Analytical Performance Specifications Research Articles

Evaluation of measurement uncertainty for 19 clinical chemistry analytes and comparison with analytical performance specifications

Evaluation of measurement uncertainty for 19 clinical chemistry analytes and comparison with analytical performance specifications

Analytical performance specifications for plasma copeptin based on outcome and biological variation data

Analytical performance specifications for plasma copeptin based on outcome and biological variation data

Outcome-based analytical performance specifications – Current status and future directions

Outcome-based analytical performance specifications – Current status and future directions

Using analytical performance specifications in a medical laboratory.

Analytical performance specifications (APS) are used for the quantitative assessment of assay analytical performance, with the aim of providing information appropriate for clinical care of patients. One of the major locations where APS are used is in the routine clinical laboratory. These may be used to assess and monitor assays in a range of settings including method selection, method verification or validation, external quality assurance, internal quality control and assessment of measurement uncertainty. The aspects of assays that may be assessed include imprecision, bias, selectivity, sample type, analyte stability and interferences. This paper reviews the practical use of APS in a routine clinical laboratory, using the laboratory I supervise as an example.

The role of analytical performance specifications in international guidelines and standards dealing with metrological traceability in laboratory medicine.

The goal of metrological traceability is to have equivalent results for a measurand in clinical samples (CSs) irrespective of the in-vitro diagnostic medical device (IVD-MD) used for measurements. The International Standards Organization standard 17511 defines requirements for establishing metrological traceability of values assigned to calibrators, trueness control materials and human samples used with IVD-MDs. Each step in metrological traceability has an uncertainty associated with the value assigned to a material. The uncertainty at each step adds to the uncertainty from preceding steps such that the combined uncertainty gets larger at each step. The combined uncertainty fora CS result must fulfil an analytical performance specification (APS) for the maximum allowable uncertainty (umax CS). The umax CS can be partitioned among the steps in a metrological traceability calibration hierarachy to derive the APS for maximum allowable uncertainty at each step. Similarly, the criterion for maximum acceptable noncommutability bias can be derived from the umax CS. One of the challenges in determining if umax CS is fulfilled is determining the repeatability uncertainty (u Rw) from operating an IVD-MD within a clinical laboratory. Most of the current recommendations for estimating u Rw from internal quality control data do not use a sufficiently representative time interval to capture all relevant sources of variability in measurement results. Consequently, underestimation of u Rw is common and may compromise assessment of how well current IVD-MDs and their supporting calibration hierarchies meet the needs of clinical care providers.

Biological Variation Estimates for Plasma Copeptin and Clinical Implications.

Plasma copeptin measurement is useful for the differential diagnoses of polyuria-polydipsia syndrome. It has also been proposed as a prognostic marker for cardiovascular diseases. However, limited information is available about the within- (CVI) and between-subject (CVG) biological variation (BV). This study presents BV estimates for copeptin in healthy individuals. Samples were collected weekly from 41 healthy subjects over 5 weeks and analyzed using the BRAHMS Copeptin proAVP KRYPTOR assay after at least 8 h of food and fluid abstinence. Outlier detection, variance homogeneity, and trend analysis were performed followed by CV-ANOVA for BV and analytical variation (CVA) estimation with 95% confidence intervals. Reference change values (RCVs), index of individuality (II), and analytical performance specification (APS) were also calculated. The analysis included 178 results from 20 males and 202 values from 21 females. Copeptin concentrations were significantly higher in males than in females (mean 8.5 vs 5.2 pmol/L, P < 0.0001). CVI estimates were 18.0% (95% CI, 15.4%-21.6%) and 19.0% (95% CI, 16.4%-22.6%), for males and females, respectively; RCVs were -35% (decreasing value) and 54% (increasing value). There was marked individuality for copeptin. No result exceeded the diagnostic threshold (>21.4 pmol/L) for arginine vasopressin resistance. The availability of BV data allows for refined APS and associated II, and RCVs applicable as aids in the serial monitoring of patients with specific diseases such as heart failure. The BV estimates are only applicable in subjects who abstained from oral intake due to the rapid and marked effects of fluids on copeptin physiology.

Analytical performance specifications based on biological variation data- considerations, strengths and limitations.

