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Reference intervals depend on the distribution of results within a reference population and can be influenced by subclinical disease. Functional reference limits present an opportunity to derive clinically relevant reference limits from routinely collected data sources, which consist of mixed populations of unhealthy and healthy groups. Serum ferritin is a good example of the utility of functional reference limits. Several studies have identified clinically relevant reference limits through examining the relationship between serum ferritin and erythrocyte parameters. These ferritin functional limits often represent the inflection point at which erythrocyte parameters change significantly. Comparison of ferritin functional reference limits with those based on population distributional reference limits reveals that the lower reference limit may fall below the point at which patients become clinically unwell. Functional reference limits may be considered for any biomarker that exhibits a correlated relationship with other biomarkers.

In this paper, we discuss the Bile Acid Comparison and Harmonisation project, a sub-study of the Trial of URsodeoxycholic acid vs RIFampicin in early-onset severe Intrahepatic Cholestasis of pregnancy, giving an overview of the current state of affairs for total bile acid measurements. [ABSTRACT FROM AUTHOR]

In this computer simulation study, we examine four different statistical approaches of linearity assessment, including two variants of deviation from linearity (individual (IDL) and averaged (AD)), along with detection capabilities of residuals of linear regression (individual and averaged). From the results of the simulation, the following broad suggestions are provided to laboratory practitioners when performing linearity assessment. A high imprecision can challenge linearity investigations by producing a high false positive rate or low power of detection. Therefore, the imprecision of the measurement procedure should be considered when interpreting linearity assessment results. In the presence of high imprecision, the results of linearity assessment should be interpreted with caution. Different linearity assessment approaches examined in this study performed well under different analytical scenarios. For optimal outcomes, a considered and tailored study design should be implemented. With the exception of specific scenarios, both ADL and IDL methods were suboptimal for the assessment of linearity compared. When imprecision is low (3 %), averaged residual of linear regression with triplicate measurements and a non-linearity acceptance limit of 5 % produces <5 % false positive rates and a high power for detection of non-linearity of >70 % across different types and degrees of non-linearity. Detection of departures from linearity are difficult to identify in practice and enhanced methods of detection need development. [ABSTRACT FROM AUTHOR]

Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers, and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the Laboratory Evaluation and Analytical Performance Characteristics (LEAP) checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners. [ABSTRACT FROM AUTHOR]

Objectives An increase in analytical imprecision and/or the introduction of bias can affect the interpretation of quantitative laboratory results. In this study, we explore the impact of varying assay imprecision and bias introduction on the classification of patients based on fixed thresholds. Methods Simple spreadsheets (Microsoft Excel) were constructed to simulate conditions of assay deterioration, expressed as coefficient of variation and bias (in percentages). The impact on patient classification was explored based on fixed interpretative limits. A combined matrix of imprecision and bias of 0%, 2%, 4%, 6%, 8%, and 10% (tool 1) as well as 0%, 2%, 5%, 10%, 15%, and 20% (tool 2) was simulated, respectively. The percentage of patients who were reclassified following the addition of simulated imprecision and bias was summarized and presented in tables and graphs. Results The percentage of patients who were reclassified increased with increasing/decreasing magnitude of imprecision and bias. The impact of imprecision lessens with increasing bias such that at high biases, the bias becomes the dominant cause for reclassification. Conclusions The spreadsheet tools, available as Supplemental Material , allow laboratories to visualize the impact of additional analytical imprecision and bias on the classification of their patients when applied to locally extracted historical results. [ABSTRACT FROM AUTHOR]

KEY POINTS: Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy liver disease, characterised by pruritus and increased total serum bile acids (TSBA), Australian incidence 0.6–0.7%.ICP is diagnosed by non‐fasting TSBA ≥19 μmol/L in a pregnant woman with pruritus without rash without a known pre‐existing liver disorder.Peak TSBA ≥40 and ≥100 μmol/L identify severe and very severe disease respectively, associated with spontaneous preterm birth when severe, and with stillbirth, when very severe.Benefit‐vs‐risk for iatrogenic preterm birth in ICP remains uncertain.Ursodeoxycholic acid remains the best pharmacotherapy preterm, improving perinatal outcome and reducing pruritus, although it has not been shown to reduce stillbirth. [ABSTRACT FROM AUTHOR]

Functional reference limits describe key changes in the physiological relationship between a pair of physiologically related components. Statistically, this can be represented by a significant change in the curvature of a mathematical function or curve (e.g., an observed plateau). The point at which the statistical relationship changes significantly is the point of curvature inflection and can be mathematically modeled from the relationship between the interrelated biomarkers. Conceptually, they reside between reference intervals, which describe the statistical boundaries of a single biomarker within the reference population, and clinical decision limits that are often linked to the risk of morbidity or mortality and set as thresholds. Functional reference limits provide important physiological and pathophysiological insights that can aid laboratory result interpretation. Laboratory professionals are in a unique position to harness data from laboratory information systems to derive clinically relevant values. Increasing research on and reporting of functional reference limits in the literature will enhance their contribution to laboratory medicine and widen the evidence base used in clinical decision limits, which are currently almost exclusively contributed to by clinical trials. Their inclusion in laboratory reports will enhance the intellectual value of laboratory professionals in clinical care beyond the statistical boundaries of a healthy reference population and pave the way to them being considered in shaping clinical decision limits. This review provides an overview of the concepts related to functional reference limits, clinical examples of their use, and the impetus to include them in laboratory reports. [ABSTRACT FROM AUTHOR]

