The impact of accuracy and precision of analytical test methods on the determination of withdrawal periods

Treatment of food-producing animals with veterinary medicinal products (VMPs) can result in residues in foodstuffs (e.g. eggs, meat, milk, or honey) representing a potential consumer health risk. To ensure consumer safety, worldwide regulatory concepts for setting safe limits for residues of VMPs e.g. as tolerances (US) or maximum residue limits (MRLs, EU) are used. Based on these limits so-called withdrawal periods (WP) are determined. A WP represents the minimum period of time required between the last administration of the VMP and the marketing of foodstuff. Usually, WPs are estimated using regression analysis based on residue studies. With high statistical confidence (usually 95% in the EU and 99% in the US) the residues in almost all treated animals (usually 95%) have to be below MRL when edible produce is harvested. Here, uncertainties from both sampling and biological variability are taken into account but uncertainties of measurement associated with the analytical test methods are not systematically considered. This paper describes a simulation experiment to investigate the extent to which relevant sources of measurement uncertainty (accuracy and precision) can impact the length of WPs. A set of real residue depletion data was artificially 'contaminated' with measurement uncertainty related to permitted ranges for accuracy and precision. The results show that both accuracy and precision had a noticeable effect on the overall WP. Due consideration of sources of measurement uncertainty may improve the robustness, quality and reliability of calculations upon which regulatory decisions on consumer safety of residues are based.

Disregarded Measurement Uncertainty Contributions and Their Magnitude in Measuring Plasma Glucose

BACKGROUND

Each measurement is subject to measurement uncertainty (MU). Consequently, each measurement of plasma glucose concentration used for diagnosis and monitoring of diabetes mellitus (DM) is affected. Although concepts and methods of MU are well established in many fields of science and technology, they are presently only incompletely implemented by medical laboratories, neglecting MU of target values of internal quality control (IQC) materials.

METHODS

An empirical and practical approach for the estimation of MU based on the analysis of routine IQC using control samples with assigned target values is presented. Its feasibility is demonstrated exemplarily by analyzing IQC data from one year obtained for glucose employing the hexokinase method with IQC of two different concentrations.

RESULTS

Combined relative extended (k = 2) MU comprising bias, coefficient of variation (CV), and MU of the target values assigned to control materials were about 9% with a lower (~ 56 mg/dL; ~3.1 mmol/L) and 8% with a higher (~ 346 mg/dL; ~19.2 mmol/L) concentration sample, analyzing IQC of one year from three different devices.

CONCLUSIONS

Estimation of MU in this study is quite reliable due to the large number of IQC data from one year. The MU of the target values of the commercial control material in this study was considerably larger than other MU contributions, ie, standard deviation and bias. In the future, the contribution of MU of commercial IQC should be addressed more carefully and technologies to measure glucose should be geared toward smaller MU possible, as needed, especially for glucose concentration measurements in diagnosis and management of DM.

Evaluation strategies and uncertainty calculation of isotope amount ratios measured by MC ICP-MS on the example of Sr

This paper critically reviews the state-of-the-art of isotope amount ratio measurements by solution-based multi-collector inductively coupled plasma mass spectrometry (MC ICP-MS) and presents guidelines for corresponding data reduction strategies and uncertainty assessments based on the example of n((87)Sr)/n((86)Sr) isotope ratios. This ratio shows variation attributable to natural radiogenic processes and mass-dependent fractionation. The applied calibration strategies can display these differences. In addition, a proper statement of uncertainty of measurement, including all relevant influence quantities, is a metrological prerequisite. A detailed instructive procedure for the calculation of combined uncertainties is presented for Sr isotope amount ratios using three different strategies of correction for instrumental isotopic fractionation (IIF): traditional internal correction, standard-sample bracketing, and a combination of both, using Zr as internal standard. Uncertainties are quantified by means of a Kragten spreadsheet approach, including the consideration of correlations between individual input parameters to the model equation. The resulting uncertainties are compared with uncertainties obtained from the partial derivatives approach and Monte Carlo propagation of distributions. We obtain relative expanded uncertainties (U rel; k = 2) of n((87)Sr)/n((86)Sr) of < 0.03 %, when normalization values are not propagated. A comprehensive propagation, including certified values and the internal normalization ratio in nature, increases relative expanded uncertainties by about factor two and the correction for IIF becomes the major contributor.