Richard W Browne1, Susan L Rosenkranz2, Yan Wang2, Charlene R Taylor3, Robin DiFrancesco3, Gene D Morse3. 1. Department of Biotechnical and Clinical Laboratory Sciences, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, New York. 2. Frontier Science Technology and Research Foundation, Amherst, New York. 3. HIV Clinical Pharmacology Research Program, Translational Pharmacology Research Core, Center of Excellence in Bioinformatics and Life Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, New York.
Abstract
BACKGROUND: The Clinical Pharmacology Quality Assurance (CPQA) program provides semiannual proficiency testing (PT) of antiretroviral analytes for 11 US and international clinical pharmacology laboratories (CPLs) to ensure interlaboratory comparability. In this article, we provide estimates of the main sources of variability and assess the accuracy of the algorithm for the assessment of performance. METHODS: Descriptive statistics are reported from 13 PT rounds from 2010 to 2016. Eight of the most common antiretroviral analytes were examined. Variance components analysis was used to rank the relative contributions of CPLs, antiretroviral analyte, and concentration category (low, medium, and high) to bias and variability using mixed models. Binary classification metrics of the PT assessment algorithm are calculated in comparison with a model using 95% prediction limits around estimated regression equations. RESULTS: CPLs provided 4109 reported concentrations of 65 unique samples for each of the 8 antiretroviral analytes across 13 PT rounds. Individual CPL accounted for the greatest amount of total variability (4.4%). Individual CPL and analyte combination (interaction) accounted for the greatest amount of bias (8.1%). Analyte alone accounted for 0.5% or less for total variability and bias. Overall, using a ±20% acceptance window around the final target, 97% of individual reported concentrations were scored acceptable, and 96% of antiretroviral/round scores were deemed satisfactory. Comparison with the regression model gave 100% sensitivity but only 34.47% specificity. Narrowing the acceptance window to ±15% improved specificity to 84.47% while maintaining a 99.17% sensitivity. CONCLUSIONS: The current CPQA PT scoring algorithm that use a ±20% acceptance window seems to suffer from a low specificity and may be too lenient. A stricter ±15% acceptance window would increase specificity and overall accuracy while lowering the overall pass rate by only 3%.
BACKGROUND: The Clinical Pharmacology Quality Assurance (CPQA) program provides semiannual proficiency testing (PT) of antiretroviral analytes for 11 US and international clinical pharmacology laboratories (CPLs) to ensure interlaboratory comparability. In this article, we provide estimates of the main sources of variability and assess the accuracy of the algorithm for the assessment of performance. METHODS: Descriptive statistics are reported from 13 PT rounds from 2010 to 2016. Eight of the most common antiretroviral analytes were examined. Variance components analysis was used to rank the relative contributions of CPLs, antiretroviral analyte, and concentration category (low, medium, and high) to bias and variability using mixed models. Binary classification metrics of the PT assessment algorithm are calculated in comparison with a model using 95% prediction limits around estimated regression equations. RESULTS: CPLs provided 4109 reported concentrations of 65 unique samples for each of the 8 antiretroviral analytes across 13 PT rounds. Individual CPL accounted for the greatest amount of total variability (4.4%). Individual CPL and analyte combination (interaction) accounted for the greatest amount of bias (8.1%). Analyte alone accounted for 0.5% or less for total variability and bias. Overall, using a ±20% acceptance window around the final target, 97% of individual reported concentrations were scored acceptable, and 96% of antiretroviral/round scores were deemed satisfactory. Comparison with the regression model gave 100% sensitivity but only 34.47% specificity. Narrowing the acceptance window to ±15% improved specificity to 84.47% while maintaining a 99.17% sensitivity. CONCLUSIONS: The current CPQA PT scoring algorithm that use a ±20% acceptance window seems to suffer from a low specificity and may be too lenient. A stricter ±15% acceptance window would increase specificity and overall accuracy while lowering the overall pass rate by only 3%.
Authors: Oskar González; María Encarnación Blanco; Gorka Iriarte; Luis Bartolomé; Miren Itxaso Maguregui; Rosa M Alonso Journal: J Chromatogr A Date: 2014-04-04 Impact factor: 4.759
Authors: Robin DiFrancesco; Susan L Rosenkranz; Charlene R Taylor; Poonam G Pande; Suzanne M Siminski; Richard W Jenny; Gene D Morse Journal: Ther Drug Monit Date: 2013-10 Impact factor: 3.681
Authors: Monica Gandhi; Babafemi Taiwo; Jacinta N Nwogu; Samuel O Ngene; Chinedum P Babalola; Adeniyi Olagunju; Andrew Owen; Saye H Khoo; Olayinka A Kotila; Baiba Berzins; Hideaki Okochi; Regina Tallerico Journal: AIDS Res Ther Date: 2022-07-10 Impact factor: 2.846
Authors: Jacinta N Nwogu; Monica Gandhi; Andrew Owen; Saye H Khoo; Babafemi Taiwo; Adeniyi Olagunju; Baiba Berzins; Hideaki Okochi; Regina Tallerico; Kevin Robertson; Chinedum P Babalola Journal: AIDS Date: 2021-10-01 Impact factor: 4.632