Analytical performance specifications (APS) are typically established through one of three models: (i)outcome studies, (ii) biological variation (BV), or (iii) state-of-the-art. Presently, The APS can, for most measurands that have a stable concentration, be based on BV. BV based APS, defined for imprecision, bias, total allowable error and allowable measurement uncertainty, are applied to many different processes in the laboratory. When calculating APS, it is important to consider the different APS formulae, for what setting they are to be applied and if they are suitable for the intended purpose. In this opinion paper, we elucidate the background, limitations, strengths, and potential intended applications of the different BV based APS formulas. When using BV data to set APS, it is important to consider that all formulae are contingent on accurate and relevant BV estimates. During the last decade, efficient procedures have been established to obtain reliable BV estimates that are presented in the EFLM biological variation database. The database publishes detailed BV data for numerous measurands, global BV estimates derived from meta-analysis of quality-assured studies of similar study design and automatic calculation of BV based APS.

Pre-analytical stability of the CEA, CYFRA 21.1, NSE, CA125 and HE4 tumor markers.

For lung cancer, circulating tumor markers (TM) are available to guide clinical treatment decisions. To ensure adequate accuracy, pre-analytical instabilities need to be known and addressed in the pre-analytical laboratory protocols. This study investigates the pre-analytical stability of CA125, CEA, CYFRA 21.1, HE4 and NSE for the following pre-analytical variables and procedures; i) whole blood stability, ii) serum freeze-thaw cycles, iii) electric vibration mixing and iv) serum storage at different temperatures. Left-over patient samples were used and for every investigated variable six patient samples were used and analysed in duplicate. Acceptance criteria were based on analytical performance specifications based on biological variation and significant differences with baseline. Whole blood was stable for at least 6 hours for all TM except for NSE. Two freeze-thaw cycles were acceptable for all TM except CYFRA 21.1. Electric vibration mixing was allowed for all TM except for CYFRA 21.1. Serum stability at 4°C was 7 days for CEA, CA125, CYFRA 21.1 and HE4 and 4 hours for NSE. Critical pre-analytical processing step conditions were identified that, if not taken into account, will result in reporting of erroneous TM results.

How clinical laboratories select and use Analytical Performance Specifications (APS) in Italy.

Even if the topic of the analytical quality required to provide laboratory results "fit for purpose" exists since the beginning of the modern medical laboratory, there is the suspect that the expression "Analytical Performance Specifications" (APS) is not well-known. To investigate this aspect a survey was conducted. A questionnaire with seven questions related to the knowledge about the topic, the sources of information and the criteria used by the laboratories to set the APS and their applications was prepared. It was distributed to all the clinical pathology laboratories of Lombardy Region (143) and to the members of SIBioC Laboratory Medicine (excluding Lombardy). We received 201 replies: 127 from Lombardy and 74 from the rest of Italy. Fifteen percent declared to ignore the meaning ofAPS and only 64 % of those knowing the meaning of theterm declared to use them in the daily practice. The state-of-the-art was the principle used more frequently to setAPS(about 48 %) followed by biological variation (41 %), and APS were typically applied to set goals for Internal Quality Control for selected measurands. Usually imprecision or total error APS were used, much less frequently uncertainty APS. In fact only 27 % of the laboratories declared to have calculated the measurement uncertainty for part or the majority of their measurands. Even considering the limits of a survey that relies upon self-declarations, it appears clearly that, at list in Italy, there is some work to be done to promote the concept and the use of APS.

Analytical Performance Specifications for Input Variables: Investigation of the Model of End-Stage Liver Disease.

Artificial intelligence models constitute specific uses of analysis results and, therefore, necessitate evaluation of analytical performance specifications (APS) for this context specifically. The Model of End-stage Liver Disease (MELD) is a clinical prediction model based on measurements of bilirubin, creatinine, and the international normalized ratio (INR). This study evaluates the propagation of error through the MELD, to inform choice of APS for the MELD input variables. A total of 6093 consecutive MELD scores and underlying analysis results were retrospectively collected. "Desirable analytical variation" based on biological variation as well as current local analytical variation was simulated onto the data set as well as onto a constructed data set, representing a worst-case scenario. Resulting changes in MELD score and risk classification were calculated. Biological variation-based APS in the worst-case scenario resulted in 3.26% of scores changing by ≥1 MELD point. In the patient-derived data set, the same variation resulted in 0.92% of samples changing by ≥1 MELD point, and 5.5% of samples changing risk category. Local analytical performance resulted in lower reclassification rates. Error propagation through MELD is complex and includes population-dependent mechanisms. Biological variation-derived APS were acceptable for all uses of the MELD score. Other combinations of APS can yield equally acceptable results. This analysis exemplifies how error propagation through artificial intelligence models can become highly complex. This complexity will necessitate that both model suppliers and clinical laboratories address analytical performance specifications for the specific use case, as these may differ from performance specifications for traditional use of the analyses.

