Uncertainty in measurement: A review of the procedures for determining uncertainty in measurement and its use in deriving the biological variation of the estimated glomerular filtration rate

Analytical assays and bootstrap resampling method to validate performance of the Roche Elecsys STAT highly sensitive troponin T assay and its application for the 'rule-out' part of ESC guidelines for NTSTEMI

BACKGROUND

The European Society of Cardiology (ESC) guidelines recommend a dynamic (0-1h) cardiac troponin (cTn) determination for non-ST elevation myocardial infarction diagnosis. For patients with low cTn levels, a discharge from emergency can be considered. Nevertheless, cTn cutoffs for discharge are lower than the limits of quantification proposed by laboratory reagent suppliers.

AIM

Validate cTn assay on the Elecsys STAT kit.

MATERIALS AND METHODS

Precision, trueness, repeatability and within-laboratory variability were calculated from internal quality control and plasma pooled at 5.78 and 10.73 ng/L. Accuracy was calculated from external quality control. Uncertainty of measurement was calculated from (i) the uncertainty of the standard and control values and (ii) by precision from pooled plasma. Distribution of precision results from pooled plasma has been evaluated by bootstrap simulations. Dilution linearity tests with patient plasma were performed to evaluate the method for values near 5 ng/L.

RESULTS

Precision and trueness ranged from 1.35 to 4.45% and from 0.14 to -3.74%, respectively. Accuracy results ranged from 101.40 to 104.90%. Within laboratory variability was 2.91%. Uncertainty ranged from 3.66% to 19.90% for higher (2188) to lower values (5.78 ng/L). Bootstrap simulations allowed utilization of precision data from pooled plasma to evaluate cTn assay. The method was linear from 4.48 to 39.80 ng/L. A linear regression model best described the data.

CONCLUSION

Elecsys STAT method provides accurate cTn results, including patients with cTn results categorizing them as 'rule-out' in the ESC guidelines.

Uncertainty in measurement and the renal tubular reabsorption of phosphate

OBJECTIVES

The ratio of tubular maximum reabsorption of phosphate to glomerular filtration rate (TmP/GFR) is used to evaluate renal phosphate transport. TmP/GFR is most probably calculated using the formula described by Kenny and Glen or obtained from the nomogram described by Walton and Bijvoet. Even though the calculation itself is well described, no attention has been given to its measurement uncertainty (MU). The aim of this study is to provide a procedure for evaluating the MU of the Kenny and Glen formula; a procedure which is based on the Evaluation of measurement data - Guide to the expression of uncertainty in measurement (GUM).

METHODS

TmP/GFR is a quantity value calculated from the input of measured values for serum (plasma) phosphate and creatinine, plus measured values of urine phosphate and creatinine. Given the measurement uncertainty associated with these input quantities, the GUM describes the mathematical procedures required to determine the uncertainty of the calculated TmP/GFR. From a medical laboratory perspective, these input uncertainties are the standard deviations of the respective internal quality control estimates for serum and urine phosphate, plus serum and urine creatinine.

RESULTS

Based on representative measurements for the input quantities and their associated standard uncertainties, the expanded relative uncertainty for a calculated TmP/GFR is approximately 3.0-4.5 %.

CONCLUSIONS

With the continued relevance of the TmP/GFR procedure and the use of creatinine clearance as an estimate of GFR, the addition of an uncertainty estimate is important as an adjunct to this diagnostic procedure.

Estimation of measurement uncertainty for the quantification of protein by ID-LC-MS/MS

The emergence of mass spectrometry (MS)-based methods to quantify proteins for clinical applications has led to the need for accurate and consistent measurements. To meet the clinical needs of MS-based protein results, it is important that the results are traceable to higher-order standards and methods and have defined uncertainty values. Therefore, we outline a comprehensive approach for the estimation of measurement uncertainty of a MS-based procedure for the quantification of a protein biomarker. Using a bottom-up approach, which is the model outlined in the "Guide to the Expression of Uncertainty of Measurement" (GUM), we evaluated the uncertainty components of a MS-based measurement procedure for a protein biomarker in a complex matrix. The cause-and-effect diagram of the procedure is used to identify each uncertainty component, and statistical equations are derived to determine the overall combined uncertainty. Evaluation of the uncertainty components not only enables the calculation of the measurement uncertainty but can also be used to determine if the procedure needs improvement. To demonstrate the use of the bottom-up approach, the overall combined uncertainty is estimated for the National Institute of Standards and Technology (NIST) candidate reference measurement procedure for albumin in human urine. The results of the uncertainty approach are applied to the determination of uncertainty for the certified value for albumin in candidate NIST Standard Reference Material® (SRM) 3666. This study provides a framework for measurement uncertainty estimation of a MS-based protein procedure by identifying the uncertainty components of the procedure to derive the overall combined uncertainty.

