A grey zone for quantitative diagnostic and screening tests

Most quantitative tests do not perfectly discriminate between subjects with and without a given disease and their results do not always allow certainty about disease status for diagnostic or screening purposes. We propose a method to construct a three-zone partition for quantitative tests to avoid t...

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Bibliographic Details
Published inInternational journal of epidemiology Vol. 32; no. 2; pp. 304 - 313
Main Authors Coste, Joël, Pouchot, Jacques
Format Journal Article
LanguageEnglish
Published England Oxford Publishing Limited (England) 01.04.2003
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Online AccessGet full text
ISSN0300-5771
1464-3685
DOI10.1093/ije/dyg054

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Abstract Most quantitative tests do not perfectly discriminate between subjects with and without a given disease and their results do not always allow certainty about disease status for diagnostic or screening purposes. We propose a method to construct a three-zone partition for quantitative tests to avoid the binary constraint of a 'black or white' decision that often does not fit the reality of clinical or screening practice. This partition intentionally includes a grey zone between positive and negative conclusions. We show that the width of this grey zone depends on the difference between the means of test results for subjects with and without the disease, the variability of the test results and its components (biological, measurement), and the level of the misclassification risks (false positive, false negative) required by the context of use. We illustrate the method by application to the tuberculin skin test and iron deficiency markers in children. This method can be used both to display the discriminatory performance of a quantitative test in a variety of contexts and to scrutinize its components of variability. Due to the simplicity of the graphical representations, the grey zone approach may be useful during the development of quantitative tests and the publication of their performance.
AbstractList Most quantitative tests do not perfectly discriminate between subjects with and without a given disease and their results do not always allow certainty about disease status for diagnostic or screening purposes. We propose a method to construct a three-zone partition for quantitative tests to avoid the binary constraint of a 'black or white' decision that often does not fit the reality of clinical or screening practice. This partition intentionally includes a grey zone between positive and negative conclusions.BACKGROUNDMost quantitative tests do not perfectly discriminate between subjects with and without a given disease and their results do not always allow certainty about disease status for diagnostic or screening purposes. We propose a method to construct a three-zone partition for quantitative tests to avoid the binary constraint of a 'black or white' decision that often does not fit the reality of clinical or screening practice. This partition intentionally includes a grey zone between positive and negative conclusions.We show that the width of this grey zone depends on the difference between the means of test results for subjects with and without the disease, the variability of the test results and its components (biological, measurement), and the level of the misclassification risks (false positive, false negative) required by the context of use. We illustrate the method by application to the tuberculin skin test and iron deficiency markers in children.METHODS AND RESULTSWe show that the width of this grey zone depends on the difference between the means of test results for subjects with and without the disease, the variability of the test results and its components (biological, measurement), and the level of the misclassification risks (false positive, false negative) required by the context of use. We illustrate the method by application to the tuberculin skin test and iron deficiency markers in children.This method can be used both to display the discriminatory performance of a quantitative test in a variety of contexts and to scrutinize its components of variability. Due to the simplicity of the graphical representations, the grey zone approach may be useful during the development of quantitative tests and the publication of their performance.CONCLUSIONThis method can be used both to display the discriminatory performance of a quantitative test in a variety of contexts and to scrutinize its components of variability. Due to the simplicity of the graphical representations, the grey zone approach may be useful during the development of quantitative tests and the publication of their performance.
Most quantitative tests do not perfectly discriminate between subjects with and without a given disease and their results do not always allow certainty about disease status for diagnostic or screening purposes. We propose a method to construct a three-zone partition for quantitative tests to avoid the binary constraint of a 'black or white' decision that often does not fit the reality of clinical or screening practice. This partition intentionally includes a grey zone between positive and negative conclusions. We show that the width of this grey zone depends on the difference between the means of test results for subjects with and without the disease, the variability of the test results and its components (biological, measurement), and the level of the misclassification risks (false positive, false negative) required by the context of use. We illustrate the method by application to the tuberculin skin test and iron deficiency markers in children. This method can be used both to display the discriminatory performance of a quantitative test in a variety of contexts and to scrutinize its components of variability. Due to the simplicity of the graphical representations, the grey zone approach may be useful during the development of quantitative tests and the publication of their performance.
Background Most quantitative tests do not perfectly discriminate between subjects with and without a given disease and their results do not always allow certainty about disease status for diagnostic or screening purposes. We propose a method to construct a three-zone partition for quantitative tests to avoid the binary constraint of a 'black or white' decision that often does not fit the reality of clinical or screening practice. This partition intentionally includes a grey zone between positive and negative conclusions. Methods and Results We show that the width of this grey zone depends on the difference between the means of test results for subjects with and without the disease, the variability of the test results and its components (biological, measurement), and the level of the misclassification risks (false positive, false negative) required by the context of use. We illustrate the method by application to the tuberculin skin test and iron deficiency markers in children. Conclusion This method can be used both to display the discriminatory performance of a quantitative test in a variety of contexts and to scrutinize its components of variability. Due to the simplicity of the graphical representations, the grey zone approach may be useful during the development of quantitative tests and the publication of their performance.
Author Coste, Joël
Pouchot, Jacques
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– reference: 12714555 - Int J Epidemiol. 2003 Apr;32(2):314-5
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Snippet Most quantitative tests do not perfectly discriminate between subjects with and without a given disease and their results do not always allow certainty about...
Background Most quantitative tests do not perfectly discriminate between subjects with and without a given disease and their results do not always allow...
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StartPage 304
SubjectTerms Analysis of Variance
Anemia, Iron-Deficiency - diagnosis
Diagnostic Errors
Diagnostic Techniques and Procedures - standards
Hemoglobinometry - standards
Humans
Mass Screening - standards
Observer Variation
Predictive Value of Tests
Reticulocytes - chemistry
Sensitivity and Specificity
Tuberculin Test - standards
Title A grey zone for quantitative diagnostic and screening tests
URI https://www.ncbi.nlm.nih.gov/pubmed/12714554
https://www.proquest.com/docview/219167791
https://www.proquest.com/docview/73230440
Volume 32
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