from-to)2161-2165
Number of pages5
JournalClinical Chemistry and Laboratory Medicine
Volume51
Issue number11
DOIs
Publication statusPublished - 1 Nov 2013

Fingerprint

Confidence Intervals
Hematology
Sample Size
Costs and Cost Analysis
Population
Costs

Cite this

Hawkins, Robert C. ; Badrick, Tony. / Reference interval studies : What is the maximum number of samples recommended?. In: Clinical Chemistry and Laboratory Medicine. 2013 ; Vol. 51, No. 11. pp. 2161-2165.
@article{5c8f34725f104ce29f88750e7a54a535,
title = "Reference interval studies: What is the maximum number of samples recommended?",
abstract = "Background: Little attention has been paid to the maximum number of specimens for reference interval calculation, i.e., the number of specimens beyond which there is no further benefit in reference interval calculation. We present a model for the estimation of the maximum number of specimens for reference interval studies based on setting the 90{\%} confidence interval of the reference limits to be equal to the analyte reporting interval. Methods: Equations describing the bounds on the upper and lower 90{\%} confidence intervals for logarithmically transformed and untransformed data were derived and applied to determine the maximum number of specimens required to calculate a reference interval for 12 common chemistry and hematology analytes. Results: Maximum sample sizes ranged from 126 to 18,171 and depended on the standard deviation of the population, any transformation involved and on the chosen reporting interval. Conclusions: This paper demonstrates the importance of the influence of reporting interval on reference intervals. Using this technique can reduce the cost of determining a reference interval by identifying the maximum number of specimens required.",
author = "Hawkins, {Robert C.} and Tony Badrick",
year = "2013",
month = "11",
day = "1",
doi = "10.1515/cclm-2013-0345",
language = "English",
volume = "51",
pages = "2161--2165",
journal = "European Journal of Clinical Chemistry and Clinical Biochemistry",
issn = "1434-6621",
publisher = "WALTER DE GRUYTER & CO",
number = "11",

}

Reference interval studies : What is the maximum number of samples recommended? / Hawkins, Robert C.; Badrick, Tony.

In: Clinical Chemistry and Laboratory Medicine, Vol. 51, No. 11, 01.11.2013, p. 2161-2165.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Reference interval studies

T2 - What is the maximum number of samples recommended?

AU - Hawkins, Robert C.

AU - Badrick, Tony

PY - 2013/11/1

Y1 - 2013/11/1

N2 - Background: Little attention has been paid to the maximum number of specimens for reference interval calculation, i.e., the number of specimens beyond which there is no further benefit in reference interval calculation. We present a model for the estimation of the maximum number of specimens for reference interval studies based on setting the 90% confidence interval of the reference limits to be equal to the analyte reporting interval. Methods: Equations describing the bounds on the upper and lower 90% confidence intervals for logarithmically transformed and untransformed data were derived and applied to determine the maximum number of specimens required to calculate a reference interval for 12 common chemistry and hematology analytes. Results: Maximum sample sizes ranged from 126 to 18,171 and depended on the standard deviation of the population, any transformation involved and on the chosen reporting interval. Conclusions: This paper demonstrates the importance of the influence of reporting interval on reference intervals. Using this technique can reduce the cost of determining a reference interval by identifying the maximum number of specimens required.

AB - Background: Little attention has been paid to the maximum number of specimens for reference interval calculation, i.e., the number of specimens beyond which there is no further benefit in reference interval calculation. We present a model for the estimation of the maximum number of specimens for reference interval studies based on setting the 90% confidence interval of the reference limits to be equal to the analyte reporting interval. Methods: Equations describing the bounds on the upper and lower 90% confidence intervals for logarithmically transformed and untransformed data were derived and applied to determine the maximum number of specimens required to calculate a reference interval for 12 common chemistry and hematology analytes. Results: Maximum sample sizes ranged from 126 to 18,171 and depended on the standard deviation of the population, any transformation involved and on the chosen reporting interval. Conclusions: This paper demonstrates the importance of the influence of reporting interval on reference intervals. Using this technique can reduce the cost of determining a reference interval by identifying the maximum number of specimens required.

UR - http://www.scopus.com/inward/record.url?scp=84886704895&partnerID=8YFLogxK

U2 - 10.1515/cclm-2013-0345

DO - 10.1515/cclm-2013-0345

M3 - Article

VL - 51

SP - 2161

EP - 2165

JO - European Journal of Clinical Chemistry and Clinical Biochemistry

JF - European Journal of Clinical Chemistry and Clinical Biochemistry

SN - 1434-6621

IS - 11

ER -