Issues in assessing analytical performance specifications in healthcare systems assembling multiple laboratories and measuring systems.

Analytical performance specifications (APS) are usually compared to the intermediate reproducibility uncertainty of measuring a particular measurand using a single invitro diagnostic medical device (IVD MD). Healthcare systems assembling multiple laboratories that include several IVD MDs and cater to patients suffering from long-term disease conditions mean that samples from apatient are analyzed using a few IVD MDs, sometimes fromdifferent manufacturers, but rarely all IVD MDs in thehealthcare system. The reproducibility uncertainty for results of a measurand measured within a healthcare system and the components of this measurement uncertainty is useful in strategies to minimize bias and overall measurement uncertainty within the healthcare system. The root mean squares deviation (RMSD) calculated as the sample standard deviation (SD) and relative SD includes both imprecision and bias and is appropriate for expressing such uncertainties. Results from commutable stabilized internal and external control samples, from measuring split natural patient samples or using big-data techniques, are essential in monitoring bias and measurement uncertainties in healthcare systems. Variance component analysis (VCA) can be employed to quantify the relative contributions of the most influential factors causing measurement uncertainty. Such results represent invaluable information for minimizing measurement uncertainty in the interest of the healthcare system's patients.

The European biological variation study (EuBIVAS): Biological variation data for testosterone, follicle stimulating hormone, prolactin, luteinizing hormone and dehydroepiandrosterone sulfate in men

BackgroundKnowledge of biological variation (BV) of hormones is essential for interpretation of laboratory tests and for diagnostics of endocrinological and reproductive diseases. There is a lack of robust BV data for many hormones in men. MethodsWe used serum samples collected weekly over 10 weeks from the European Biological Variation Study (EuBIVAS) to determine BV of testosterone, follicle-stimulating hormone (FSH), prolactin, luteinizing hormone (LH) and dehydroepiandrosterone sulfate (DHEA-S) in 38 men. We derived within-subject (CVI) and between-subject (CVG) BV estimates by CV-ANOVA after trend, outlier, and homogeneity analysis and calculated reference change values, index of individuality (II), and analytical performance specifications. ResultsThe CVI estimates were 10 % for testosterone, 8 % for FSH, 13 % for prolactin, 22 % for LH, and 9 % for DHEA-S, respectively. The IIs ranged between 0.14 for FSH to 0.66 for LH, indicating high individuality. ConclusionsIn this study, we have used samples from the highly powered EuBIVAS study to derive BV estimates for testosterone, FSH, prolactin, LH and DHEA-S in men. Our data confirm previously published BV estimates of testosterone, FSH and LH. For prolactin and DHEA-S BV data for men are reported for the first time.

When bias becomes part of imprecision: how to use analytical performance specifications to determine acceptability of lot-lot variation and other sources of possibly unacceptable bias.

ISO 15189 requires laboratories to estimate the uncertainty of their quantitative measurements and to maintain them within relevant performance specifications. Furthermore, it refers to ISO TS 20914 for instructions on how to estimate the uncertainty and what to take into consideration when communicating uncertainty of measurement with requesting clinicians. These instructions include the responsibility of laboratories to verify that bias is not larger than medically significant. If estimated to be larger than acceptable, such bias first needs to be eliminated or (temporarily) corrected for. In the latter case, the uncertainty of such correction becomes part of the estimation of the total measurement uncertainty. If small enough to be acceptable, bias becomes part of the long term within laboratory random variation. Sources of possible bias are (not limited to) changes in reagent or calibrator lot variation or calibration itself. In this paper we clarify how the rationale and mathematics from an EFLM WG ISO/A position paper on allowable between reagent lot variation can be applied to calculate whether bias can be accepted to become part of long-term imprecision. The central point of this rationale is to prevent the risk that requesting clinicians confuse changes in bias with changes in the steady state of their patients.