Lot-to-lot verification is an integral component for monitoring the long-term stability of a measurement procedure. The practice is challenged by the resource requirements as well as uncertainty surrounding experimental design and statistical analysis that is optimal for individual laboratories, although guidance is becoming increasingly available. Collaborative verification efforts as well as application of patient-based monitoring are likely to further improve identification of any differences in performance in a relatively timely manner. Appropriate follow up actions of failed lot-to-lot verification is required and must balance potential disruptions to clinical services provided by the laboratory. Manufacturers need to increase transparency surrounding release criteria and work closer with laboratory professionals to ensure acceptable reagent lots are released to end users. A tripartite collaboration between regulatory bodies, manufacturers, and laboratory medicine professional bodies is key to developing a balanced system where regulatory, manufacturing, and clinical requirements of laboratory testing are met, to minimize differences between reagent lots and ensure patient safety. Clinical Chemistry and Laboratory Medicine has served as a fertile platform for advancing the discussion and practice of lot-to-lot verification in the past 60 years and will continue to be an advocate of this important topic for many more years to come. [ABSTRACT FROM AUTHOR]

Method evaluation is one of the critical components of the quality system that ensures the ongoing quality of a clinical laboratory. As part of implementing new methods or reviewing best practices, the peer-reviewed published literature is often searched for guidance. From the outset, Clinical Chemistry and Laboratory Medicine (CCLM) has a rich history of publishing methods relevant to clinical laboratory medicine. An insight into submissions, from editors' and reviewers' experiences, shows that authors still struggle with method evaluation, particularly the appropriate requirements for validation in clinical laboratory medicine. Here, we consider through a series of discussion points an overview of the status, challenges, and needs of method evaluation from the perspective of clinical laboratory medicine. We identify six key high-level aspects of clinical laboratory method evaluation that potentially lead to inconsistency. 1. Standardisation of terminology, 2. Selection of analytical performance specifications, 3. Experimental design of method evaluation, 4. Sample requirements of method evaluation, 5. Statistical assessment and interpretation of method evaluation data, and 6. Reporting of method evaluation data. Each of these areas requires considerable work to harmonise the practice of method evaluation in laboratory medicine, including more empirical studies to be incorporated into guidance documents that are relevant to clinical laboratories and are freely and widely available. To further close the loop, educational activities and fostering professional collaborations are essential to promote and improve the practice of method evaluation procedures. [ABSTRACT FROM AUTHOR]

Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers, and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the LEAP checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners. [ABSTRACT FROM AUTHOR]

Background: Calibration is a critical component for the reliability, accuracy, and precision of mass spectrometry measurements. Optimal practice in the construction, evaluation, and implementation of a new calibration curve is often underappreciated. This systematic review examined how calibration practices are applied to liquid chromatography-tandem mass spectrometry measurement procedures. Methods: The electronic database PubMed was searched from the date of database inception to April 1, 2022. The search terms used were "calibration," "mass spectrometry," and "regression." Twenty-one articles were identified and included in this review, following evaluation of the titles, abstracts, full text, and reference lists of the search results. Results: The use of matrix-matched calibrators and stable isotope-labeled internal standards helps to mitigate the impact of matrix effects. A higher number of calibration standards or replicate measurements improves the mapping of the detector response and hence the accuracy and precision of the regression model. Constructing a calibration curve with each analytical batch recharacterizes the instrument detector but does not reduce the actual variability. The analytical response and measurand concentrations should be considered when constructing a calibration curve, along with subsequent use of quality controls to confirm assay performance. It is important to assess the linearity of the calibration curve by using actual experimental data and appropriate statistics. The heteroscedasticity of the calibration data should be investigated, and appropriate weighting should be applied during regression modeling. Conclusions: This review provides an outline and guidance for optimal calibration practices in clinical mass spectrometry laboratories. [ABSTRACT FROM AUTHOR]

Objectives: Automated qualitative serology assays often measure quantitative signals that are compared against a manufacturer-defined cutoff for qualitative (positive/negative) interpretation. The current general practice of assessing serology assay performance by overall concordance in a qualitative manner may not detect the presence of analytical shift/drift that could affect disease classifications.Methods: We describe an approach to defining bias specifications for qualitative serology assays that considers minimum positive predictive values (PPVs) and negative predictive values (NPVs). Desirable minimum PPVs and NPVs for a given disease prevalence are projected as equi-PPV and equi-NPV lines into the receiver operator characteristic curve space of coronavirus disease 2019 serology assays, and the boundaries define the allowable area of performance (AAP).Results: More stringent predictive values produce smaller AAPs. When higher NPVs are required, there is lower tolerance for negative biases. Conversely, when higher PPVs are required, there is less tolerance for positive biases. As prevalence increases, so too does the allowable positive bias, although the allowable negative bias decreases. The bias specification may be asymmetric for positive and negative direction and should be method specific.Conclusions: The described approach allows setting bias specifications in a way that considers clinical requirements for qualitative assays that measure signal intensity (eg, serology and polymerase chain reaction). [ABSTRACT FROM AUTHOR]

This article is a reply to a letter that raised concerns about a previous study. The authors clarify that their study was not intended to derive analytical performance specifications based on indirect outcomes. Instead, their supplementary tool aimed to show the impact of changes in bias and imprecision on the interpretation of laboratory results. The authors also address concerns about the presentation and interpretation of simulation results, noting that different measurands, interpretation thresholds, and statistical assessments can lead to differing conclusions. They emphasize the importance of careful and objective review to avoid drawing misguided interpretations and conclusions. [Extracted from the article]