Risk-based redesign of internal quality control procedures for emergency immunoassays in clinical laboratories: a multicenter study from China

CLOSING THE LOOP – APPLYING REFERENCE MEASUREMENT SERVICES TO EXTERNAL QUALITY ASSURANCE FOR ROUTINE CLINICAL CHEMISTRY TESTS

Introduction Low between-method bias is vital for interpretation of medical laboratory tests for patient care. For common clinical chemistry tests the manufacturers are responsible for providing reagents, instruments and calibrators which can provide traceable results. The Royal College of Pathologists of Australasia Quality Assurance Program (RCPAQAP) has run an external quality assurance program with presumed commutable materials – The Liquid Serum Chemistry Program - for over 10 years. Currently over 270 laboratories are enrolled measuring up to 60 measurands with 2 or 4 samples per year. In 2022 and 2023 two samples each year were sent for value assignment in JCTLM-listed Reference Measurement Services (RMS). We assess the added utility of performing this RMS testing. Methods Freshly collected serum samples are frozen and rapidly distributed. Laboratories submit results to the RCPAQAP together with supporting information including instrument, reagent manufacturer and method principle. Samples were also sent to either RFB in Germany or WEQAS in Wales for RMS testing for 14 measurands. The following instrument groups were assessed: Abbott Alinity and Architect, Beckman-Coulter AU, QuidelOrtho Vitros, Roche Cobas, and Siemens Atellica and Dimension. Bias assessment was made against the overall method median and against RMS values, using criteria based on Australian common reference intervals, biological variation or expert recommendations. Results The effect of performing the RMS testing added to result interpretation in the following ways. For some tests with acceptable between-method bias for all methods, it was shown that all methods were also unbiased to the RMS results (ALT(+P5P), ALP, creatinine, urate). For tests where one or more method was biased relative to the all-assay median, that most methods had acceptable bias and the outlier method(s) were biased against the RMS result (AST(+P5P) – Dimension low; CK – Vitros low; Cholesterol – Beckman high; Amylase – Dimension low; Calcium – Dimension low; Magnesium – Atellica Low; Triglycerides – Vitros, Roche High). For GGT and Glucose all methods showed a bias to the RMS (negative and positive respectively). For ALP, LDH and cholesterol there was a change in the bias for all methods relative to the RMS between 2022 and 2023. For ALP all methods remained within acceptable bias, but for LDH, while between-method bias was acceptable, for 2022 data several methods exceeded bias limits against the RMS. These inconsistent biases, or all-method biases raise concerns about analyte stability and sample handling for RMS testing which is generally delayed and further afield. Discussion Reference method value assignment for presumed commutable EQA samples can increase confidence that methods working correctly, and can support identification of poorly performing methods. The Measurement Uncertainty of RMS results can be relevant in assessing method bias. Limitations to providing RMS testing include sample stability; required sample volumes; the limited number samples included; and costs. We note that in this study we included only 14 of the measurands in the program. Conclusions Correctly performed RMS testing of commutable EQA materials adds supporting information that manufacturers are supplying traceable assays, and supplies evidence for methods that may need improvement.

