Biological variation of asymmetric dimethylarginine and related arginine metabolites and analytical performance goals for their measurement in human plasma

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.

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

Clinical Chemistry and Laboratory Medicine (CCLM) ◽

10.1515/cclm-2014-1201 ◽

2015 ◽

Vol 53 (6) ◽

Cited By ~ 3

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.

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

LaboratoriumsMedizin ◽

10.1515/labmed-2018-0030 ◽

2018 ◽

Vol 42 (6) ◽

pp. 289-296 ◽

Cited By ~ 1

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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Analytical performance goals for measuring prostate-specific antigen

Clinical Chemistry ◽

10.1093/clinchem/39.7.1525 ◽

1993 ◽

Vol 39 (7) ◽

pp. 1525-1529 ◽

Cited By ~ 6

Author(s):

H A Fritsche ◽

R J Babaian

Keyword(s):

Prostate Specific Antigen ◽

Specific Antigen ◽

Clinical Decision ◽

Clinical Applications ◽

Analytical Performance ◽

Performance Goals ◽

Clinical Use ◽

Psa Test ◽

Decision Points ◽

Medical Relevance

Abstract We have assessed the feasibility of using fixed-limit criteria based on medical relevance and biological variation for evaluating the analytical performance of the prostate-specific antigen (PSA) test. The estimated within-subject variation of serum PSA is on the order of 10-20% at clinical decision points. The calculated performance goals of 5-10% CV are attainable with current immunoassay technology and agree with precision goals based on clinical experience and the current clinical use of the test. However, new clinical applications of PSA may require a degree of analytical performance that current methods may not be able to provide. The PSA model demonstrates the need for biologically based fixed-limit criteria for all tumor-marker tests.

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Analytical performance of a new automated chemiluminescent magnetic immunoassays for soluble PD-1, PD-L1, and CTLA-4 in human plasma

Scientific Reports ◽

10.1038/s41598-019-46548-3 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 6

Author(s):

Megumi Goto ◽

Kenji Chamoto ◽

Keiko Higuchi ◽

Saya Yamashita ◽

Kenta Noda ◽

...

Keyword(s):

Human Plasma ◽

Analytical Performance

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Evaluation of the clinical chemistry tests analytical performance by using different models and specifications

Turkish Journal of Biochemistry ◽

10.1515/tjb-2018-0250 ◽

2019 ◽

Vol 45 (1) ◽

pp. 11-18

Author(s):

Murat Keleş

Keyword(s):

Quality Management ◽

Measurement Uncertainty ◽

Goal Setting ◽

Clinical Chemistry ◽

Biological Variation ◽

Analytical Performance ◽

Analytical Quality ◽

Analytical Error ◽

Circular Letter ◽

Clinical Chemistry Tests

Abstract Background The importance of managing analytical quality in clinical laboratories is known. Goal-setting models are critical for analytical quality management, along with correctly implemented error models. However, the methods used to determine analytical performance and more importantly, the relevant analytical quality goals are open to discussion. Our aim was to compare the analytical performance characteristics of routine clinical chemistry tests with different goal-setting models which was proposed by various establishments. In addition, to provide a perspective to Turkish total analytical error (TAE) circular letter that compulsory to calculate from 2016. Materials and methods This study was performed by the data obtained from the internal and external quality control of clinical chemistry tests which were measured by Roche Cobas c501 biochemistry analyzer. TAE calculated with TAE% = 1.65 ×(CV%) + Bias% formula. Nordtest uncertainty model was used in the calculation of measurement uncertainty (MU). In this context, total analytical error was evaluated with biological variation (BV), RCPA, CLIA and Turkish allowable total error (ATE) goals. Measurement uncertainty was evaluated with only permissible measurement uncertainty (pU%) goal. Results In our study, RCPA goals are the most stringent, followed by the BVEuBIVAS, BVRicos, pU%, CLIA and finally the ATETurkey goals coming in last. In cumulatively, BVEuBIVAS goals were 18.3% lower than BVRicos for evaluated parameters. Conclusion The balance between applicability and analytical assurance of goals should be well ensured when determining goal-setting models. Circular letter (2016/18) creates awareness to the analytical quality management but still open to development. Biological variation dependent total allowable error model never designed to be used as benchmarks for measurement uncertainty and it is not methodologically appropriate for assessing measurement uncertainty which was estimated by the Nordtest method. Also considered that, the use of “permissible MU” is more methodologically appropriate in the evaluation of measurement uncertainty.

