Supplements to a recent proposal for permissible uncertainty of measurements in laboratory medicine

2016 ◽  
Vol 40 (2) ◽  
Author(s):  
Rainer Haeckel ◽  
Werner Wosniok ◽  
Eberhard Gurr ◽  
Burkhard Peil

Abstract:The DGKL Working Group Guide Limits (Arbeitsgruppe Richtwerte) has published a proposal for deriving permissible analytical uncertainty limits related to biological variation data. Reference intervals were used to estimate biological variation. Biological variation data as basis for permissible uncertainty limits are generally accepted. These concepts usually apply a fixed factor leading to unrealistic stringent limits for quantities with a relatively small biological variation and to very permissive limits for quantities with relatively large biological variation. The working group has suggested a non-linear relation between biological variation and permissible uncertainty limits. The new approach has been exemplified with 84 quantities listed in the RiliBÄK (official German guidelines). The algorithms published allowed to derive permissible limits for all quantitative measurands in laboratory medicine. After its publication, three supplements appear necessary: 1. additional specifications of standard uncertainty, 2. a discussion on permissible limits for diagnosis and monitoring purposes, and 3. a discussion on circular reasoning in our approach.

Author(s):  
Anna Carobene ◽  
Marta Strollo ◽  
Niels Jonker ◽  
Gerhard Barla ◽  
William A. Bartlett ◽  
...  

AbstractBackground:Biological variation (BV) data have many fundamental applications in laboratory medicine. At the 1st Strategic Conference of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) the reliability and limitations of current BV data were discussed. The EFLM Working Group on Biological Variation is working to increase the quality of BV data by developing a European project to establish a biobank of samples from healthy subjects to be used to produce high quality BV data.Methods:The project involved six European laboratories (Milan, Italy; Bergen, Norway; Madrid, Spain; Padua, Italy; Istanbul, Turkey; Assen, The Netherlands). Blood samples were collected from 97 volunteers (44 men, aged 20–60 years; 43 women, aged 20–50 years; 10 women, aged 55–69 years). Initial subject inclusion required that participants completed an enrolment questionnaire to verify their health status. The volunteers provided blood specimens once per week for 10 weeks. A short questionnaire was completed and some laboratory tests were performed at each sampling consisting of blood collected under controlled conditions to provide serum, KResults:Samples from six out of the 97 enroled subjects were discarded as a consequence of abnormal laboratory measurements. A biobank of 18,000 aliquots was established consisting of 120 aliquots of serum, 40 of EDTA-plasma, and 40 of citrated-plasma from each subject. The samples were stored at –80 °C.Conclusions:A biobank of well-characterised samples collected under controlled conditions has been established delivering a European resource to enable production of contemporary BV data.


2005 ◽  
Vol 51 (11) ◽  
pp. 2145-2150 ◽  
Author(s):  
Dinesh K Talwar ◽  
Mohammed K Azharuddin ◽  
Cathy Williamson ◽  
Yee Ping Teoh ◽  
Donald C McMillan ◽  
...  

Abstract Background: Components of biological variation can be used to define objective quality specifications (imprecision, bias, and total error), to assess the usefulness of reference values [index of individuality (II)], and to evaluate significance of changes in serial results from an individual [reference change value (RCV)]. However, biological variation data on vitamins in blood are limited. The aims of the present study were to determine the intra- and interindividual biological variation of vitamins A, E, B1, B2, B6, C, and K and carotenoids in plasma, whole blood, or erythrocytes from apparently healthy persons and to define quality specifications for vitamin measurements based on their biology. Methods: Fasting plasma, whole blood, and erythrocytes were collected from 14 healthy volunteers at regular weekly intervals over 22 weeks. Vitamins were measured by HPLC. From the data generated, the intra- (CVI) and interindividual (CVG) biological CVs were estimated for each vitamin. Derived quality specifications, II, and RCV were calculated from CVI and CVG. Results: CVI was 4.8%–38% and CVG was 10%–65% for the vitamins measured. The CVIs for vitamins A, E, B1, and B2 were lower (4.8%–7.6%) than for the other vitamins in blood. For all vitamins, CVG was higher than CVI, with II <1.0 (range, 0.36–0.95). The RCVs for vitamins were high (15.8%–108%). Apart from vitamins A, B1, and erythrocyte B2, the imprecision of our methods for measurement of vitamins in blood was within the desirable goal. Conclusions: For most vitamin measurements in plasma, whole blood, or erythrocytes, the desirable imprecision goals based on biological variation are obtainable by current methodologies. Population reference intervals for vitamins are of limited value in demonstrating deficiency or excess.


Author(s):  
Per Hyltoft Petersen ◽  
Callum G Fraser ◽  
Lone Jørgensen ◽  
Ivan Brandslund ◽  
Marta Stahl ◽  
...  

