Improving measurement uncertainty of plasma electrolytes: a complex but not impossible task

Evaluation of Measurement Uncertainty in Clinical Chemistry and its Comparison With Analytical Performance Specifications

Introduction To evaluate the variability in values reported by a clinical laboratory, it is important to assess the measurement uncertainty (MU). Furthermore, verifying that the estimated MU aligns with relevant analytical performance specifications (APS) is essential. Previous research has indicated variability in how laboratories estimate and apply MU, with some failing to meet APS, potentially affecting clinical decision-making. Additionally, factors such as differences in instrumentation, reagent quality, and calibration protocols may contribute to regional variations in MU, emphasizing the need for a systematic evaluation. This study aimed to determine the MU of 31 measurands and compare it with the APS available in the literature to assess whether our measuring systems can meet these APS. Methods  The study was conducted in the Clinical Biochemistry Laboratory of the Himalayan Institute of Medical Sciences, Dehradun, India. The measuring systems in our laboratory are Beckman Coulter DxC 700 AU (Beckman Coulter, Inc., Brea, California, United States), Beckman Coulter UniCel DxI 800 (Beckman Coulter, Inc.,), and bioMérieux VIDAS (bioMérieux SA, Marcy-l'Étoile, France). The 'top-down' approach which uses internal quality control data and calibrator information was used for the estimation of MU. The formula used was: u result =√(u cal 2 + u Rw 2+ u bias 2). Objectively derived APS available in the literature were utilized to determine the allowable MU. Results A total of 24 measurands exhibited uncertainty estimates below the minimum APS limits. However, serum lactate dehydrogenase (LD), creatine kinase (CK), alkaline phosphatase (ALP), sodium, chloride, glucose, and ferritin showed MU higher than the minimum APS. The calibrator uncertainties (ucal) for ALP (4.7), LD (5.45), CK (11.06), and Ferritin (23.2) were significantly high, contributing to their elevated MU estimates. Additionally, the minimum APS for serum chloride (0.74) and sodium (0.40) were particularly stringent and could not be met. Conclusion The evaluation of MU provides objective insights into the quality of measurement systems and, its comparison, against set APS, supports the applicability of laboratory results in clinical decision-making. Failing to meet APS can lead to misdiagnosis, treatment errors, and patient safety risks. It may also hinder ISO 15189 accreditation and increase retesting costs.

Feasibility of Metrological Traceability Implementation Using the Joint Committee on Traceability in Laboratory Medicine Database Entries Including the Fulfillment of "Fit-for-Purpose" Maximum Allowable Measurement Uncertainty

BACKGROUND

In previous publications, the Task Force on Reference Measurement System Implementation proposed a procedural approach combining a critical review of entries available in the Joint Committee on Traceability in Laboratory Medicine (JCTLM) database with a comparison of this information against analytical performance specifications for measurement uncertainty (MU) and applied it to a group of 13 measurands.

CONTENT

Here we applied this approach to 17 additional measurands, of which measurements are frequently requested. The aims of the study were (a) to describe the main characteristics for implementing traceability and the potential to fulfill the maximum allowable MU (MAU) at the clinical sample level of certified reference materials and reference measurement procedures listed in the JCTLM database; (b) to discuss limitations and obstacles, if any, to the achievement of the required quality of laboratory measurements; and (c) to provide a gap analysis by highlighting what is still missing in the database. Results were integrated with those obtained in the previous study, therefore offering an overview of where we are and what is still missing in the practical application of the metrological traceability concept to 30 common biochemical tests employed in laboratory medicine.

SUMMARY

Our analysis shows that for 28 out of 30 measurands, conditions exist to correctly implement metrological traceability to the International System of units and fulfill at least the MAU of the minimum quality level derived according to internationally recommended models. For 2 measurands (serum albumin and chloride), further improvements in MU of higher-order references would be necessary.

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

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.

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.

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 in vitro diagnostic medical device performance and the average quality of provided results may be obtained.

