scholarly journals Performance Criteria for Testosterone Measurements Based on Biological Variation in Adult Males: Recommendations from the Partnership for the Accurate Testing of Hormones

2012 ◽  
Vol 58 (12) ◽  
pp. 1703-1710 ◽  
Author(s):  
Yeo-Min Yun ◽  
Julianne Cook Botelho ◽  
Donald W Chandler ◽  
Alex Katayev ◽  
William L Roberts ◽  
...  
Keyword(s):  
Total Error ◽  
Full Range ◽  
Biological Variation ◽  
Analytical Performance ◽  
Performance Criteria ◽  
Performance Goals ◽  
Adult Males ◽  
Large Variability ◽  
Wide Range ◽  
Variation Data

BACKGROUND Testosterone measurements that are accurate, reliable, and comparable across methodologies are crucial to improving public health. Current US Food and Drug Administration–cleared testosterone assays have important limitations. We sought to develop assay performance requirements on the basis of biological variation that allow physiologic changes to be distinguished from assay analytical errors. METHODS From literature review, the technical advisory subcommittee of the Partnership for the Accurate Testing of Hormones compiled a database of articles regarding analytical and biological variability of testosterone. These data, mostly from direct immunoassay-based methodologies, were used to specify analytical performance goals derived from within- and between-person variability of testosterone. RESULTS The allowable limits of desirable imprecision and bias on the basis of currently available biological variation data were 5.3% and 6.4%, respectively. The total error goal was 16.7%. From recent College of American Pathologists proficiency survey data, most currently available testosterone assays missed these analytical performance goals by wide margins. Data from the recently established CDC Hormone Standardization program showed that although the overall mean bias of selected certified assays was within 6.4%, individual sample measurements could show large variability in terms of precision, bias, and total error. CONCLUSIONS Because accurate measurement of testosterone across a wide range of concentrations [approximately 2–2000 ng/dL (0.069–69.4 nmol/L)] is important, we recommend using available data on biological variation to calculate performance criteria across the full range of expected values. Additional studies should be conducted to obtain biological variation data on testosterone from women and children, and revisions should be made to the analytical goals for these patient populations.

Optimizing the use of the “state-of-the-art” performance criteria

2015 ◽  
Vol 53 (6) ◽  
Author(s):  
Rainer Haeckel ◽  
Werner Wosniok ◽  
Thomas Streichert
Keyword(s):  
State Of The Art ◽  
Clinical Chemistry ◽  
Reference Interval ◽  
German Society ◽  
Laboratory Medicine ◽  
Biological Variation ◽  
The State ◽  
Analytical Performance ◽  
Performance Criteria ◽  
Performance Goals

AbstractThe organizers of the first EFLM Strategic Conference “Defining analytical performance goals” identified three models for defining analytical performance goals in laboratory medicine. Whereas the highest level of model 1 (outcome studies) is difficult to implement, the other levels are more or less based on subjective opinions of experts, with models 2 (based on biological variation) and 3 (defined by the state-of-the-art) being more objective. A working group of the German Society of Clinical Chemistry and Laboratory Medicine (DGKL) proposes a combination of models 2 and 3 to overcome some disadvantages inherent to both models. In the new model, the permissible imprecision is not defined as a constant proportion of biological variation but by a non-linear relationship between permissible analytical and biological variation. Furthermore, the permissible imprecision is referred to the target quantity value. The biological variation is derived from the reference interval, if appropriate, after logarithmic transformation of the reference limits.

scholarly journals Analytical and clinical performance of a homogeneous enzymatic LDL-cholesterol assay compared with the ultracentrifugation-dextran sulfate-Mg2+ method

1998 ◽  
Vol 44 (6) ◽  
pp. 1242-1250 ◽  
Author(s):  
Nader Rifai ◽  
Elizabeth Iannotti ◽  
Kristen DeAngelis ◽  
Terence Law
Keyword(s):  
Dextran Sulfate ◽  
Ldl Cholesterol ◽  
Clinical Performance ◽  
Total Error ◽  
Analytical Performance ◽  
Medical Decision ◽  
Serum Samples ◽  
Predictive Values ◽  
Clinical Laboratories ◽  
Wide Range

