<p><strong>Validation of analytical methods (i.e. procedures) usually excludes the primary sampling, but this is now widely recognised as the first step in the measurement procedure [1] (Fig.1). Validation of the whole measurement procedure therefore requires consideration of a performance characteristic that reflects the quality of all of the steps (including sampling and physical sample preparation). The uncertainty of the final measurement value is that key characteristic that unifies this whole measurement procedure and enables its validation, particularly when supported by performance characteristics that have an established role in the validation of an analytical procedure as a standalone activity [2]. This leaflet summarises the new Eurachem/CITAC guidance on the Validation of Measurement Procedures that Include Sampling (VaMPIS) [3]. It can be applied to the whole measurement process either simultaneously, where the sampling and analytical procedures are validated as a unified measurement procedure, or sequentially when the analytical procedure has previously been validated in isolation.</strong></p><h4><strong>In situ and ex situ measurement</strong></h4><p>There are now many <i><strong>in situ</strong></i> measurement techniques (e.g. portable XRF in Fig. 1c), where the measurement is taken directly from the sampling target, without the need to extract a physical sample. This <strong>new mode of measurement </strong>highlights the need for an integrated approach to the definition of the measurement process so that it includes sampling. This approach is also equally applicable to the traditional mode of ex situ measurement (Fig. 1b) of a physical sample extracted from a sampling target (Fig. 1a). Both modes require the primary sampling to be included within the measurement procedure, its validation, and in the estimation of measurement uncertainty.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Figure_1_Representation_of_the_whole_measurement_process_7e63297705.jpg" alt="Eurachem: Figure 1. Representation of the whole measurement process that requires validation. In the ex situ mode this includes the two steps of (a) primary sampling (in this case of a bay of lettuce heads) followed by (b) chemical analysis. In in situ mode this usually requires just one step (c) both sampling and analysis within the same measurement process (in this case in situ pXRF on an area of soil)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Figure_1_Representation_of_the_whole_measurement_process_7e63297705.jpg 172w," sizes="100vw" width="857" height="778"></p><h4><strong>How to apply VaMPIS</strong></h4><p>The only parameter of a measurement procedure that can effectively integrate the effects on data quality from all of the steps in the procedure (including sampling) is the <strong>measurement uncertainty.</strong> This uncertainty is stated within the final measurement result. It allows the user of that result to assess the effects of both random and systematic effects arising at every stage of the measurement procedure on decisions that are to be made using that result (e.g. compliance of a batch of material with a regulatory threshold). The VaMPIS approach therefore uses the uncertainty of the measurement value to judge the <strong>fitness for purpose</strong> (and hence validity) of the whole measurement procedure by comparing it with a ‘target’ uncertainty. It is <strong>essential that the target uncertainty should also include the contribution from sampling</strong>, and it can either be set by an external body (e.g. a regulator) or, if that is not available, by the user, using a technique such as the <strong>Optimum Uncertainty method</strong> ([3] Appendix B). <strong>Worked examples</strong> of validation are given where the whole measurement procedure is applied, either ex situ (Appendix A1: Nitrate in extracted composite samples of lettuce, Fig. 1a) or in situ (A2: Pb in soil by pXRF without removal of physical samples, Fig. 1c). There are eleven broad steps for the application of VaMPIS (Fig. 2). Measurement uncertainty is generally estimated using the <strong>Duplicate Method</strong> in which duplicate primary samples are taken from at least eight sampling targets by an independent reinterpretation of the sampling procedure. Both duplicate samples are then analysed in duplicate. The measurement uncertainty, and its main components from sampling and analysis (as repeatability), are estimated by applying ANOVA to the resultant measurement values, and also including analytical bias and sampling bias where possible [1]. The <strong>fitness for purpose of the procedure</strong> is judged by comparing the estimated measurement uncertainty against a value of target uncertainty set for that particular purpose [3].</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Figure_2_Flow_chart_for_Va_MPIS_application_0371d52580.jpg" alt="Eurachem: Figure 2. Flow chart for VaMPIS application" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Figure_2_Flow_chart_for_Va_MPIS_application_0371d52580.jpg 127w," sizes="100vw" width="735" height="898"></p><p>There are <strong>planning steps</strong> followed by <strong>implementation steps</strong>. The measurement uncertainty (MU) and its component arising from sampling (UfS) are usually estimated using the Duplicate Method followed by Analysis of Variance (ANOVA) [1]. The <strong>decision</strong> on whether the measurement procedure (MP) is fit for purpose (FFP) is based upon comparing the actual MU against the target MU. If not FFP, the decision on whether to improve the sampling procedure (SP) or the analytical procedure (AP) depends on their respective contributions to both the MU and the measurement cost. In the sequential approach to VaMPIS, the FFP of the AP, that has been previously validated in isolation, is checked to see if it is still FFP within this whole MP. If the MU from the analytical procedure needs to be improved, the most appropriate of the traditional performance characteristics [2] need to be modified to that end. (AQC is Analytical Quality Control.)