Verifying measurements on Siemens Atellica® instruments using clinically acceptable analytical performance specifications

Measurements on clinical chemistry analysers must be verified to demonstrate applicability to their intended clinical use. We verified the performance of measurements on the Siemens Atellica® Solution chemistry analysers against the clinically acceptable analytical performance specifications, CAAPS, including the component of intra-individual biological variation, CVI. The relative standard uncertainty of measurement, i.e. analytical variation, CVA, was estimated for six example measurands, haemoglobin A1c in whole blood (B-HbA1c), albumin in urine (U-Alb), and the following measurands in plasma: sodium (P-Na), pancreatic amylase (P-AmylP), low-density lipoprotein cholesterol (P-LDL-C), and creatinine (P-Crea). Experimental CVA was calculated from single-instrument imprecision using control samples, variation between measurements on parallel instruments, and estimation of bias with pooled patient specimens. Each obtained CVA was compared with previously developed CAAPS. The calculated CVA was 1.4% for B-HbA1c (CAAPS 1.9% for single diagnostic testing, CAAPS 2.0% for monitoring after duplicate tests; IFCC units), 10.9% for U-Alb (CAAPS 44.9%), 1.2% for P-Na (CAAPS 0.6%, after triplicate testing 1.5%), 8.2% for P-AmylP (CAAPS 22.9%). The CVA was 4.9% for P-LDL-C (CAAPS for cardiovascular risk stratification 4.9% after four replicates), and 4.2% for P-Crea (CAAPS 8.0%). Three of the six measurands fulfilled the estimated clinical need. Results from P-Na measurements indicate a general need for improving the P-Na assays for emergency patients. It is necessary to consider CVI when creating diagnostic targets for laboratory tests, as emphasised by the CAAPS estimates of B-HbA1c and P-LDL-C.

Clinical decision limits as criteria for setting analytical performance specifications for laboratory tests

BACKGROUND

The biological (CV_I), preanalytical (CV_PRE), and analytical variation (CV_A) are inherent to clinical laboratory testing and consequently, interpretation of clinical test results.

METHODS

The sum of the CV_I, CV_PRE, and CV_A, called diagnostic variation (CV_D), was used to derive clinically acceptable analytical performance specifications (CAAPS) for clinical chemistry measurands. The reference change concept was applied to clinically significant differences (CD) between two measurements, with the formula CD = z*√2* CV_D. CD for six measurands were sought from international guidelines. The CAAPS were calculated by subtracting variances of CV_I and CV_PRE from CV_D. Modified formulae were applied to consider statistical power (1-β) and repeated measurements.

RESULTS

The obtained CAAPS were 44.9% for urine albumin, 0.6% for plasma sodium, 22.9% for plasma pancreatic amylase, and 8.0% for plasma creatinine (z = 3, α = 2.5%, 1-β = 85%). For blood HbA_1c and plasma low-density lipoprotein cholesterol, replicate measurements were necessary to reach CAAPS for patient monitoring. The derived CAAPS were compared with analytical performance specifications, APS, based on biological variation.

CONCLUSIONS

The CAAPS models pose a new tool for assessing APS in a clinical laboratory. Their usability depends on the relevance of CD limits, required statistical power and the feasibility of repeated measurements.

Performance specifications for sodium should not be based on biological variation

When increasing the quality in clinical laboratories by decreasing measurement uncertainty, reliable methods are needed not only to quantify the performance of measuring systems, but also to set goals for the performance. Sigma metrics used in medical laboratories for documenting and expressing levels of performance, are evidently totally dependent on the "total permissible error" used in the formulas. Although the conventional biological variation (BV) based model for calculation of the permissible (or allowable) total error is commonly used, it has been shown to be flawed. Alternative methods are proposed, mainly also based on the within-subject BV. Measurement uncertainty models might offer an alternative to total error models. Defining the limits for analytical quality still poses a challenge in both models. The aim of the present paper is to critically discuss current methods for establishing performance specifications by using the measurement of sodium concentrations in plasma or serum. Sodium can be measured with high accuracy but fails by far to meet conventional performance specifications based on BV. Since the use of sodium concentrations is well established for supporting clinical care, we question the concept that quality criteria for sodium and similar analytes that are under strict homeostatic control are best set by biology.