Abstract LDL-cholesterol (LDL-C) concentration is currently determined in most clinical laboratories by the Friedewald calculation. This approach has several limitations and may not meet the current total error requirement in LDL-C measurement of ≤ 12%. We evaluated the analytical and clinical performance of the direct N-geneous LDL-C assay (Equal Diagnostics). The N-geneous method correlated highly with the modified beta-quantification assay (r = 0.95; y = 0.91x + 70.6 mg/L; n = 199), showed no significant effect of increased triglyceride or other common interferants, and performed adequately in serum samples from nonfasting individuals. This assay demonstrated a mean total error of 6.75% over a wide range of LDL-C concentrations. In addition, at the medical decision cutoff points, this LDL-C assay showed positive predictive values of 78–95% and negative predictive values of 84–99%. We conclude that the N-geneous LDL-C meets the currently established analytical performance goals and appears to have a role in the diagnosis and management of hypercholesterolemic patients.

scholarly journals Glucose Meter Performance Criteria for Tight Glycemic Control Estimated by Simulation Modeling

2010 ◽  
Vol 56 (7) ◽  
pp. 1091-1097 ◽  
Author(s):  
Brad S Karon ◽  
James C Boyd ◽  
George G Klee
Keyword(s):  
Glycemic Control ◽  
Simulation Modeling ◽  
Total Error ◽  
Simulation Models ◽  
Tight Glycemic Control ◽  
Analytical Performance ◽  
Performance Criteria ◽  
Total Allowable Error ◽  
Allowable Error ◽  
Glucose Meter

Abstract Background: Glucose meter analytical performance criteria required for safe and effective management of patients on tight glycemic control (TGC) are not currently defined. We used simulation modeling to relate glucose meter performance characteristics to insulin dosing errors during TGC. Methods: We used 29 920 glucose values from patients on TGC at 1 institution to represent the expected distribution of glucose values during TGC, and we used 2 different simulation models to relate glucose meter analytical performance to insulin dosing error using these 29 920 initial glucose values and assuming 10%, 15%, or 20% total allowable error (TEa) criteria. Results: One-category insulin dosing errors were common under all error conditions. Two-category insulin dosing errors occurred more frequently when either 20% or 15% TEa was assumed compared with 10% total error. Dosing errors of 3 or more categories, those most likely to result in hypoglycemia and thus patient harm, occurred infrequently under all error conditions with the exception of 20% TEa. Conclusions: Glucose meter technologies that operate within a 15% total allowable error tolerance are unlikely to produce large (≥3-category) insulin dosing errors during TGC. Increasing performance to 10% TEa should reduce the frequency of 2-category insulin dosing errors, although additional studies are necessary to determine the clinical impact of such errors during TGC. Current criteria that allow 20% total allowable error in glucose meters may not be optimal for patient management during TGC.

scholarly journals Biological Variation of Vitamins in Blood of Healthy Individuals

2005 ◽  
Vol 51 (11) ◽  
pp. 2145-2150 ◽  
Author(s):  
Dinesh K Talwar ◽  
Mohammed K Azharuddin ◽  
Cathy Williamson ◽  
Yee Ping Teoh ◽  
Donald C McMillan ◽  
...  
Keyword(s):  
Whole Blood ◽  
Total Error ◽  
Reference Intervals ◽  
Biological Variation ◽  
Reference Change Value ◽  
Objective Quality ◽  
Variation Data ◽  
Quality Specifications ◽  
Index Of Individuality ◽  
Apparently Healthy

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.

Performance goals for the laboratory testing of antithrombin, protein C and protein S

2006 ◽  
Vol 96 (11) ◽  
pp. 584-589 ◽  
Author(s):  
Frits Haverkate ◽  
Cornelis Kluft ◽  
Piet Meijer
Keyword(s):  
Protein C ◽  
Total Error ◽  
Diagnostic Testing ◽  
Protein S ◽  
Analytical Performance ◽  
Performance Goals ◽  
Analytical Quality ◽  
Performance Goal ◽  
Protein S Activity