</p><p>The VaMPIS guide [3] also includes a discussion of the role of ongoing quality control of the whole measurement procedure (integrated measurement quality control, IMQC) to ensure ongoing quality compliance after the initial validation. One major challenge for implementation that is also discussed, is to ensure effective communication and cooperation between the laboratory staff and the oftendifferent organisation that takes the samples.</p><blockquote><p>Produced by the Joint Technical Group on VaMPIS with representatives from the Eurachem and AMC Sampling Uncertainty and Eurachem Method Validation Working Groups, as well as from CITAC &amp; Nordtest. First English edition, [April 2025], <a href="www.eurachem.org"><strong>www.eurachem.org</strong></a></p></blockquote>

VaMPIS - Validation of Measurement Procedures that Include Sampling

<p><strong>Eurachem and CITAC welcome analysts interested in the evaluation of chemical analysis uncertainty and in how to use this information in results interpretation. The Eurachem Week 2026 will begin with a training course on “Evaluation of the measurement uncertainty from in-house precision and recovery data” scheduled for Sunday, 10 May 2026. A two-days workshop on “Quality in Analytical Measurements: Uncertainty Evaluation and Results Interpretation” open to all interested participants will take place from 11 to 12 May 2026. On 13 May 2026, the Eurachem Working Groups will convene, followed by the Eurachem General Assembly, which will bring together the Executive and national delegates on 14 and 15 May. Both Working Group Meetings and the General Assembly are restricted to their members.</strong></p><p>The results of qualitative and quantitative chemical analyses should have an acceptable uncertainty, which should ideally be reported and considered in results interpretation.</p><p>For many analytical applications, simplified uncertainty evaluations can determine uncertainty values that meet the defined requirements for this parameter. The workshop will focus on the key technical challenges involved in practical evaluations of measurement uncertainty based on precision and recovery data gathered during in-house method validation and quality control. There will be a discussion of how to model the variation of the measurement uncertainty within the analytical range and how to handle divergent recovery values from the analysis of various reference materials. A session on the use of measurement uncertainty in conformity assessment will explore how the risk of false conformity decisions can be managed.</p><blockquote><h5><strong>New Eurachem guidance on using in-house precision and recovery data will be discussed at the workshop.</strong></h5></blockquote><p>Topics will also include the validation and uncertainty evaluation for qualitative analyses with particular attention to current accreditation requirements for these types of analysis. The last session of the workshop will be dedicated to the evaluation of measurement uncertainty arising from sampling and using it to judge the fitness for purpose, and hence validation, of measurement procedures that include sampling. Four sessions of the workshop will include engaging breakout sessions where participants will have the chance to share their views about challenging aspects of the analytical work. Participants are invited to propose posters and oral communications on session topics or any other relevant topic for analytical chemists or stakeholders of the analytical work.</p><h3><strong>Registration</strong></h3><blockquote><p class="cke-user_style-important"><strong>👉</strong><a target="_blank" rel="noopener noreferrer" href="https://conferences.chemistry.pt/register/eurachem2026"><strong>Register here for the workshop</strong></a></p></blockquote><h4><strong>Registration Fees</strong></h4><h5><strong>Early bird (EUR) - Until April 15th</strong></h5><ul><li><strong>Workshop: Regular participant (11 &amp; 12 May 2026): </strong>400 EUR</li><li><strong>Workshop: Student (11 &amp; 12 May 2026): </strong>250 EUR</li><li><strong>Eurachem Working Group<sup>1</sup> (13 May 2026):</strong> 75</li><li><strong>General Assembly<sup>2</sup> (14 &amp; 15 May 2026): </strong>250</li><li><strong>Training On Uncertainty Evaluation<sup>3</sup> (10 May 2026):</strong> 150</li></ul><h5><strong>After April 15th</strong></h5><ul><li><strong>Workshop: Regular participant (11 &amp; 12 May 2026): </strong>450 EUR</li><li><strong>Workshop: Student (11 &amp; 12 May 2026):</strong> 300 EUR</li><li><strong>Eurachem Working Group<sup>1</sup> (13 May 2026): </strong>100</li><li><strong>General Assembly<sup>2</sup> (14 &amp; 15 May 2026):</strong> 300</li><li><strong>Training On Uncertainty Evaluation<sup>3</sup> (10 May 2026): </strong>200</li></ul><blockquote><p>§ - <strong>50 EUR reduction for members of Eurachem</strong>, CITAC, SPQ, RELACRE, ForMEQ and SPMet at the workshop.</p><p>10% reduction for organisations that registered more than one participant.