TY  - JOUR
AU  - Çubukçu, Hikmet Can
AU  - Vanstapel, Florent
AU  - Thelen, Marc
AU  - Van Schrojenstein Lantman, Marith
AU  - Bernabeu-Andreu, Francisco A
AU  - Meško Brguljan, Pika
AU  - Milinković, Neda
AU  - Linko, Solveig
AU  - Panteghini, Mauro
AU  - Boursier, Guilaine
PY  - 2023
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/5345
AB  - According to ISO 15189:2022, analytical performance specifications (APS) should relate to intended clinical use and impact on patient care. Therefore, we aimed to develop a web application for laboratory professionals to calculate APS based on a simulation of the impact of measurement uncertainty (MU) on the outcome using the chosen decision limits, agreement thresholds, and data of the population of interest. We developed the "APS Calculator"allowing users to upload and select data of concern, specify decision limits and agreement thresholds, and conduct simulations to determine APS for MU. The simulation involved categorizing original measurand concentrations, generating measured (simulated) results by introducing different degrees of MU, and recategorizing measured concentrations based on clinical decision limits and acceptable clinical misclassification rates. The agreements between original and simulated result categories were assessed, and values that met or exceeded user-specified agreement thresholds that set goals for the between-category agreement were considered acceptable. The application generates contour plots of agreement rates and corresponding MU values. We tested the application using National Health and Nutrition Examination Survey data, with decision limits from relevant guidelines. We determined APS for MU of six measurands (blood total hemoglobin, plasma fasting glucose, serum total and high-density lipoprotein cholesterol, triglycerides, and total folate) to demonstrate the potential of the application to generate APS. The developed data-driven web application offers a flexible tool for laboratory professionals to calculate APS for MU using their chosen decision limits and agreement thresholds, and the data of the population of interest.
PB  - Walter de Gruyter GmbH
T2  - Clinical Chemistry and Laboratory Medicine
T1  - APS calculator: A data-driven tool for setting outcome-based analytical performance specifications for measurement uncertainty using specific clinical requirements and population data
DO  - 10.1515/cclm-2023-0740
ER  - 

@article{
author = "Çubukçu, Hikmet Can and Vanstapel, Florent and Thelen, Marc and Van Schrojenstein Lantman, Marith and Bernabeu-Andreu, Francisco A and Meško Brguljan, Pika and Milinković, Neda and Linko, Solveig and Panteghini, Mauro and Boursier, Guilaine",
year = "2023",
abstract = "According to ISO 15189:2022, analytical performance specifications (APS) should relate to intended clinical use and impact on patient care. Therefore, we aimed to develop a web application for laboratory professionals to calculate APS based on a simulation of the impact of measurement uncertainty (MU) on the outcome using the chosen decision limits, agreement thresholds, and data of the population of interest. We developed the "APS Calculator"allowing users to upload and select data of concern, specify decision limits and agreement thresholds, and conduct simulations to determine APS for MU. The simulation involved categorizing original measurand concentrations, generating measured (simulated) results by introducing different degrees of MU, and recategorizing measured concentrations based on clinical decision limits and acceptable clinical misclassification rates. The agreements between original and simulated result categories were assessed, and values that met or exceeded user-specified agreement thresholds that set goals for the between-category agreement were considered acceptable. The application generates contour plots of agreement rates and corresponding MU values. We tested the application using National Health and Nutrition Examination Survey data, with decision limits from relevant guidelines. We determined APS for MU of six measurands (blood total hemoglobin, plasma fasting glucose, serum total and high-density lipoprotein cholesterol, triglycerides, and total folate) to demonstrate the potential of the application to generate APS. The developed data-driven web application offers a flexible tool for laboratory professionals to calculate APS for MU using their chosen decision limits and agreement thresholds, and the data of the population of interest.",
publisher = "Walter de Gruyter GmbH",
journal = "Clinical Chemistry and Laboratory Medicine",
title = "APS calculator: A data-driven tool for setting outcome-based analytical performance specifications for measurement uncertainty using specific clinical requirements and population data",
doi = "10.1515/cclm-2023-0740"
}

Çubukçu, H. C., Vanstapel, F., Thelen, M., Van Schrojenstein Lantman, M., Bernabeu-Andreu, F. A., Meško Brguljan, P., Milinković, N., Linko, S., Panteghini, M.,& Boursier, G.. (2023). APS calculator: A data-driven tool for setting outcome-based analytical performance specifications for measurement uncertainty using specific clinical requirements and population data. in Clinical Chemistry and Laboratory Medicine
Walter de Gruyter GmbH..
https://doi.org/10.1515/cclm-2023-0740

Çubukçu HC, Vanstapel F, Thelen M, Van Schrojenstein Lantman M, Bernabeu-Andreu FA, Meško Brguljan P, Milinković N, Linko S, Panteghini M, Boursier G. APS calculator: A data-driven tool for setting outcome-based analytical performance specifications for measurement uncertainty using specific clinical requirements and population data. in Clinical Chemistry and Laboratory Medicine. 2023;.
doi:10.1515/cclm-2023-0740 .

Çubukçu, Hikmet Can, Vanstapel, Florent, Thelen, Marc, Van Schrojenstein Lantman, Marith, Bernabeu-Andreu, Francisco A, Meško Brguljan, Pika, Milinković, Neda, Linko, Solveig, Panteghini, Mauro, Boursier, Guilaine, "APS calculator: A data-driven tool for setting outcome-based analytical performance specifications for measurement uncertainty using specific clinical requirements and population data" in Clinical Chemistry and Laboratory Medicine (2023),
https://doi.org/10.1515/cclm-2023-0740 . .