Assessment of Analytical Quality in Clinical Laboratory Using Sigma Metrics

Background: Analytical quality in clinical laboratories is crucial for generating reliable test results that directly influence diagnosis and patient management. Traditional indicators, such as precision and accuracy, provide only partial assessment. Six sigma metrics offer a comprehensive, quantitative approach by integrating total allowable error (TEa), bias, and imprecision to evaluate the overall performance of analytical methods. Objectives: To assess the analytical performance of routine biochemical analytes using six sigma metrics and classify analytes according to sigma performance, and to identify analytes that require method improvement. Methods: A retrospective observational study was conducted at Biochemistry department DRPGMC, Tanda, Himachal Pradesh, India, using Internal Quality Control data and External Quality Assessment (EQA) results of 6 months from a clinical biochemistry laboratory. Imprecision (coefficient of variation [CV %]) was calculated from daily quality control (QC) data, and bias (%) was derived from EQA peer-group mean values. TEa% values were adopted from the Clinical Laboratory Improvement Amendments (CLIA) guidelines. Sigma metrics were calculated using the formula: σ = TEa ˗ ∣Bias∣ ÷ CV. Analytes were categorized into high (≥6σ), moderate (3–5.9σ), and low (<3σ) performance groups to guide QC rule selection. Results: Sigma metrics varied across analytes and required the TEa criteria applied. When assessed using the CLIA-88 TEa limits, triglycerides and high-density lipoprotein cholesterol (HDL-C) demonstrated high sigma performance (≥6σ), indicating excellent analytical precision. Moderate sigma performance (3–5.9σ) was observed for glucose, uric acid, alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, total protein, cholesterol (at level 3), and calcium (at level 3), necessitating multi-rule quality control strategies. In contrast, urea, creatinine, albumin, and phosphorus exhibited poor analytical performance with sigma values <3σ, indicating the need for improving the method. However, when sigma metrics were recalculated using the more stringent CLIA-2025 TEa limits, a further decline in analytical performance was observed. Uric acid, liver enzymes, and total protein demonstrated sigma values <3σ under the revised criteria, whereas triglycerides (at level 3) and HDL-C consistently maintained high sigma performance (≥6σ) despite the narrower allowable error limits. Conclusion: Six sigma assessments provided a comprehensive and quantitative measure of analytical quality in a clinical laboratory. Incorporating sigma metrics into routine quality assurance enhances reliability, optimizes QC protocols, and strengthens patient safety.

Long-term analytical performance of apixaban measurements based on external quality assessment data.

OBJECTIVES Although direct oral anticoagulants (DOACs) do not usually require monitoring and clinical cut-off values are not well established yet, measurement of apixaban is often requested in emergency settings and may be requested for patients with suspected variable pharmacokinetics. For safe interpretation, results must be comparable between laboratories and platforms. Most external quality assessment (EQA) schemes, however, only provide short-term performance data. This study aimed to assess the long-term analytical performance of apixaban assays using multicenter EQA data and to identify sources of analytical variation. METHODS Anonymized data from the ECAT program were analyzed. Twice yearly, two lyophilized citrate plasma samples (apixaban range 24-413 ng/mL) were distributed. Consensus values were established, and linear regression of individual laboratory results versus consensus values was performed to calculate slope, intercept, and standard error. Total error, random error, bias (constant and proportional), long-term coefficient of variation (LCVa), and analytical critical difference (ACD) were determined. The effect of platform uniformity was also evaluated. RESULTS Data from 233 laboratories representing 238 method-reagent-calibrator combinations met inclusion criteria. Consensus coefficients of variation were < 10% above 50 ng/mL but increased at lower concentrations, reaching 24.6%. Mean total error was 16.8% and was mainly driven by random error (10.7%). Mean total bias was 33.1 ng/mL, predominantly proportional. The median LCVa was 5% (range 1.7-19.9%), and the median ACD was 34.2 ng/mL. Uniform platforms (same-manufacturer equipment, method, and calibrator) showed significantly lower LCVa and ACD than partially or non-uniform platforms. CONCLUSIONS Apixaban assays demonstrate good long-term precision despite methodological heterogeneity. Proportional bias is the primary source of deviation. Platform harmonization improves reproducibility.

Assay performance verification and reference interval establishment for PIVKA-II on the Roche cobas e 801.