SummaryTo achieve a reliable analytical quality for both monitoring and diagnostic testing, laboratories need to fulfil the widely accepted analytical performance goals based on the biological variation of the analytes of testing. Not only is the short-term analytical performance, which regularly is assessed by internal quality control procedures, of importance, but also the long-term analytical performance. To assess the long-term analytical performance, data obtained from an external quality assessment programme can be used. In this study we have used the evaluation model designed by the ECAT Foundation for the assessment of the longterm analytical performance, including imprecision, bias and total analytical error. The model was applied to the data from 136 different laboratories for the assay of antithrombin (activity), protein C (activity and antigen) and protein S (activity, total and free antigen). The imprecision (median; range), reflected by the long-term analytical coefficient of variation (LCVA), was the lowest for antithrombin (7.6%; 2.6 – 43.8%) and the highest for protein S activity (17.2%; 4.3 – 88.6%). For bias and total error the same pattern was observed (antithrombin: 3.8%; 0.3 – 17.1% and 9.1%; 3.4 – 34.3%, respectively; protein S activity: 12.8%; 3.1 – 34.8% and 24.5%; 9.9 – 87.0%, respectively). For the majority of the laboratories (70 – 85%) the imprecision contributes considerably more to the total error than the bias. However the effect of the bias on the analytical quality is not negligible. Assays for antithrombin, protein C and protein S are mainly used for diagnostic testing. About 70 – 100% of the laboratories can fulfil the desirable performance goal for imprecision. The desirable performance goal for bias was reached by 50 – 95% of the laboratories. In all cases the highest numbers of laboratories fulfilling performance goals was obtained for the protein C variables. To improve the analytical quality in assays of antithrombin, protein C and protein S it is highly recommended that primarily imprecision (non-systematic failures) be suppressed. However the effect of the bias (systematic failures) on the analytical quality should not be neglected. A useful tool for determining the imprecision (LCVA) and bias is the long-term analytical performance evaluation model as used by the ECAT Foundation.

Total error vs. measurement uncertainty: revolution or evolution?

2016 ◽  
Vol 54 (2) ◽  
Author(s):  
Wytze P. Oosterhuis ◽  
Elvar Theodorsson
Keyword(s):  
Clinical Chemistry ◽  
Total Error ◽  
Error Theory ◽  
Theory And Practice ◽  
Analytical Performance ◽  
Performance Goals ◽  
Comprehensive Overview ◽  
Medical Diagnoses ◽  
Stockholm Conference ◽  
Monitoring Treatment

AbstractThe first strategic EFLM conference “Defining analytical performance goals, 15 years after the Stockholm Conference” was held in the autumn of 2014 in Milan. It maintained the Stockholm 1999 hierarchy of performance goals but rearranged them and established five task and finish groups to work on topics related to analytical performance goals including one on the “total error” theory. Jim Westgard recently wrote a comprehensive overview of performance goals and of the total error theory critical of the results and intentions of the Milan 2014 conference. The “total error” theory originated by Jim Westgard and co-workers has a dominating influence on the theory and practice of clinical chemistry but is not accepted in other fields of metrology. The generally accepted uncertainty theory, however, suffers from complex mathematics and conceived impracticability in clinical chemistry. The pros and cons of the total error theory need to be debated, making way for methods that can incorporate all relevant causes of uncertainty when making medical diagnoses and monitoring treatment effects. This development should preferably proceed not as a revolution but as an evolution.

Percentiler and Flagger – low-cost, on-line monitoring of laboratory and manufacturer data and significant surplus to current external quality assessment

2018 ◽  
Vol 42 (6) ◽  
pp. 289-296 ◽  
Author(s):  
Linda M. Thienpont ◽  
Dietmar Stöckl
Keyword(s):  
Low Cost ◽  
Biological Variation ◽  
Analytical Performance ◽  
Performance Goals ◽  
Web Based ◽  
Analytical Stability ◽  
Performance Specifications ◽  
On Line ◽  
The Stability ◽  
Stability Limits

AbstractBackground:We developed two web-based applications called the “Percentiler” and “Flagger”. They use electronically sent data from the analysis of patient samples (medians in the Percentiler; % flagging in the Flagger). Through a graphical user interface, the applications allow on-line monitoring of the stability of analytical performance and flagging rate, both assessed against quality specifications. These are guided by biological variation (Percentiler) and effect of analytical instability on surrogate medical decisions (Flagger). Here, we report on the use of the applications.Methods:We constructed examples with combined observations to investigate whether the Flagger adequately translates the effect of analytical instability observed in the Percentiler, and whether the changes in the flagging rate tolerated by the proposed stability limits is realistic in combination with the analytical performance goals.Results:In general, the examples show that the most prominent flagging rates correlate well with the analytical stability and that the limits proposed for the Flagger are realistically linked to those of the Percentiler. They also show that for certain analytes the specifications for stable flagging rates can be restricted to 20% (relatively to the laboratory’s long-term flagging median) despite ambitious analytical performance goals, while for others they need to be expanded up to 70% in concordance with decreasing biological variation.Conclusions:The examples confirm that the changes in flagging rate is well related to the analytical variation, and that the proposed stability limits are fit-for-purpose. The combined observations may help individual laboratories to define realistic but ambitious performance specifications that apply for their local situation.

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