At a conference on ‘Strategies to Set Global Analytical Quality Specifications in Laboratory Medicine’ in Stockholm 1999, a hierarchy of models to set analytical quality specifications was decided. The consensus agreement from the conference defined the highest level as ‘evaluation of the effect of analytical performance on clinical outcomes in specific clinical settings’ and the second level as ‘data based on components of biological variation’. Here, the many proposals for analytical quality specifications based on biological variation are examined and the outcomes of the different models for maximum allowable combined analytical imprecision and bias are illustrated graphically. The following models were investigated. (1) The Cotlove et al. (1970) model defining analytical imprecision (%CVA) in relation to the within-subject biological variation (%CVw-s) as: %CVA≤ 0·5 × %CVW-S (where %CV is percentage coefficient of variation), (2) The Gowans et al. (1988) concept, which defines a functional relationship between analytical imprecision and bias for the maximum allowable combination of errors for the purpose of sharing common reference intervals. (3) The European Group for the Evaluation of Reagents and Analytical Systems in Laboratory Medicine (EGE Lab) Working Group concept, which combines the Cotlove model with the Gowans concept using the maximal acceptable bias. (4) The External Quality Assessment (EQA) Organizers Working Group concept, which is close to the EGE Lab Working Group concept, but follows the Gowans et al. concept of imprecision up to the limit defined by the model of Cotlove et al. (5) The ‘three-level’ concept classifying analytical quality into three levels: optimum, desirable and minimum. The figures created clearly demonstrated that the results obtained were determined by the basic assumptions made. When %CVW-S is small compared with the population-based coefficient of variation [%CVp = (%CV2W-S +%CV2B-S)1/2], the EGE Lab and EQA Organizers Working Group concepts become similar. Examples of analytical quality specifications based on biological variations are listed and an application on external quality control is illustrated for plasma creatinine.


Author(s):  
William A. Bartlett ◽  
Federica Braga ◽  
Anna Carobene ◽  
Abdurrahman Coşkun ◽  
Richard Prusa ◽  
...  

AbstractData on biological variation are used for many purposes in laboratory medicine but concern exists over the validity of the data reported in some studies. A critical appraisal checklist has been produced by a working group established by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) to enable standardised assessment of existing and future publications of biological variation data. The checklist identifies key elements to be reported in studies to enable safe accurate and effective transport of biological variation data sets across healthcare systems. The checklist is mapped to the domains of a minimum data set required to enable this process.


2021 ◽  
Vol 59 (1) ◽  
pp. 179-186
Author(s):  
Chenbin Li ◽  
Yu Wang ◽  
Hong Lu ◽  
Zhongli Du ◽  
Chengshan Xu ◽  
...  

AbstractObjectivesIt is important to select proper quality specifications for laboratories and external quality assessment (EQA) providers for their quality control and assessment. The aim of this study is to produce new total error (TE) specifications for lymphocyte subset enumeration by analyzing the allowable TE using EQAS data and comparing them with that based on reliable biological variation (BV).MethodsA total of 54,400 results from 1,716 laboratories were collected from China National EQAS for lymphocyte subset enumeration during the period 2017–2019. The EQA data were grouped according to lower limits of reference intervals for establishing concentration-dependent specifications. The TE value that 80% of laboratories can achieve were considered as TE specifications based on state of the art. The BV studies compliant with Biological Variation Data Critical Appraisal Checklist (BIVAC) were used to calculate the three levels of TE specifications. Then these TE specifications were compared for determining the recommended TE specifications.ResultsFour parameters whose quality specifications could achieve the optimum criteria were as follows: the percentages of CD3+, CD3+CD4+ (high concentration) and CD3–CD16/56+ cells, and the absolute count of CD3–CD16/56+ cells. Only the TE specifications of CD3–CD19+ cells could achieve the minimum criteria. The TE specifications of remaining parameters should reach the desirable criteria.ConclusionsNew TE specifications were established by combining the EQA data and reliable BV data, which could help laboratories to apply proper criteria for continuous improvement of quality control, and EQA providers to use robust acceptance limits for better evaluation of EQAS results.


2018 ◽  
Vol 56 (10) ◽  
pp. 1629-1636 ◽  
Author(s):  
Aasne K. Aarsand ◽  
Thomas Røraas ◽  
William A. Bartlett ◽  
Abdurrahman Coşkun ◽  
Anna Carobene ◽  
...  

Abstract Biological variation (BV) data have many applications in laboratory medicine. However, concern has been raised that some BV estimates in use today may be irrelevant or of unacceptable quality. A number of initiatives have been launched by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) and other parties to deliver a more harmonized practice in the generation, reporting and application of BV data. Resulting from a necessary focus upon the veracity of historical BV studies, critical appraisal and meta-analysis of published BV studies is possible through application of the Biological Variation Data Critical Appraisal Checklist (BIVAC), published in 2017. The BIVAC compliant large-scale European Biological Variation Study delivers updated high-quality BV data for a wide range of measurands. Other significant developments include the publication of a Medical Subject Heading term for BV and recommendations for common terminology for reporting of BV data. In the near future, global BV estimates derived from meta-analysis of BIVAC appraised publications will be accessible in a Biological Variation Database at the EFLM website. The availability of these high-quality data, which have many applications that impact on the quality and interpretation of clinical laboratory results, will afford improved patient care.