</p><p><sup>1 </sup>- Working group members</p><p><sup>2</sup> - Eurachem members</p><p><sup>3</sup> - 50% reduction for workshop participants</p></blockquote><h3><strong>Workshop</strong></h3><h4><strong>Eurachem/CITAC Workshop on Quality in Analytical Measurements:</strong></h4><h5><strong>Uncertainty Evaluation and Results Interpretation</strong></h5><p>The results of qualitative and quantitative chemical analyses should have an acceptable uncertainty, which should ideally be reported and considered in results interpretation. For many analytical applications, simplified uncertainty evaluations can determine uncertainty values meeting defined requirements for this parameter. The workshop will focus on the key technical challenges involved in practical evaluations of measurement uncertainty based on precision and recovery data gathered during in-house method validation. It will be discussed how to model the variation of the measurement uncertainty within the analytical range and how to handle divergent recovery values from the analysis of various reference materials. A session on the use of measurement uncertainty in conformity assessment will explore how the risk of false conformity decisions can be managed.</p><p>Topics will also include the validation and uncertainty evaluation of qualitative analyses with particular attention to current accreditation requirements for these types of analysis. The last session of the workshop will be dedicated to the evaluation of measurement uncertainty arising from sampling and using it to judge the fitness for purpose, and hence validation, of measurement procedures that include sampling.</p><p>Four sessions of the workshop will include engaging breakout sessions where participants will have the chance to share their views about challenging aspects of the analytical work. Participants are invited to propose posters and oral communications on session topics or any other relevant topic for analytical chemists or stakeholders of the analytical work.</p><h3><strong>Training Course</strong></h3><h4><strong>Evaluation of the measurement uncertainty from in-house precision and recovery data</strong></h4><ul><li>10 May 2026</li></ul><p>A course on the fundamentals of the evaluation of the measurement uncertainty from in-house precision and recovery data will be held on Sunday, 10 May 2026. This training is targeted for analysts with a basic understanding of the measurement uncertainty concept, how uncertainty components propagate, and how the combined uncertainty is expanded. Following the morning presentation of the theory of uncertainty evaluation, the afternoon will be dedicated to applying the theory to real-world cases. Trainees should have basic skills in using Microsoft Excel spreadsheets and bring a laptop with Microsoft Excel to complete the exercises. The interaction between trainers and trainees will be promoted to guarantee learning efficiency.</p><h5><strong>Trainers:</strong></h5><ul><li>Ricardo Bettencourt da Silva, Faculdade de Ciências da Universidade de Lisboa, Portugal (rjsilva@ciencias.ulisboa.pt)</li><li>Stephen L. R. Ellison - UK National Measurement Laboratory (NML) hosted at LGC, United Kingdom</li><li>Vicki Barwick - UK National Measurement Laboratory (NML) hosted at LGC, United Kingdom</li></ul><h4><strong>Agenda</strong></h4><h5><strong>8:00 Registration</strong></h5><h5><strong>9:00 Opening</strong></h5><h5><strong>9:05 Identifying, combining, and expanding uncertainty components: Theory and examples</strong></h5><h5><strong>9:45 Precision uncertainty: Theory and examples</strong></h5><h5><strong>10:30 </strong>Coffee break</h5><h5><strong>10:50 Trueness-related uncertainty: Theory and examples</strong></h5><h5><strong>12:00 Additional questions and discussion</strong></h5><h5><strong>12:30 </strong>Lunch</h5><h5><strong>13:30 Application example 1</strong></h5><h5><strong>15:30 </strong>Coffee break</h5><h5><strong>15:50 Application example 2</strong></h5><h5><strong>17:00 Additional questions and discussion</strong></h5><h5><strong>17:30 Closing</strong></h5><h3><strong>Venue</strong></h3><p>The series of Eurachem events will be held in:</p><ul><li>Meliã Lisboa Aeroporto ****</li><li>Rua C,2 1749-125 Lisboa, Portugal&nbsp;</li></ul>

Eurachem/CITAC Workshop on Quality in Analytical Measurements 2026

<p><strong>This leaflet is intended as a comprehensive checklist outlining the key steps to consider when participating in a proficiency testing (PT) scheme. Selection of an appropriate PT scheme must be ensured [1]. It provides essential tips to help participants avoid common mistakes and achieve successful outcomes. The main stages of PT participation are covered, from receipt of PT items through to the review of received evaluations [1-3]. Documentation of outcomes for many of the topics addressed below is recommended, particularly for accreditation purposes.&nbsp;</strong></p><h4><strong>1. Prior to PT participation&nbsp;</strong></h4><ul><li>Verify that the PT provider has up-to-date billing, shipping and technical contact information for the laboratory.&nbsp;</li><li>Ensure that the laboratory has documented procedures in place or, if necessary, prepare procedures for: reviewing PT results upon receipt; taking corrective actions when assessments indicate poor performance; conducting periodic reviews of PT results over time; storing PT reports.&nbsp;</li></ul><h4><strong>2. Receipt of PT items&nbsp;</strong></h4><ul><li>Open the package of PT items immediately upon receipt to check their condition. Contact the PT provider and request a replacement if any PT items are missing, broken, leaking or otherwise compromised.