To rule-in, or not to falsely rule-out, that is the question: evaluation of hs-cTnT EQA performance in light of the ESC-2020 guideline.

To accurately evaluate non-ST-elevated acute cardiac syndrome (NSTE-ACS), the quality of high-sensitive cardiac troponin (hs-cTn) assays is of vital importance. The 2020 revision of the NSTE-ACS guideline includes clinical decision-limits (CDL's) to both rule-in and rule-out NSTE-ACS for most commercially available platforms, providing both 0/1 h and 0/2 h delta limits. Our study evaluated whether laboratories are able to meet the analytical performance specifications for imprecision (APS) for hs-cTnT. Results from external quality assurance (EQA) in commutable samples were used to evaluate the current and historic performance of analyzers. The performance of analyzers that either passed or failed to comply with 0/1 h-APS were used on a real-world dataset of first hs-cTnT-values to simulate 10.000 samples of t=0, t=1 and t=2 h values with multiple delta's for all relevant CDL's. We compared the simulated values to the input values to obtain the percentage of aberrant results simulated. The majority of analyzers complies with APS for rule-in in 2022 (0/1 h: 90.4 % and 0/2 h: 100 %), compliance for the 0/1 h rule-out is still far from optimal (0/1 h: 30.7 %, 0/2 h: 75.4 %), with improving compliance over the past years (rule-in p=<0.0001, rule-out p=0.011, χ2). Whilst 0/1 h-APS-passing analyzers have a minute risk to falsely rule-out patients whom should be ruled-in (0.0001 %), failing performance increases this risk to 2.1 % upon using 0/1 h CDL's. Here, adopting 0/2 h CDL's is favorable (0.01 %). Laboratories that fail to meet hs-cTnT 0/1 h-APS should improve their performance to the required and achievable level. Until performance is reached clinics should adopt the 0/2 h CDL's.

State-of-the-art model for derivation of analytical performance specifications: how to define the highest level of analytical performance technically achievable.

To be accurate and equivalent among assays, laboratory results should be traceable to higher-order references and their quality should fulfill maximum allowable measurement uncertainty (MU) as defined to fit the intended clinical use. Accordingly, laboratory professionals should estimate and validate MU of performed tests using appropriate analytical performance specifications (APS). Current consensus supports the derivation of APS by using one of the three models established by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Strategic Conference held in Milan in 2014. It is recognized that some models are better suited for certain measurands than for others and the attention should be primarily directed towards their biological and clinical characteristics. Among others, model 3 should reflect the state of the art of the measurements that can be defined as the best analytical performance that is technically achievable. Taking serum C-reactive protein and ferritin as examples, here we describe the theoretical premises and the experimental protocol to be used to derive APS for MU when a measurand is allocated to this model. Although the model lacks a direct relationship with clinical outcomes, useful information about the invitro diagnostic medical device performance and the average quality of provided results may be obtained.

Analytical performance specifications for combined uncertainty budget in the implementation of metrological traceability.

In addition to the correct implementation of calibration traceability, the definition and fulfillment of maximum allowable measurement uncertainty (MAU) are essential in assuring that laboratory measurements are clinically usable. Across the entire calibration hierarchy, three major contributors to the measurement uncertainty (MU) budget are identified, starting with the higher-order reference providers, extending through the in vitro diagnostic (IVD) manufacturers and their processes for assigning calibrator values, and ending with medical laboratories generating the random variability of results reported to clinicians. To understand if it is possible to achieve MAU and, consequently, to fix the possible drawbacks, the definition of combined MU budget limits across the entire calibration hierarchy has a central role. In particular, quality specifications for MU of reference and commercial calibrator materials should be defined according to the MAU on clinical samples. All involved stakeholders (i.e., higher-order reference providers, IVD manufacturers, medical laboratories) should be prepared to improve their performance whenever the clinical application of the test is made questionable by the failure to achieve MAU.

What the Milan conference has taught us about analytical performance specification model definition and measurand allocation

Abstract Analytical performance specifications (APS) represent the criteria that specify the quality required for laboratory test information to satisfy clinical needs. In 2014 the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) considered timely to update the topic of APS by organizing a conference in Milan in which some strategic concepts were proposed. Here I summarize the essential points representing the EFLM Strategic Conference heritage and discuss the approaches that will permit us to become more concrete, including roles and main actions expected from each of involved stakeholders for contributing a quantum leap forward in the way of practicality of Milan consensus about APS.