OBJECTIVE To validate the analytical performance of the Roche cobas e 801 chemiluminescent immunoassay for Protein induced by vitamin K absence or antagonist-II (PIVKA-II), establish age-/gender-specific reference intervals for healthy adults in the Gansu population, and evaluate its concordance with the Abbott Alinity i system currently used in our laboratory. METHODS Precision (intra-run/inter-run coefficients of variation [CVs]), linearity (0.50-12000 ng/mL), and clinical reportable range (via 10-fold dilution with 80%-120% recovery criteria) were verified following Clinical and Laboratory Standards Institute (CLSI) and Chinese health industry standards. Agreement between the cobas e 801 and Alinity i systems was assessed using Passing-Bablok regression and Bland-Altman analysis (n = 173). Reference intervals were established based on 2253 healthy participants (≥ 18 years, permanent residents of Lanzhou). The 2.5th-97.5th percentiles were calculated using a nonparametric method, and decision tree analysis was used to determine age stratification cutoffs. RESULTS Intra-run coefficients of variation ranged from 1.36% to 1.57%, and inter-run CVs from 1.13% to 1.16%, all below CLIA'88 total allowable error and manufacturer claims (except for intra-run high-value quality control (QC), which was slightly higher than the manufacturer's specification). The linear regression equation was Y = 0.99X + 6.34 (R2= 0.99), and deviations at all concentration points were < 1/2 Total allowable error (Tea) (11%), meeting linearity requirements. Recoveries after 10-fold dilution ranged from 89.62% to 92.16%, validating the clinical reportable range of 15.30-91533.33 ng/mL. Verification using 20 healthy individuals showed that 100% of results were below the manufacturer's reference interval upper limit (< 28.4 ng/mL). Method comparison revealed that the intercept 95% confidence interval (CI) (-2.16 to 3.42) included 0, indicating no significant constant (systematic) error, while the slope 95% CI (0.4693 to 0.6925) did not include 1, indicating significant proportional bias. Bland-Altman analysis showed that 96.50% (167/173) of data points fell within the limits of agreement, indicating good agreement between the two methods. The reference interval for males (≥ 18 years) was 9.63-29.10 ng/mL, with no age stratification required. For females, age-stratified reference intervals were established: 9.50-26.30 ng/mL for ages 18-54 years, and 9.42-30.00 ng/mL for ages ≥ 55 years. We recommend a unified reference interval of 9.52-29.10 ng/mL for routine clinical use. Age- and sex-stratified intervals are statistically significant but have modest clinical impact (∼3 ng/mL difference in upper limits). CONCLUSION The PIVKA-II assay on the Roche cobas e 801 system meets laboratory quality requirements for analytical performance and is suitable for clinical application. Due to significant proportional bias compared with the Abbott Alinity i system, system-specific reference intervals are recommended, and the two systems should not be used interchangeably. For results approaching the upper reference limit, clinical follow-up is advised. The established local reference intervals can provide more targeted decision-making support for hepatocellular carcinoma screening.

A longitudinal EQA-based process sigma framework for risk-oriented quality management of infectious disease immunoassays.

BACKGROUND Traditional Six Sigma evaluation mainly relies on internal quality control (IQC) data and reflects analytical precision under controlled conditions. However, it may not adequately capture long-term process variation in multicenter laboratory networks. External quality assessment (EQA) provides information on inter-laboratory performance, but single-round EQA results are insufficient for evaluating longitudinal process stability. METHODS Six consecutive EQA rounds from eight clinical laboratories between 2023 and 2025 were analyzed, covering eight infectious disease immunoassays. Each round included five samples, yielding 30 standardized ratios, defined as the measured result divided by the corresponding EQA target value, for each laboratory-assay combination. The dispersion of these longitudinal standardized ratios was summarized as the CV proxy, an empirical indicator of long-term process variation. EQA-derived process sigma was subsequently calculated using long-term systematic bias, study-defined total allowable error, and the CV proxy. Linear mixed-effects modeling was used to estimate the contributions of assay type and laboratory center to process sigma variation. Bootstrap and leave-one-round-out analyses were performed to assess the empirical stability of the CV proxy estimates. Exploratory analyses were conducted to examine associations between operational factors and increased CV proxy. RESULTS Across 64 laboratory-assay combinations, the median process sigma was 4.85, ranging from 1.20 to 12.50. HBeAg showed the lowest median process sigma, whereas anti-HIV, anti-HCV, and HBsAg showed higher values. Assay type explained 58% of process sigma variation, and center-level differences accounted for approximately 20%. Higher CV proxy values showed exploratory associations with calibration delay, reagent lot changes, and insufficient training. CONCLUSIONS CV proxy and EQA-derived process sigma provide complementary tools for long-term process capability assessment and risk-oriented quality management using routinely available EQA data.

An Update on State-of-the-Art Performance for Precision in Medical Laboratories.