The 1999 Stockholm Consensus Conference on quality specifications in laboratory medicine

2015 ◽  
Vol 53 (6) ◽  
Author(s):  
Callum G. Fraser
Keyword(s):  
Laboratory Medicine ◽  
Consensus Conference ◽  
Analytical Performance ◽  
Performance Goals ◽  
Analytical Quality ◽  
Global Consensus ◽  
Current State ◽  
Regulatory Bodies ◽  
Quality Specifications ◽  
Stockholm Conference

AbstractThe setting of analytical quality specifications in laboratory medicine has been a topic of discussion and debate for over 50 years: 15 years ago, as the subject matured and a profusion of recommendations appeared, many of them from expert groups, it was realised by a number of leading professionals that there was a need for a global consensus on the setting of such specifications. The Stockholm Conference held in 1999 on “Strategies to set global analytical quality specifications in laboratory medicine” achieved this and advocated the ubiquitous application of a hierarchical structure of approaches. The hierarchy has five levels, namely: 1) evaluation of the effect of analytical performance on clinical outcomes in specific clinical settings; 2) evaluation of the effect of analytical performance on clinical decisions in general using a) data based on components of biological variation, or b) analysis of clinicians’ opinions; 3) published professional recommendations from a) national and international expert bodies, or b) expert local groups or individuals; 4) performance goals set by a) regulatory bodies, or b) organisers of external quality assessment (EQA) schemes; and 5) goals based on the current state of the art as a) demonstrated by data from EQA or proficiency testing scheme, or b) found in current publications on methodology. This approach has been much used since its wide promulgation, but there have been ongoing criticisms and new developments. The time seems right for an objective reappraisal of recommended strategies to set analytical performance goals.

scholarly journals Spanish society of laboratory medicine external quality assurance programmes: evolution of the analytical performance of clinical laboratories over 30 years and comparison with other programmes

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Carmen Perich ◽  
Carmen Ricós ◽  
Fernando Marqués ◽  
Joana Minchinela ◽  
Angel Salas ◽  
...  
Keyword(s):  
Quality Assurance ◽  
State Of The Art ◽  
Laboratory Medicine ◽  
Analytical Performance ◽  
External Quality Assurance ◽  
Biological Variability ◽  
External Quality ◽  
Spanish Society ◽  
Clinical Laboratories ◽  
Quality Specifications

AbstractThe purpose of this study is to understand the evolution of the analytical performance of the laboratories participating in the Spanish society of laboratory medicine (SEQCML) external quality assurance (EQA) programmes during its 30 years of operation and to compare it with the performance of other EQA programmes to establish whether the results are similar. The results obtained during this period are evaluated by applying the biological variability (BV) and state of the art-derived quality specifications. In addition, the results are compared with those obtained by other EQA programme organisations. It is noted that the laboratories participating in the EQA–SEQCML programmes have improved their performance over 30 years of experience and that the specifications derived from biological variation are achievable. It is difficult to compare EQA programmes, due to lack of accessibility and the differences in the design of these programmes (control materials, calculations used and analytical specifications established). The data from this study show that for some biological magnitudes the results obtained by the programmes are not yet harmonised, although efforts are being made to achieve this. Organisers of EQA programmes should also join the harmonisation effort by providing information on their results to enable comparison.

Biological variation database: structure and criteria used for generation and update

2015 ◽  
Vol 53 (2) ◽  
Author(s):  
Carmen Perich ◽  
Joana Minchinela ◽  
Carmen Ricós ◽  
Pilar Fernández-Calle ◽  
Virtudes Alvarez ◽  
...  
Keyword(s):  
Numerical Data ◽  
Relevant Information ◽  
Laboratory Medicine ◽  
Biological Variation ◽  
The Internet ◽  
Analytical Quality ◽  
Database Structure ◽  
Variation Database ◽  
Quality Specifications ◽  
Allowable Error

AbstractNumerical data on the components of biological variation (BV) have many uses in laboratory medicine, including in the setting of analytical quality specifications, generation of reference change values and assessment of the utility of conventional reference values.Generation of a series of up-to-date comprehensive database of components of BV was initiated in 1997, integrating the more relevant information found in publications concerning BV. A scoring system was designed to evaluate the robustness of the data included. The database has been updated every 2 years, made available on the Internet and derived analytical quality specifications for imprecision, bias and total allowable error included in the tabulation of data.Our aim here is to document, in detail, the methodology we used to evaluate the reliability of the included data compiled from the published literature. To date, our approach has not been explicitly documented, although the principles have been presented at many symposia, courses and conferences.

Analytical performance, reference values and decision limits. A need to differentiate between reference intervals and decision limits and to define analytical quality specifications

2012 ◽  
Vol 50 (5) ◽  
Author(s):  
Per Hyltoft Petersen ◽  
Esther A. Jensen ◽  
Ivan Brandslund
Keyword(s):  
Reference Values ◽  
Clinical Guidelines ◽  
Reference Intervals ◽  
Analytical Performance ◽  
International Expert ◽  
Analytical Quality ◽  
Quality Specifications ◽  
Reference Samples ◽  
Critical Situations

AbstractWith the increasing use of decision limits (action limits, cut-off points) specified for a number of analytical components in diagnosis and for action in critical situations, formulated in national or international recommendations, the traditional interpretation of reference intervals has been uncertain, and sometimes the two concepts are being mixed up by incorporating risk calculations in the reference intervals. There is, therefore, a need to clarify the two concepts and to keep them definitely separated. Reference intervals are the 95% limits for the descriptions of the distributions of the values of analytical components measured on reference samples from reference individuals. Decision limits are based on guidelines from national and international expert groups defining specific concentrations of certain components as limits for decision about diagnosis or well-defined specific actions. Analytical quality specifications for reference intervals have been defined for bias since the 1990s, but in the recommendations specified in the clinical guidelines analytical quality specifications are only scarcely defined. The demands for negligible biases are, however, even more essential for decision limits, as the choice is no longer left to the clinician, but emerge directly from the concentration. Even a small bias will change the number of diseased individuals, so the demands for negligible biases are obvious. A view over the analytical quality as published gives a variable picture of bias for many components, but with many examples of considerable bias which must be critical – yet no specifications have been stipulated until now.

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.

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.

Combination of Analytical Quality Specifications Based on Biological Within- and Between-Subject Variation

2002 ◽  
Vol 39 (6) ◽  
pp. 543-550 ◽  
Author(s):  
Per Hyltoft Petersen ◽  
Callum G Fraser ◽  
Lone Jørgensen ◽  
Ivan Brandslund ◽  
Marta Stahl ◽  
...  
Keyword(s):  
Coefficient Of Variation ◽  
Working Group ◽  
Population Based ◽  
Laboratory Medicine ◽  
Biological Variation ◽  
Analytical Quality ◽  
External Quality ◽  
Analytical Imprecision ◽  
Quality Specifications ◽  
Group Concept

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.

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.

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