Jun Xia1,2, Su-Feng Chen1,2, Fei Xu1,2, Yong-Lie Zhou1,2. 1. Clinical Laboratory Center of Zhejiang Provincial People's Hospital, Hangzhou, China. 2. People's Hospital of Hangzhou Medical college, Hangzhou, China.
Abstract
INTRODUCTION: Sigma metrics were applied to evaluate the performance of 20 routine chemistry assays, and individual quality control criteria were established based on the sigma values of different assays. METHODS: Precisions were expressed as the average coefficient variations (CVs) of long-term two-level chemistry controls. The biases of the 20 assays were obtained from the results of trueness programs organized by National Center for Clinical Laboratories (NCCL, China) in 2016. Four different allowable total error (TEa) targets were chosen from biological variation (minimum, desirable, optimal), Clinical Laboratory Improvements Amendments (CLIA, US), Analytical Quality Specification for Routine Analytes in Clinical Chemistry (WS/T 403-2012, China) and the National Cholesterol Education Program (NECP). RESULTS: The sigma values from different TEa targets varied. The TEa targets for ALT, AMY, Ca, CHOL, CK, Crea, GGT, K, LDH, Mg, Na, TG, TP, UA and Urea were chosen from WS/T 403-2012; the targets for ALP, AST and GLU were chosen from CLIA; the target for K was chosen from desirable biological variation; and the targets for HDL and LDL were chosen from the NECP. Individual quality criteria were established based on different sigma values. CONCLUSIONS: Sigma metrics are an optimal tool to evaluate the performance of different assays. An assay with a high value could use a simple internal quality control rule, while an assay with a low value should be monitored strictly.
INTRODUCTION: Sigma metrics were applied to evaluate the performance of 20 routine chemistry assays, and individual quality control criteria were established based on the sigma values of different assays. METHODS: Precisions were expressed as the average coefficient variations (CVs) of long-term two-level chemistry controls. The biases of the 20 assays were obtained from the results of trueness programs organized by National Center for Clinical Laboratories (NCCL, China) in 2016. Four different allowable total error (TEa) targets were chosen from biological variation (minimum, desirable, optimal), Clinical Laboratory Improvements Amendments (CLIA, US), Analytical Quality Specification for Routine Analytes in Clinical Chemistry (WS/T 403-2012, China) and the National Cholesterol Education Program (NECP). RESULTS: The sigma values from different TEa targets varied. The TEa targets for ALT, AMY, Ca, CHOL, CK, Crea, GGT, K, LDH, Mg, Na, TG, TP, UA and Urea were chosen from WS/T 403-2012; the targets for ALP, AST and GLU were chosen from CLIA; the target for K was chosen from desirable biological variation; and the targets for HDL and LDL were chosen from the NECP. Individual quality criteria were established based on different sigma values. CONCLUSIONS: Sigma metrics are an optimal tool to evaluate the performance of different assays. An assay with a high value could use a simple internal quality control rule, while an assay with a low value should be monitored strictly.
Authors: Sverre Sandberg; Callum G Fraser; Andrea Rita Horvath; Rob Jansen; Graham Jones; Wytze Oosterhuis; Per Hyltoft Petersen; Heinz Schimmel; Ken Sikaris; Mauro Panteghini Journal: Clin Chem Lab Med Date: 2015-05 Impact factor: 3.694
Authors: Justice Afrifa; Seth A Gyekye; William K B A Owiredu; Richard K D Ephraim; Samuel Essien-Baidoo; Samuel Amoah; David L Simpong; Aaron R Arthur Journal: Niger Med J Date: 2015 Jan-Feb