&nbsp;</li><li>Study the PT provider’s instructions carefully to ensure they are clear and understandable (e.g. handling, storage, pre-treatment, preparation, reporting of results).&nbsp;</li><li>Register, identify, and mark the PT items according to normal procedures in the laboratory.&nbsp;</li><li>Store the PT items in accordance with any instructions provided.&nbsp;</li></ul><h4><strong>3. Measurements&nbsp;</strong></h4><ul><li>Read the instructions supplied by the PT provider carefully before starting the measurements.&nbsp;</li><li>Carry out the measurements under conditions as close as possible to routine testing, unless otherwise instructed by the PT provider.&nbsp;</li><li>Ensure that the analysis is carried out to meet any measurement deadline requirements.</li></ul><h4><strong>4. Reporting results&nbsp;</strong></h4><ul><li>Allow sufficient time for reporting the results to the PT provider.&nbsp;</li><li>Report all the information required by the PT provider.&nbsp;</li><li>Ensure that the results are reported in the requested format (e.g. units, number of significant figures, decimal places).&nbsp;</li><li>Ensure that the results you are going to submit are those that you intend, correcting for any identified transcription errors (e.g. mix-up of samples or analytes).&nbsp;</li><li>Confirm that the submission process of the results to the PT provider has been completed.&nbsp;</li></ul><h4><strong>5. Reviewing PT reports&nbsp;</strong></h4><ul><li>Read the PT report as soon as possible and check that your results and other information are correctly represented; report any errors immediately to the PT provider.&nbsp;</li><li>Take notice of any comments on the specific PT round, evaluation of performance, and other matters relevant to the results of the PT round which provide valuable context to your individual results.&nbsp;</li><li>Review your assessed performance carefully in accordance with your laboratory procedures.&nbsp;</li><li>Store the PT report according to internal procedures.&nbsp;</li></ul><h4><strong>6. Follow-up on participation in a PT scheme&nbsp;</strong></h4><ul><li>Investigate any poor performance in accordance with your laboratory quality system [4].&nbsp;</li><li>Evaluate the impact of poor performance (e.g. risk that poor quality data may have been reported to customers).&nbsp;</li><li>Implement any corrective actions as relevant, and if possible, make use of any surplus PT items [5] to assess effectiveness.&nbsp;</li><li>Monitor any trends in performance over time, concentration levels, etc.&nbsp;</li></ul><blockquote><p>Information about PT providers and PT schemes can be obtained from your national accreditation body, from the <a target="_blank" rel="noopener noreferrer" href="https://www.eptis.org/"><strong>EPTIS website</strong></a> or from other national or international organizations.</p></blockquote>

Basic instructions for participants in a proficiency testing scheme

<p><strong>The leaflet outlines the role and handling of analytical equipment and systems in the process of a laboratory dealing with the analysis of chemical elements and molecules. It is an introduction to topics being considered by the Eurachem Analytical Equipment and Systems Qualification Working Group.&nbsp;</strong></p><p>Various steps are required to draw a conclusion concerning the <strong>object being examined</strong> (sampling target), see Fig. 1. The core part, the analytical <strong>measurement</strong>, is based on an <strong>analytical principle</strong>. The measurement is based on a physical or chemical interaction, e.g. between light of a certain wavelength and the sample, which leads to a displayed measured value. This measurement is carried out using analytical equipment. This <strong>equipment</strong> must be <strong>fit for its intended use</strong>. Complex analytical equipment with extensive data processing is referred to as a system. Analytical equipment is used to perform the <strong>analytical method</strong>. The method must be validated to demonstrate that it is <strong>fit for purpose</strong>.&nbsp;</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Fig_1_Analytical_principle_method_and_procedure_1_b751d25236.jpg" alt="Eurachem: Fig. 1 Analytical principle, method and procedure [1]" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Fig_1_Analytical_principle_method_and_procedure_1_b751d25236.jpg 245w," sizes="100vw" width="841" height="439"></p><h4><strong>The pyramid of quality&nbsp;</strong></h4><p>The pyramid of quality (Fig. 2) covers the <strong>analytical method</strong>. In order to produce a reproducible, <strong>reportable result</strong> that is suitable for the intended purpose, the <strong>equipment (system) </strong>(1<sup>st</sup> level) and <strong>analytical method </strong>(2<sup>nd</sup> level) must be well defined and under control, qualified or validated, respectively.&nbsp;</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Fig_2_Pyramid_of_quality_979312ac6b.jpg" alt="Eurachem: Fig. 2 Pyramid of quality" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Fig_2_Pyramid_of_quality_979312ac6b.jpg 163w," sizes="100vw" width="708" height="677"></p><p>The equipment must have similar performance when carrying out the analyses as when developing and validating the method. Particularly in the case of methods based on libraries or training datasets, the long-term stability of the equipment must be ensured. In the case of transfer of the method to other equipment, both sets of equipment must have similar performance.