On the Geochemistry of the Danube River Sediments (Serbian Sector)

To determine the nature and origin of the unconsolidated bottom sediments, as well as to demonstrate and quantify the presence of Presumably Contaminating Elements (PCE) in the Serbian Danube River, as a novelty, the mass fractions on nine major elements as oxides-SiO₂, TiO₂, Al₂O₃, FeO, MnO, MgO, CaO, Na₂O, and K₂O, as well as Sc, V, Cr, Co, Ni, Cu, Zn, As, Rb, Sr, Zr, Sb, Cs, Ba, La, Hf, Ta, W, Th, and U were determined by Instrumental Neutron Activation Analysis (INAA) in 13 sediment samples collected between Belgrade and Iron Gate 2 dam. INAA was chosen for its ability to perform elemental analysis without any preliminary sample treatment that could introduce systematic errors. The distribution of major elements was relatively uniform, with the sampling locations having less influence. Concerning the trace elements, excepting the PCE Cr, Ni, Cu, Zn, As, and Sb, their distributions presented the same remarkable similarity to the Upper Continental Crust (UCC), North American Shale Composite (NASC), Average Bottom Load (ABL), and Average Dobrogea Loess (AVL), and were in good concordance with the location of the Serbian Danube River in the Pannonian Plain. In the case of considered PCE, both Enrichment Factor and Pollution Load Index showed values higher than the pollution threshold, which pointed towards a significant anthropogenic contamination, and rising concern to what extent the water quality and biota could be affected.

ISO/TS 20914:2019 - a critical commentary

The long-anticipated ISO/TS 20914, Medical laboratories - Practical guidance for the estimation of measurement uncertainty, became publicly available in July 2019. This ISO document is intended as a guide for the practical application of estimating uncertainty in measurement (measurement uncertainty) in a medical laboratory. In some respects, the guide does indeed meet many of its stated objectives with numerous very detailed examples. Even though it is claimed that this ISO guide is based on the Evaluation of measurement data - Guide to the expression of uncertainty in measurement (GUM), JCGM 100:2008, it is with some concern that we believe several important statements and statistical procedures are incorrect, with others potentially misleading. The aim of this report is to highlight the major concerns which we have identified. In particular, we believe the following items require further comment: (1) The use of coefficient of variation and its potential for misuse requires clarification, (2) pooled variance and measurement uncertainty across changes in measuring conditions has been oversimplified and is potentially misleading, (3) uncertainty in the results of estimated glomerular filtration rate (eGFR) do not include all known uncertainties, (4) the international normalized ratio (INR) calculation is incorrect, (5) the treatment of bias uncertainty is considered problematic, (6) the rules for evaluating combined uncertainty in functional relationships are incomplete, and (7) specific concerns with some individual statements.

Glomerular Filtration Rate in Former Extreme Low Birth Weight Infants over the Full Pediatric Age Range: A Pooled Analysis

Various cohort studies document a lower glomerular filtration rate (GFR) in former extremely low birth weight (ELBW, <1000 g) neonates throughout childhood when compared to term controls. The current aim is to pool these studies to describe the GFR pattern over the pediatric age range. To do so, we conducted a systematic review on studies reporting on GFR measurements in former ELBW cases while GFR data of healthy age-matched controls included in these studies were co-collected. Based on 248 hits, 6 case-control and 3 cohort studies were identified, with 444 GFR measurements in 380 former ELBW cases (median age 5.3–20.7 years). The majority were small (17–78 cases) single center studies, with heterogeneity in GFR measurement (inulin, cystatin C or creatinine estimated GFR formulae) tools. Despite this, the median GFR (mL/min/1.73 m²) within case-control studies was consistently lower (−13%, range −8% to −25%) in cases, so that a relevant minority (15–30%) has a eGFR<90 mL/min/1.73 m²). Consequently, this pooled analysis describes a consistent pattern of reduced eGFR in former ELBW cases throughout childhood. Research should focus on perinatal risk factors for impaired GFR and long-term outcome, but is hampered by single center cohorts, study size and heterogeneity of GFR assessment tools.

Statistical distributions commonly used in measurement uncertainty in laboratory medicine

Uncertainty is an inseparable part of all types of measurement. Recently, the International Organization for Standardization (ISO) released a new standard (ISO 20914) on how to calculate measurement uncertainty (MU) in laboratory medicine. This standard can be regarded as the beginning of a new era in laboratory medicine. Measurement uncertainty comprises various components and is used to calculate the total uncertainty. All components must be expressed in standard deviation (SD) and then combined. However, the characteristics of these components are not the same; some are expressed as SD, while others are expressed as a ± b, such as the purity of the reagents. All non-SD variables must be transformed into SD, which requires a detailed knowledge of common statistical distributions used in the calculation of MU. Here, the main statistical distributions used in MU calculation are briefly summarized.

Extra-analytical sources of uncertainty: which ones really matter?

Since the endorsement by ISO15189:2012 of measurement uncertainty (MU) for the estimation of error in measurement procedures, the debate has been ongoing with questions concerning which method should be used for estimating MU and the benefits of using MU over other error methods. However, only limited attention has been given to extra-analytical sources of uncertainty and, currently, a clear standpoint is still missing. This opinion paper aims to evaluate whether extra-analytical variables could be included in MU. Considering coagulation tests as an example, the possible sources of preanalytical variations are evaluated by using a fishbone diagram. After excluding preanalytical errors, additional sources of uncertainty are divided into amenable to standardization/harmonization and/or possible random sources, which are not standardizable nor harmonizable. Finally, sources of uncertainty are evaluated for a possible inclusion into MU. In addition, postanalytical uncertainty is discussed, particularly considering the laboratory results calculated through a mathematical equation, derived from one or more quantities affected by their specific uncertainty.