Redesigning the surveillance of in vitro diagnostic medical devices and of medical laboratory performance by quality control in the traceability era

IVD manufacturers have total responsibility in terms of the traceability of marketed in vitro diagnostic medical devices (IVD-MD). This includes the provision of a quality control (QC) material as a part of the measuring system, suitable for traceability verification and alignment surveillance by end-users in daily practice. This material [to be used for the internal QC (IQC) component I as described in this paper] should have unbiased target values and an acceptability range corresponding to analytical performance specifications (APS) for suitable (expanded) measurement uncertainty (MU) on clinical samples. On the other hand, medical laboratories (by the IQC component II as described in this paper) should improve the IQC process and its judging criteria to establish a direct link between their performance, estimated as MU of provided results, and APS defined according to recommended models to apply corrective actions if the performance is worsening with the risk to jeopardize the clinical validity of test results. The participation to external quality assessment (EQA) programs that meet specific metrological criteria is also central to the evaluation of performance of IVD-MDs and of medical laboratories in terms of harmonization and clinical suitability of their measurements. In addition to the use of commutable materials, in this type of EQA it is necessary to assign values to them with selected reference procedures and to define and apply maximum allowable APS to substantiate the suitability of laboratory measurements in the clinical setting.

Optimizing Available Tools for Achieving Result Standardization: Value Added by Joint Committee on Traceability in Laboratory Medicine (JCTLM)

BACKGROUND

The JCTLM created a Task Force on Reference Measurement System Implementation (TF-RMSI) to provide guidance on metrological traceability implementation for the in vitro diagnostics (IVD) community.

CONTENT

TF-RMSI investigated the reference measurement systems (RMS) for 13 common measurands by applying the following procedural steps: (a) extracting data from the JCTLM database of available certified reference materials (CRMs) and reference measurement procedures (RMPs); (b) describing the RMS to which each recruited CRM or RMP belongs; (c) identifying the intended use of the CRMs, and, if used as a common calibrator for IVD measuring systems and/or trueness assessment of field methods was included, checking the CRM's certificate for information about commutability with clinical samples; and (d) checking if the CRM or RMP measurement uncertainty (MU) has the potential to be small enough to avoid significantly affecting the analytical performance specifications (APS) for MU of clinical sample results when the MU from the IVD calibrator and from the end-user measuring system were combined.

SUMMARY

We produced a synopsis of JCTLM-listed higher-order CRMs and RMPs for the selected measurands, including their main characteristics for implementing traceability and fulfilling (or not) the APS for suitable MU. Results showed that traceability to higher-order references can be established by IVD manufacturers within the defined APS for most of the 13 selected measurands. However, some measurands do not yet have suitable CRMs for use as common calibrators. For these measurands, splitting clinical samples with a laboratory performing the RMP may provide a practical alternative for establishing a calibration hierarchy.

Performance specifications for measurement uncertainty of common biochemical measurands according to Milan models

OBJECTIVES

Definition and fullfillment of analytical performance specifications (APS) for measurement uncertainty (MU) allow to make laboratory determinations clinically usable. The 2014 Milan Strategic Conference have proposed models to objectively derive APS based on: (a) the effect of analytical performance on clinical outcome; (b) biological variation components; and (3) the state of the art of the measurement, defined as the highest level of analytical performance technically achievable. Using these models appropriately, we present here a proposal for defining APS for standard MU for some common biochemical measurands.

METHODS

We allocated a group of 13 measurands selected among the most commonly laboratory requested tests to each of the three Milan models on the basis of their biological and clinical characteristics. Both minimum and desirable levels of quality of APS for standard MU of clinical samples were defined by using information obtained from available studies.

RESULTS

Blood total hemoglobin, plasma glucose, blood glycated hemoglobin, and serum 25-hydroxyvitamin D3 were allocated to the model 1 and the corresponding desirable APS were 2.80, 2.00, 3.00, and 10.0%, respectively. Plasma potassium, sodium, chloride, total calcium, alanine aminotransferase, creatinine, urea, and total bilirubin were allocated to the model 2 and the corresponding desirable APS were 1.96, 0.27, 0.49, 0.91, 4.65, 2.20, 7.05, and 10.5%, respectively. For C-reactive protein, allocated to the model 3, a desirable MU of 3.76% was defined.

CONCLUSIONS

APS for MU of clinical samples derived in this study are essential to objectively evaluate the reliability of results provided by medical laboratories.