&nbsp;</p><p>The performance of the equipment and the behaviour of the method are monitored by quality control measures. This is the purpose of the <strong>internal</strong> or <strong>short term</strong> (3<sup>rd</sup> level) and <strong>inter-laboratory</strong> or <strong>long term</strong> (4<sup>th</sup> level) <strong>quality assurance</strong>. When selecting the quality assurance elements, the findings from levels 1 and 2 are taken into account.&nbsp;</p><h4><strong>Is "calibration" sufficient?&nbsp;</strong></h4><p>All relevant quality assurance systems, e.g. those meeting the requirements of ISO/IEC 17025 [2] and related standards, require equipment and systems to be traceably calibrated. But is that enough to prove the fitness for the intended use of the analytical equipment?&nbsp;</p><p>According to the definition in VIM [3] calibration is the operation that, under specified conditions, establishes a relation between the <strong>quantity values</strong> with measurement uncertainties provided by measurement standards <strong>and corresponding indications</strong> with associated measurement uncertainties. It is implicitly assumed that the <strong>influencing quantities</strong> (e.g. ambient conditions, temperature, flow rates, intensities of signal sources, etc.) are constant and do not exhibit any short or long-term fluctuations or drifts. This assumes that no changes occur due to influencing quantities.&nbsp;</p><p>Nevertheless this is not the case in everyday analytical work. The influence of fluctuations or changes in the influencing quantities is evaluated through robustness investigations during method development and validation. The magnitude of the fluctuations or deviations of the equipment is specified and verified during equipment qualification.&nbsp;</p><h4><strong>The Fitness for Intended Use&nbsp;</strong></h4><p>The life cycle (Fig. 3) of new equipment to be purchased by the laboratory begins with the definition of the requirements and the intended use of the equipment.&nbsp;</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Fig_3_Equipment_or_system_lifecycle_2919ea802d.jpg" alt="Eurachem: Fig. 3 Equipment or system lifecycle" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Fig_3_Equipment_or_system_lifecycle_2919ea802d.jpg 186w," sizes="100vw" width="887" height="742"></p><p>The <strong>User Requirement Specifications (URS) </strong>define the selection criteria and the operational ranges of the equipment parameters (influence variables), e.g. flows, temperatures, analysis volumes, etc. Considerations to support data integrity and traceability are also included in the URS. For more complex systems, the interfaces and compatibility of the components are essential.&nbsp;</p><p>All considerations made in this phase have an impact on the entire life cycle, i.e. right through to decommissioning. The stability and variability of the influence variables are monitored over the entire service life.&nbsp;</p><p>In most cases, data and metadata should remain accessible and analysable beyond the end of the equipment's life. The laboratory must use its resources as sparingly and sustainably as possible. This includes the expected service life and the costs incurred. Data integrity considerations (ALCOA+ = <strong>A</strong>ttributable, <strong>L</strong>egible, <strong>C</strong>ontemporaneous, <strong>O</strong>riginal, <strong>A</strong>ccurate, + Complete, Consistent, Enduring, Available) play a role during operation and at the end of life. These include paper records and electronic records.&nbsp;</p><p>In the pharmaceutical industry, qualification of equipment and thus ensuring that analytical equipment and systems are suitable for the intended use, is mandatory, and the respective processes are often clearly defined. Specifications are also comprehensively defined for various equipment classes.&nbsp;</p><p>The ISO standards, in particular ISO 9001 [4], ISO 10012 [5], ISO/IEC 17025 [2], ISO 17034 [6] or ISO/IEC 17043 [7], cover a very large area and a wide range of sectors. For specific sectors, an interpretation of the standards is required. Eurachem guides cover requirements for analytical chemistry and related disciplines. The Analytical Equipment and Systems Qualification Working Group is therefore developing guidance on establishing the fitness for intended use of analytical equipment and systems aimed at these disciplines.</p>

Fitness for the intended use of analytical equipment and systems

<h4><strong>The problem&nbsp;</strong></h4><p>We live in a “global village” but we are all different and we use many different languages to communicate.&nbsp;</p><p>Even when people speak the same language, the same words may be used with different meanings. See, for example, some different uses of the word “standard” in English – a normative document, a solution of known concentration or even a type of flag.&nbsp;</p><p>Even in the same area of activity misunderstandings do occur which may result in a waste of time and money, or even worse consequences.&nbsp;</p><p>When talking about laboratory tests, lack of a full understanding of key terms and inappropriate translations leaves room for different interpretations of stated requirements. For example, there have historically been a number of different but related uses of the term ‘<strong>detection limit’</strong>. This may lead to inadequate fulfilment of those requirements, thus becoming an obstacle to the production of analytical data that is fit for its intended use. A shared interpretation of concepts related to quality in measurement between laboratories and accreditation bodies is also crucial for a fair and harmonised approach to laboratory assessment across the world.