APS calculator: A data-driven tool for setting outcome-based analytical performance specifications for measurement uncertainty using specific clinical requirements and population data


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Çubukçu H. C., Vanstapel F., Thelen M., Van Schrojenstein Lantman M., Bernabeu-Andreu F. A., Meško Brguljan P., ...More

Clinical Chemistry and Laboratory Medicine, 2023 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2023
  • Doi Number: 10.1515/cclm-2023-0740
  • Journal Name: Clinical Chemistry and Laboratory Medicine
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, CAB Abstracts, Chemical Abstracts Core, EMBASE, MEDLINE
  • Keywords: analytical performance specifications, data, decision limits, ISO 15189, measurement uncertainty, outcome
  • Hacettepe University Affiliated: No

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.