Comparative analysis of allowable total error specifications for coagulation factor assays utilizing China National External quality assessment scheme data and biological variation data.
Chengshan Xu, Zhongli Du, Gaofeng Hu, Yating Ma, Chenbin Li
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引用次数: 0
Abstract
Background: It is necessary and challenging to establish reasonable and feasible total error specifications for coagulation factor assays for quality control and assessment. The aim of this study is to establish new total error specifications for coagulation factor assays by combining External Quality Assessment data with reliable biological variation data.
Methods: Data from China National External Quality Assessment Scheme (28,408 results from 1,381 laboratories) were analyzed, stratifying External Quality Assessment data by reference intervals to establish concentration-dependent total error specifications. A "state-of-the-art" total error was defined at 80% best results of the participants. Then these specifications were compared with biological variation-derived total error to determine recommended total error specifications for different concentration levels.
Results: None of the measurands could meet biological variation-derived optimum total error. Eight parameters (FII, FVIII, FX at both high and low levels; FVII and FIX at high level) reached the desirable criteria. Only FXI at low level can't met the minimum criteria.
Conclusions: The establishment of total error specifications for coagulation factor assays should be set separately according to different concentration levels and attainability of current testing technologies. Setting total error specifications should also consider clinical requirements and regulatory standards across different regions. Analyte concentration significantly influences laboratory performance, particularly for low-concentration coagulation factors. Total error specifications need updated periodically in the further.
Abbreviations: Tea, allowable total error; BV, biological variation; SOTA, state of the art; EQAS, External quality assessment schemes; ME, measurement error; RIs, reference intervals; BIVAC, Biological Variation Data Critical Appraisal Checklist; QIs, quality items; EFLM, European Federation of Clinical Chemistry and Laboratory Medicine; APS, analytical quality specifications; ISO, International Organization for Standardization; EQA, External quality assessment; PT, proficiency testing; RCPA, Royal College of Pathologists of Australasia; RfB, Reference Institute for Bioanalytics; ECAT, External Quality Control for Assays and Tests.
期刊介绍:
The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC)
Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells.
The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.