&nbsp;</p><h4><strong>A common language&nbsp;</strong></h4><p>We need a <strong>common language</strong>; clear and unambiguous. We need a common vocabulary to provide consistent definitions of concepts with their associated terms. To this end, several organisations participate in a joint effort to develop and maintain an <strong>international vocabulary of metrology</strong> (VIM) [1], which aims to achieve a unique understanding of concepts related to measurements across all sectors. The VIM is a normative reference in the standards <strong>ISO/IEC 17025, ISO 15189 and ISO/IEC 17043</strong>, and is therefore a key document for all organisations seeking accreditation.&nbsp;</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_You_talk_we_understand_The_way_out_of_the_tower_of_Babel_Standards_8d947dbd5f.jpg" alt="Eurachem: You talk, we understand – The way out of the tower of Babel_A common language" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_You_talk_we_understand_The_way_out_of_the_tower_of_Babel_Standards_8d947dbd5f.jpg 245w," sizes="100vw" width="1126" height="499"></p><h4><strong>Is this enough?&nbsp;</strong></h4><p>For laboratory staff some problems still stand and need to be addressed:&nbsp;</p><ul><li>Many people are confused about both concepts and terms.&nbsp;</li><li>It may be difficult to understand the “formal” VIM definitions – they are short statements intended to apply to many different measurement sectors.</li><li>Translations into local languages may add to the confusion, e.g. if different terms are used in different sectors for the same VIM concept and the translator overlooks this issue.</li><li>Some substantial changes to terminology have been made in an attempt to accommodate chemical and biological measurements. Some “old” concepts still stand but have new names, e.g. “within laboratory reproducibility” vs. “intermediate precision”.&nbsp;</li></ul><p>To address these issues Eurachem has produced a guide [2] which provides an accessible reference containing simple and in context explanations of terms most relevant to analysts, with additional examples relating those concepts to chemical and biological measurements.&nbsp;</p><h4><strong>Do you understand the meaning of these terms?&nbsp;</strong></h4><p>Are you interested in a <strong>quantity</strong> or a quality? Depending on the answer, will you use a <strong>measurement</strong> <strong>procedure</strong> or an examination? Is method <strong>verification</strong> the same or less demanding than method <strong>validation</strong>? Do you need a <strong>calibration</strong> or just performance verification? Do you have a <strong>measurement standard</strong> in your laboratory? Is <strong>metrological traceability</strong> something you worry about? These are examples of the terms supporting the reliability of any measurement result that need to be clearly understood.&nbsp;</p><h5><strong>Example – Accuracy, trueness, precision: are they synonyms?&nbsp;</strong></h5><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_You_talk_we_understand_The_way_out_of_the_tower_of_Babel_accuracy_231e1e005e.jpg" alt="Eurachem: You talk, we understand – The way out of the tower of Babel_Example – Accuracy, trueness, precision" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_You_talk_we_understand_The_way_out_of_the_tower_of_Babel_accuracy_231e1e005e.jpg 146w," sizes="100vw" width="754" height="807"></p><ul><li>Closeness between measurement results (relating to the concept of precision)</li><li>Closeness of the average of the measurement results to a reference value (relating to the concept of trueness)&nbsp;</li><li>Closeness of an individual measurement result to the true value (relating to the concept of accuracy)&nbsp;</li></ul><p>The different situations in the figure show the effect of:&nbsp;</p><ol style="list-style-type:lower-latin;"><li>poor precision and trueness (imprecise and biased)&nbsp;</li><li>good precision, poor trueness (precise but biased)&nbsp;</li><li>poor precision, good trueness (imprecise but unbiased)&nbsp;</li><li>good precision and trueness (precise and unbiased)&nbsp;</li></ol><p>Improving both precision and trueness is expected to improve accuracy.&nbsp;</p><h4><strong>Is all this relevant to you?&nbsp;</strong></h4><p>Do you work in a laboratory, either as an analyst, quality manager or director? Are you involved in other activities related to analytical work, such as providing proficiency tests, producing reference materials or accrediting any such activity? Do you teach or study subjects related to measurements? Do you use measurement results or prescribe how to use them? <i><strong>If the answer is yes to any of these questions, the following reference documents are also for you</strong></i>.</p>

You talk, we understand – The way out of the tower of Babel

