Supplements to a recent proposal for permissible uncertainty of measurements in laboratory medicine

Haeckel, Rainer; Wosniok, Werner; Gurr, Eberhard; Peil, Burkhard

doi:10.1515/labmed-2015-0112

Cited by 7 publications

(15 citation statements)

References 7 publications

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“…Diagnostic accuracy is fundamental to clinical decision-making (32), 2. Defining the permissible measurement uncertainty is critical to quality and risk management in laboratory medicine (33) 3. Sampling uncertainty is decisive for clinical study design to evaluate a screening or diagnostic test (34).…”

Section: Discussionmentioning

confidence: 99%

WITHDRAWN: A software tool for calculating the uncertainty of diagnostic accuracy measures

Chatzimichail¹,

Hatjimihail²

2020

Preprint

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Background: Screening and diagnostic tests are used to classify people with and without a disease. Although diagnostic accuracy measures are used to evaluate the correctness of a classification in clinical research and practice, there has been limited research on their uncertainty. The objective for this work is to develop a tool for calculating the uncertainty of diagnostic accuracy measures, as diagnostic accuracy is fundamental to clinical decision-making.Results: For this reason, a freely available interactive program has been developed in Wolfram Language. The program provides six modules with nine submodules, for calculating and plotting the standard and expanded uncertainty and the resultant confidence intervals of various diagnostic accuracy measures of screening or diagnostic tests, which measure a normally distributed measurand, applied at a single point in time in non-diseased and diseased populations. This is done for differing population sample sizes, mean and standard deviation of the measurand, diagnostic threshold and standard measurement uncertainty of the test.The application of the program is illustrated with a case study of glucose measurements in diabetic and non-diabetic populations, that demonstrates the calculation of the uncertainty of diagnostic accuracy measures.Conclusion: The presented interactive program is user-friendly and can be used as a flexible educational and research tool in medical decision making, to calculate and explore the uncertainty of diagnostic accuracy measures.

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Section: Discussionmentioning

confidence: 99%

WITHDRAWN: A software tool for calculating the uncertainty of diagnostic accuracy measures

Chatzimichail¹,

Hatjimihail²

2020

Preprint

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“…Defining the permissible measurement uncertainty is critical to quality and risk management in laboratory medicine [13].…”

Section: Introductionmentioning

confidence: 99%

A Software Tool for Calculating the Uncertainty of Diagnostic Accuracy Measures

Chatzimichail¹,

Hatjimihail²

2021

Diagnostics

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Screening and diagnostic tests are applied for the classification of people into diseased and non-diseased populations. Although diagnostic accuracy measures are used to evaluate the correctness of classification in clinical research and practice, there has been limited research on their uncertainty. The objective for this work was to develop a tool for calculating the uncertainty of diagnostic accuracy measures, as diagnostic accuracy is fundamental to clinical decision-making. For this reason, the freely available interactive program Diagnostic Uncertainty has been developed in the Wolfram language. The program provides six modules with nine submodules for calculating and plotting the standard measurement, sampling and combined uncertainty and the resultant confidence intervals of various diagnostic accuracy measures of screening or diagnostic tests, which measure a normally distributed measurand, applied at a single point in time in samples of non-diseased and diseased populations. This is done for differing sample sizes, mean and standard deviation of the measurand, diagnostic threshold and standard measurement uncertainty of the test. The application of the program is demonstrated with an illustrative example of glucose measurements in samples of diabetic and non-diabetic populations, that shows the calculation of the uncertainty of diagnostic accuracy measures. The presented interactive program is user-friendly and can be used as a flexible educational and research tool in medical decision-making, to calculate and explore the uncertainty of diagnostic accuracy measures.

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“…A working group of the German Society of Clinical Chemistry and Laboratory Medicine (DGKL) has developed a model for deriving APS based on a combination of BV and state-of-the-art, with the definition of empiric biologic variation (EBV). [26][27][28] Traditional BV studies assess intra-individual (CV I ) and inter-individual variation (CV G ) through periodically repeated measurements over a specified time period, which can be merged into combined biological variation (CV B ). Conversely, EBV is derived from limits of population-based reference intervals (pRI), which should indirectly reflect biological variability and is expressed as an empirical coefficient of variation (CV E ).…”

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confidence: 99%

“…Conversely, EBV is derived from limits of population-based reference intervals (pRI), which should indirectly reflect biological variability and is expressed as an empirical coefficient of variation (CV E ). 26,27 CV E has been proposed as a surrogate for combined biological variation (CV B ) and has a good correlation with CV B for most human measurands, despite the fact that CV E additionally contains analytical variation (CV A ). 26 CV E can be utilized to determine APS.…”

mentioning

confidence: 99%

“…29 The EBV model was further simplified, resulting in a single set of permissible limits. 26,27 These limits are expressed in percentage units as permissible analytical uncertainty (pU), permissible analytical imprecision (pCV A ), permissible bias (pB), and permissible limit for external quality assessment schemes (pU EQAS ). The present study will focus on proposals of pCV A and pU as APS and will compare them to specifications derived from expert opinion (EO) and veterinary BV studies.…”

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confidence: 99%

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Are analytical performance specifications derived from reference intervals of any use in the veterinary clinical laboratory? A preliminary study on the empirical biological variation model

Manzocchi,

van Rooyen

2024

Veterinary Clinical Pathol

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BackgroundAnalytical performance specifications (APS) are vital for method evaluation and quality control validation. However, the limited availability of biological variation (BV) data, regulatory guidelines, and expert opinion (EO) may present challenges in veterinary medicine. The empirical biological variation (EBV) approach, based on population reference intervals (pRI), has emerged as an alternative method to derive APS in human medicine.ObjectivesThis study aimed to assess the practicality and usefulness of the EBV approach in deriving performance limits for various measurands in dogs and cats.MethodsEight hematology and 13 biochemistry measurands were analyzed in dogs and cats. Estimates of combined biologic variation based on traditional biological (CVB) and EBV‐derived (CVE*) formulas were calculated and assessed for evidence of correlation. Performance limits for expanded uncertainty/total error and imprecision were compared among EO, BV, and EBV.ResultsStrong and significant correlations were found between CVB and CVE* for both dogs (r = .86, p < .00001) and cats (r = 0.95, p < .00001). The EBV‐derived APS were generally comparable to EO and BV, with a subjective criterion of 1.5% difference for imprecision and 3% for total error/expanded uncertainty.ConclusionThe EBV approach, using pRI, shows promise as a surrogate marker for biological variation and as a practical tool for determining performance limits in dogs and cats. Assuming accurate pRI generated on analyzers with stable analytical performance, this approach could offer benefits when expert recommendations or robust BV studies are lacking or yield conflicting results. Further research is needed to explore the applicability and advantages of the EBV in veterinary medicine.

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Supplements to a recent proposal for permissible uncertainty of measurements in laboratory medicine

Cited by 7 publications

References 7 publications

WITHDRAWN: A software tool for calculating the uncertainty of diagnostic accuracy measures

WITHDRAWN: A software tool for calculating the uncertainty of diagnostic accuracy measures

A Software Tool for Calculating the Uncertainty of Diagnostic Accuracy Measures

Are analytical performance specifications derived from reference intervals of any use in the veterinary clinical laboratory? A preliminary study on the empirical biological variation model

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