Author(s):  
Carmen Ricós ◽  
Pilar Fernández-Calle ◽  
Elisabet Gonzalez-Lao ◽  
Margarida Simón ◽  
Jorge Díaz-Garzón ◽  
...  

AbstractObjectivesNumerous biological variation (BV) studies have been performed over the years, but the quality of these studies vary. The objectives of this study were to perform a systematic review and critical appraisal of BV studies on glycosylated albumin and to deliver updated BV estimates for glucose and HbA1c, including recently published high-quality studies such as the European Biological Variation study (EuBIVAS).MethodsSystematic literature searches were performed to identify BV studies. Nine publications not included in a previous review were identified; four for glycosylated albumin, three for glucose, and three for HbA1c. Relevant studies were appraised by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Global BV estimates were derived by meta-analysis of BIVAC-compliant studies in healthy subjects with similar study design.ResultsOne study received BIVAC grade A, 2B, and 6C. In most cases, the C-grade was associated with deficiencies in statistical analysis. BV estimates for glycosylated albumin were: CVI=1.4% (1.2–2.1) and CVG=5.7% (4.7–10.6), whereas estimates for HbA1c, CVI=1.2% (0.3–2.5), CVG=5.4% (3.3–7.3), and glucose, CVI=5.0% (4.1–12.0), CVG=8.1% (2.7–10.8) did not differ from previously published global estimates.ConclusionsThe critical appraisal and rating of BV studies according to their methodological quality, followed by a meta-analysis, generate robust, and reliable BV estimates. This study delivers updated and evidence-based BV estimates for glycosylated albumin, glucose and HbA1c.


2020 ◽  
Vol 58 (10) ◽  
pp. 1663-1672 ◽  
Author(s):  
Andrea Padoan ◽  
Aldo Clerico ◽  
Martina Zaninotto ◽  
Tommaso Trenti ◽  
Renato Tozzoli ◽  
...  

AbstractBackgroundThe comparability of thyroid-stimulating hormone (TSH) results cannot be easily obtained using SI-traceable reference measurement procedures (RPMs) or reference materials, whilst harmonization is more feasible. The aim of this study was to identify and validate a new approach for the harmonization of TSH results.MethodsPercentile normalization was applied to 125,419 TSH results, obtained from seven laboratories using three immunoassays (Access 3rd IS Thyrotropin, Beckman Coulter Diagnostics; Architect System, Abbott Diagnostics and Elecsys, Roche Diagnostics). Recalibration equations (RCAL) were derived by robust regressions using bootstrapped distribution. Two datasets, the first of 119 EQAs, the second of 610, 638 and 639 results from Access, Architect and Elecsys TSH results, respectively, were used to validate RCAL. A dataset of 142,821 TSH values was used to derive reference intervals (RIs) after applying RCAL.ResultsAccess, Abbott and Elecsys TSH distributions were significantly different (p < 0.001). RCAL intercepts and slopes were −0.003 and 0.984 for Access, 0.032 and 1.041 for Architect, −0.031 and 1.003 for Elecsys, respectively. Validation using EQAs showed that before and after RCAL, the coefficients of variation (CVs) or among-assay results decreased from 10.72% to 8.16%. The second validation dataset was used to test RCALs. The median of between-assay differences ranged from −0.0053 to 0.1955 mIU/L of TSH. Elecsys recalibrated to Access (and vice-versa) showed non-significant difference. TSH RI after RCAL resulted in 0.37–5.11 mIU/L overall, 0.49–4.96 mIU/L for females and 0.40–4.92 mIU/L for males. A significant difference across age classes was identified.ConclusionsPercentile normalization and robust regression are valuable tools for deriving RCALs and harmonizing TSH values.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ceylan Bal ◽  
Serpil Erdogan ◽  
Gamze Gök ◽  
Cemil Nural ◽  
Betül Özbek ◽  
...  

Abstract Objectives Calculation of biological variation (BV) components is very important in evaluating whether a test result is clinically significant. The aim of this study is to analyze BV components for copper, zinc and selenium in a cohort of healthy Turkish participants. Methods A total of 10 serum samples were collected from each of the 15 healthy individuals (nine female, six male), once a week, during 10 weeks. Copper, zinc and selenium levels were analyzed by atomic absorption spectrometer. BV parameters were calculated with the approach suggested by Fraser. Results Analytical variation (CVA), within-subject BV (CVI), between-subject BV (CVG) values were 8.4, 7.1 and 4.3 for copper; 4.2, 9.1 and 13.7 for zinc; 7.6, 2.5 and 6.9 for selenium, respectively. Reference change values (RCV) were 30.46, 27.56 and 22.16% for copper, zinc and selenium, respectively. The index of individuality (II) values were 1.65, 0.66 and 0.36 for copper, zinc and selenium, respectively. Conclusions According to the results of this study, traditional reference intervals can be used for copper but we do not recommend using it for zinc and selenium. We think that it would be more accurate to use RCV value for zinc and selenium in terms of following significant changes in recurrent results of a patient.


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