<h4><strong>1 - What is fitness for purpose?&nbsp;</strong></h4><p>The test meets the necessary performance criteria for a clinical binary examination<strong> to ensure it is suitable for making accurate and reliable clinical decisions in the intended patient population. </strong>Among others, performance criteria include clinical sensitivity and clinical specificity.&nbsp;</p><h4><strong>2 - How to assess clinical performance?&nbsp;</strong></h4><p>Assessing the clinical performance of a binary examination, stating results as 'positive' or 'negative,' involves calculating the examination's <strong>Clinical Sensitivity and Clinical Specificity</strong>. From the physician's point of view, clinical performance is evaluated by using predictive values, i.e., how likely is it that a positive or negative result corresponds to the presence or absence of the condition, which is also influenced by the prevalence of the condition in the population being tested.&nbsp;</p><h4><strong>3 - What is Clinical Sensitivity?&nbsp;</strong></h4><p><strong>Clinical sensitivity (SS)</strong>, also known as the True Positive Rate, measures the proportion of true positives correctly identified by the test. Data from a group of subjects who have been confirmed to have the disease or condition through diagnosis or a gold standard test (<i>D<sub>1</sub></i> in Table 1) are needed to calculate clinical sensitivity.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Table_1_2x2_Contingency_table_for_clinical_diagnosis_241735a171.jpg" alt="Eurachem: Table 1. 2x2 Contingency table for clinical diagnosis." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Table_1_2x2_Contingency_table_for_clinical_diagnosis_241735a171.jpg 245w," sizes="100vw" width="1401" height="461"></p><p>The formula for clinical sensitivity is:&nbsp;</p><p><i><strong>SS = tp / (tp + fn)</strong></i>, with:&nbsp;</p><ul><li><i>tp</i>, <strong>True Positives</strong> are the cases where the test correctly identifies the presence of the disease.&nbsp;</li><li><i>fn</i>, <strong>False Negatives</strong> are the cases where the test incorrectly identifies the absence of the disease when it is actually present.&nbsp;</li></ul><p>Table 1 represents the components of clinical sensitivity and specificity. Figure 1 illustrates an example of the overlapping of the number of components. The symbol "∩" represents the intersection of groups. For example, <i>D<sub>1</sub></i>∩n denotes the set of negative results obtained for known positive cases, i.e., false negatives.</p><h4><strong>4 - What is Clinical Specificity?&nbsp;</strong></h4><p><strong>Clinical Specificity (SP)</strong>, also known as the True Negative Rate, measures the proportion of true negatives correctly identified by the test. Data from a group of subjects who have been confirmed not to have the disease or condition through a gold standard test (<i>D<sub>0</sub></i> in Table 1) are needed to calculate clinical specificity.</p><p>The formula for clinical specificity is:&nbsp;</p><p><i><strong>SP = tn / (tn + fp)</strong></i>, where:&nbsp;</p><ul><li><i><strong>tn</strong></i>, <strong>True Negatives</strong> are the cases where the test correctly identifies the absence of the disease.&nbsp;</li><li><i><strong>fp</strong></i>, <strong>False Positives</strong> are the cases where the test incorrectly identifies the presence of the disease when it is actually absent.&nbsp;</li></ul><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Figure_1_Graphical_representation_of_an_example_of_85ab82a16b.jpg" alt="Eurachem: Figure 1. Graphical representation of an example of tp (D1∩p), tn (D0∩n), fn (D1∩n), and fp (D0∩p). " srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Figure_1_Graphical_representation_of_an_example_of_85ab82a16b.jpg 245w," sizes="100vw" width="1300" height="736"></p><h4><strong>5 - How to calculate the uncertainty of clinical sensitivity and specificity?</strong></h4><p>Calculating clinical sensitivity and specificity uncertainty <strong>involves statistical methods that estimate each parameter's confidence interval (CI)</strong>. These intervals provide a range of values within which the true sensitivity or specificity is expected to lie with a certain level of confidence,<strong> typically 95 %</strong>. Please refer to the AQA:2021 for information about statistical models to compute the 95 % CI [1].</p><h4><strong>6 - How to define targets?&nbsp;</strong></h4><p>Target minimum values for clinical sensitivity and specificity should be identified. These values may originate from regulations or criteria based on the intended use of the binary results. A target or minimum value for the lower limit of the 95 % CI for result rate, i.e., SS or SP, (<i>LL<sub>SS.95</sub> </i>or <i>LL<sub>SP.95</sub></i>) or the upper limit of the 95 % CI for result rate (<i>HL<sub>SS.95</sub></i> or <i>HL<sub>SS.95</sub></i>) should also be defined according to the purpose of the analysis. The target or minimum value (LL<sub>SS</sub><sup>tg </sup>or LL<sub>SP</sub><sup>tg</sup>) is particularly significant when the impact of false results is critical. For example, for blood components used in transfusions, the screening for infectious diseases should be performed with tests associated with an <i>LL<sub>SS.95</sub> </i>close to 100 %.&nbsp;</p><p><strong>Figure 2</strong> illustrates five different tests, each assessed for clinical sensitivity and its associated uncertainty. These cases reflect different levels of compliance with a target sensitivity of 0.5. Case 1 is non-compliant, Cases 2 to 4 are partially compliant, and Case 5 is compliant. From a simplified statistical power view, the laboratory should always take into account the minimum number of samples when defining its target. This number can be estimated by simulation. For example, for a clinical sensitivity of 90 % the evaluation will require a minimum of 10 samples. It should be emphasized that samples must be representative of the target population for a clinical power evaluation - for example, epidemiologically representative samples of the types and subtypes of a given virological agent are required.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Figure_2_Compliance_assessment_with_clinical_sensitivity_a21ece043c.jpg" alt="Eurachem: Figure 2. Compliance assessment with clinical sensitivity uncertainty using the lower 95% confidence interval limit for five performance assessment scenarios. " srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Figure_2_Compliance_assessment_with_clinical_sensitivity_a21ece043c.jpg 245w," sizes="100vw" width="1500" height="648"></p>

