Thomas Røraas1, Bård Støve2, Per Hyltoft Petersen3, Sverre Sandberg4. 1. Norwegian Quality Improvement of Primary Care Laboratories, Haraldsplass Deaconess Hospital, Bergen, Norway; Department of Global Public Health and Primary Care, University of Bergen, Norway, and thomas.roraas@noklus.no. 2. Department of Mathematics, University of Bergen, Norway; 3. Norwegian Quality Improvement of Primary Care Laboratories, Haraldsplass Deaconess Hospital, Bergen, Norway; 4. Norwegian Quality Improvement of Primary Care Laboratories, Haraldsplass Deaconess Hospital, Bergen, Norway; Department of Global Public Health and Primary Care, University of Bergen, Norway, and Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway.
Abstract
BACKGROUND: Good estimates of within-person biological variation, CVI, are essential for diagnosing and monitoring patients and for setting analytical performance specifications. The aim of the present study was to use computer simulations to evaluate the impact of various measurement distributions on different methods for estimating CVI and reference change value (RCV). METHOD: Data were simulated on the basis of 3 models for distributions of the within-person effect. We evaluated 3 different methods for estimating CVI: standard ANOVA, ln-ANOVA, and CV-ANOVA, and 3 different methods for calculating RCV: classic, ln-RCV, and a nonparametric method. We estimated CVI and RCV with the different methods and compared the results with the true values. RESULTS: The performance of the methods varied, depending on both the size of the CVI and the type of distributions. The CV-ANOVA model performed well for the estimation of CVI with all simulated data. The ln-RCV method performed best if data were ln-normal distributed or CVI was less than approximately 12%. The nonparametric RCV method performed well for all simulated data but was less precise. CONCLUSIONS: The CV-ANOVA model is recommended for both calculation of CVI and the step-by-step approach of checking for outliers and homogeneity in replicates and samples. The standard method for calculation of RCV should not be used when using CVs.
BACKGROUND: Good estimates of within-person biological variation, CVI, are essential for diagnosing and monitoring patients and for setting analytical performance specifications. The aim of the present study was to use computer simulations to evaluate the impact of various measurement distributions on different methods for estimating CVI and reference change value (RCV). METHOD: Data were simulated on the basis of 3 models for distributions of the within-person effect. We evaluated 3 different methods for estimating CVI: standard ANOVA, ln-ANOVA, and CV-ANOVA, and 3 different methods for calculating RCV: classic, ln-RCV, and a nonparametric method. We estimated CVI and RCV with the different methods and compared the results with the true values. RESULTS: The performance of the methods varied, depending on both the size of the CVI and the type of distributions. The CV-ANOVA model performed well for the estimation of CVI with all simulated data. The ln-RCV method performed best if data were ln-normal distributed or CVI was less than approximately 12%. The nonparametric RCV method performed well for all simulated data but was less precise. CONCLUSIONS: The CV-ANOVA model is recommended for both calculation of CVI and the step-by-step approach of checking for outliers and homogeneity in replicates and samples. The standard method for calculation of RCV should not be used when using CVs.
Authors: Emma M Strage; Charles J Ley; Johannes Forkman; Malin Öhlund; Sarah Stadig; Anna Bergh; Cecilia Ley Journal: BMC Vet Res Date: 2021-01-18 Impact factor: 2.741
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