Are analytical performance specifications derived from reference intervals of any use in the veterinary clinical laboratory? A preliminary study on the empirical biological variation model.

Analytical performance specifications (APS) are vital for method evaluation and quality control validation. However, the limited availability of biological variation (BV) data, regulatory guidelines, and expert opinion (EO) may present challenges in veterinary medicine. The empirical biological variation (EBV) approach, based on population reference intervals (pRI), has emerged as an alternative method to derive APS in human medicine. This study aimed to assess the practicality and usefulness of the EBV approach in deriving performance limits for various measurands in dogs and cats. Eight hematology and 13 biochemistry measurands were analyzed in dogs and cats. Estimates of combined biologic variation based on traditional biological (CVB ) and EBV-derived (CVE *) formulas were calculated and assessed for evidence of correlation. Performance limits for expanded uncertainty/total error and imprecision were compared among EO, BV, and EBV. Strong and significant correlations were found between CVB and CVE * for both dogs (r = .86, p < .00001) and cats (r = 0.95, p < .00001). The EBV-derived APS were generally comparable to EO and BV, with a subjective criterion of 1.5% difference for imprecision and 3% for total error/expanded uncertainty. The EBV approach, using pRI, shows promise as a surrogate marker for biological variation and as a practical tool for determining performance limits in dogs and cats. Assuming accurate pRI generated on analyzers with stable analytical performance, this approach could offer benefits when expert recommendations or robust BV studies are lacking or yield conflicting results. Further research is needed to explore the applicability and advantages of the EBV in veterinary medicine.

Analysis of HbA1c using microfluidic card (Capitainer qDBS card) as a pre-step before determination of the HbA1c value with an immunological method

The objective of the study was to evaluate Capitainer’s quantitative dried blood spots (qDBS) card for Hemoglobin A1c (HbA1c) testing. qDBS cards can be used for at-home sampling for HbA1c determination in a Swedish laboratory setting. A total of 153 routine requested HbA1c samples were used in this evaluation of microfluidic cards (qDBS). The HbA1c was extracted from the disc and HbA1c was determined at cobas 6000 instruments with immunological technology. The results were compared with results from traditional venous HbA1c testing. The reproducibility of using this elution procedure was 4.0% measured as coefficient of variation at a HbA1c concentration of 51 mmol/mol. Analytical performance specifications for HbA1c < 52 mmol/mol using DBS card (c501) compared with assigned values from Capillarys 3 was (y) = 1.03 x Capillarys 3(x) − 0.87; R2 = 0.97. There is a good agreement between HbA1c determined by traditional HbA1c testing and determination from Capitainer’s qDBS cards. This shows that the technology could be used for out-of doctor’s office testing.

Specifications of qPCR based epigenetic immune cell quantification.

Immune monitoring is an important aspect indiagnostics and clinical trials for patients with compromised immune systems. Flow cytometry is the standard method forimmune cell counting but faces limitations. Bestpracticeguidelines are available, but lack of standardization complicates compliance with e.g., invitro diagnostic regulations. Limited sample availability forces immune monitoring to predominantly use population-based reference intervals. Epigenetic qPCR has evolved asalternative with broad applicability and low logistical demands. Analytical performance specifications (APS) havebeen defined for qPCR in several regulated fields including testing of genetically modified organisms or vector-shedding. APS were characterized using five epigenetic qPCR-based assays quantifying CD3+, CD4+, CD8+ T, B and NK cells in light of regulatory requirements. Epigenetic qPCR meets all specifications including bias, variability, linearity, ruggedness and sample stability as suggested by pertinent guidelines and regulations. The assays were subsequently applied to capillary blood from 25 normal donors over a 28-day period. Index of individuality (IoI) and reference change values were determined to evaluate potential diagnostic gains of individual reference intervals. Analysis of the IoI suggests benefits for individual over population-based references. Reference change values (RCVs) show that changes of approx. Fifty percent from prior measurement are suggestive for clinically relevant changes in any of the 5 cell types. The demonstrated precision, long-term stability and obtained RCVs render epigenetic cell counting a promising tool for immune monitoring in clinical trials and diagnosis.