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Analytical performance of nano-LC-SRM using nondepleted human plasma over an 18-month period

PROTEOMICS ◽

10.1002/pmic.201500507 ◽

2016 ◽

Vol 16 (15-16) ◽

pp. 2118-2127 ◽

Cited By ~ 5

Author(s):

Xiaomin Song ◽

Ardeshir Amirkhani ◽

Jemma X. Wu ◽

Dana Pascovici ◽

Thiri Zaw ◽

...

Keyword(s):

Human Plasma ◽

Analytical Performance

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Milan – The new hierarchy: Update from the EFLM strategic conference on defining analytical performance goals. Quality specifications for QC and QAP

Pathology ◽

10.1016/j.pathol.2015.12.044 ◽

2016 ◽

Vol 48 ◽

pp. S16

Author(s):

Graham Jones

Keyword(s):

Analytical Performance ◽

Performance Goals ◽

Quality Specifications

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Application of the CLSI EP15-A3 Guideline as an Alternative Troubleshooting Tool for Verification of Assay Precision

American Journal of Clinical Pathology ◽

10.1093/ajcp/aqz117.007 ◽

2019 ◽

Vol 152 (Supplement_1) ◽

pp. S88-S88

Author(s):

Jose Jara Aguirre ◽

Karl Ness ◽

Alicia Algeciras-Schimnich

Keyword(s):

Quality Control ◽

Carcinoembryonic Antigen ◽

Laboratory Investigation ◽

Analysis Of Variance ◽

Experimental Approach ◽

Biological Variation ◽

Analytical Performance ◽

Microsoft Excel ◽

Before And After ◽

Assay Precision

Abstract Introduction The CLSI EP15-A3 guideline “User Verification of Precision and Estimation of Bias” provides a simple experimental approach to estimate a method’s imprecision and bias. The objective is to determine if the laboratory precision performance of repeatability (SR) and within-laboratory imprecision (SWL) are in accordance to the manufacturer specification claims (MSCs). Objectives Evaluate the utility of the EP15-A3 protocol to verify method precision during a troubleshooting investigation and after major instrument maintenance, using a carcinoembryonic antigen (CEA) immunoassay as an example. Methods CEA was performed on the Beckman Coulter DxI (Beckman Coulter, Brea, CA). Quality control (QC) levels (L1: 2.89; L2: 21.10; L3: 39.10 ng/mL) (Bio-Rad Laboratories, Irvine, CA) were used. Each QC level was measured before and after instrument maintenance as follows: five replicates per run, one run per day, and during 5 days. Imprecision estimates (IEs) for SR (%CVR) and SWL (%CVWL) were calculated by one-way analysis of variance using Microsoft Excel Analyse-it software. Estimated imprecision was compared to MSC and desirable imprecision specifications based on biological variation (BV). Results A change in the analytical performance of CEA was detected by a decreased sigma-metric indicator. After a bias problem was ruled out, the observed %CVR for L1, L2, and L3 were 7.2%, 3.7%, and 4.8%, respectively. The %CVWL were 8.3%, 5.0%, and 5.5%, which exceeded the MSC of %CVWL~4.0% to 4.5%. After a laboratory investigation, major instrument maintenance was performed by the manufacturer. The %CVR and %CVWL estimates for L1, L2, and L3 after maintenance were 3.2%, 3.8%, 3.5% and 3.9%, 4.2%, 4.0%, respectively. After maintenance, the CEA performance was consistent with the MSC for each of the levels analyzed and within the BV impression goal of %CV ≤6.4. Conclusion CLSI EP15-A3 guideline is an alternative troubleshooting tool that can be used to investigate and verify method precision performance before and after significant instrument maintenance.

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