Performance Assessment of Binary Output Examinations in Medical Laboratories

<h4><strong>Introduction&nbsp;</strong></h4><p><strong>Millions of tests, measurements and examinations are made every day in thousands of laboratories around the world. There are innumerable reasons underpinning them, for example: as a way of valuing goods for trade purposes; supporting healthcare and construction; checking the quality and safety of food and feed; and in forensic analysis and environmental monitoring. Virtually every aspect of society is supported in some way by analytical work.&nbsp;</strong></p><p>The cost of carrying out these measurements is high and additional costs may arise from decisions made on the basis of the results. For example, tests showing food to be unfit for consumption may result in compensation claims. In addition, tests confirming the presence of banned drugs could result in fines or imprisonment. Clearly it is important to make a correct measurement and be able to show that the result is correct.</p><h4><strong>The validation/verification process</strong></h4><p>Most analysts know that method validation/verification is important, but exactly why, how and when it should be done is not always clear.&nbsp;</p><p>Method validation/verification is the process whereby the laboratory demonstrates whether or not a method is ‘fit for purpose’ (Fig. 1). This means that the tests carried out should be appropriate with respect to uncertainty, cost, time etc. The final report should present analytical data in such a way that the customer can, readily, interpret it and draw appropriate conclusions.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_The_validation_verification_82742c1029.jpg" alt="Eurachem: Fig. 1. The method validation/verification process. The laboratory ‘translates’ the customer’s problem into an analytical requirement, i.e. the method performance required to solve the problem. Method validation/verification includes a stage where various performance characteristics are evaluated and then compared with analytical requirements." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_The_validation_verification_82742c1029.jpg 124w," sizes="100vw" width="821" height="1029"></p><h4><strong>The Eurachem Guide&nbsp;</strong></h4><p>A <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2242"><strong>Guide from Eurachem</strong></a> (Fig. 2) gives practical advice on how method validation/verification can be accomplished. The Guide and its supplements [1-4]:&nbsp;</p><ul><li>Introduce the basic concepts related to method validation and method verification;&nbsp;</li><li>Indicate how to plan, record and report validation and verification studies to best support the statement of ‘fitness for purpose’;&nbsp;</li><li>Provide key definitions and the rationale behind the experiments for assessing the various performance characteristics and related topics (Fig. 3);&nbsp;</li><li>Include quick reference tables that suggest experiments together with the necessary statistical calculations for evaluation and reporting each performance characteristic;&nbsp;</li><li>Provide support to the analyst on how to make the best use of method validation data for setting up an internal quality control plan.</li></ul><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_The_Fitness_for_Purpose_of_Analytical_Methods_95fc1a74e3.jpg" alt="Eurachem: Fig. 2. The Eurachem Guide is available free of charge at www.eurachem.org." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_The_Fitness_for_Purpose_of_Analytical_Methods_95fc1a74e3.jpg 135w," sizes="100vw" width="1062" height="1231"></p><h4><strong>How should methods be validated/verified?</strong></h4><p>The guide focuses on a single-laboratory approach to method validation/verification and gives guidance on planning, carrying out and reporting method validation and verification studies. Any method validation or verification study will require the laboratory to investigate several performance characteristics:</p><ul><li>Precision<ul><li>Repeatability&nbsp;</li><li>Intermediate precision</li></ul></li><li>Trueness</li><li>Selectivity</li><li>Working range</li><li>Analytical sensitivity</li><li>Limit of detection</li><li>Limit of quantification</li><li>Ruggedness</li></ul><p>Exactly which characteristics are studied will depend on the analytical application. Verification of the performance of a standard method requires substantially less work than validation of a method developed in-house. Legislative/sectoral requirements must also be considered.&nbsp;</p><p>Sampling and subsampling can be part of the measurement or testing procedure and must, in those cases, be validated.</p>

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Eurachem is a European network promoting international traceability of chemical measurements and good analytical practice. It provides expert guidance, supports method validation, uncertainty evaluation, proficiency testing, and facilitates discussion on technical and policy issues in analytical quality.

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