approach to integrated data assessment in a proficiency test on the enumeration of Escherichia coli

• Published in: Journal of applied microbiology Vol. 110; no. 1; pp. 128 - 138
• Main Authors: Bremser, W, Lücke, F.‐K, Urmetzer, C, Fuchs, E, Leist, U
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 2011; Blackwell
• Subjects: bacteria; bias; Biological and medical sciences; Colony Count, Microbial - methods; data assessment; data collection; Data Interpretation, Statistical; Escherichia coli; Escherichia coli - growth & development; Fundamental and applied biological sciences. Psychology; inoculation methods; Laboratory Proficiency Testing; Microbiology; Monte Carlo method; planning; precision; proficiency testing; Reproducibility of Results; statistics; uncertainty; Enumeration; Applied microbiology; Escherichia coli; bias; precision; Bacteria; proficiency testing; Statistics; Enterobacteriaceae; Enumeration(counting); data assessment
• ISSN: 1364-5072; 1365-2672
• DOI: 10.1111/j.1365-2672.2010.04866.x

Aims: To develop appropriate statistical approaches to plan and evaluate proficiency tests for the enumeration of Escherichia coli, addressing, in particular, a possible but frequently unavoidable lack of test sample homogeneity. Methods and Results: Each of 50 laboratories analysed two samples of a stabilized suspension of E. coli in duplicate, using various media, inoculation methods, and incubation times and conditions. In parallel, the E. coli suspension was tested by the organiser for homogeneity and stability. Escherichia coli counts followed a log‐normal distribution. After eliminating, by Youden analysis, two data sets that were considered outliers and eight data sets for underperformance of the laboratories (substantial lack of repeatability), the standard deviation of the mean was about 0·06 log₁₀ units. There was no evidence of bimodality of the data. Lack of homogeneity of distribution of bacteria had a strong effect on measurement uncertainty, in addition to laboratory bias and method repeatability. The homogeneity decreases during storage of the individual test vials; this effect could be modelled by the known kinetics of inactivation of micro‐organisms. The results were confirmed by Monte Carlo simulations. Conclusions: By a tailored analysis of proficiency testing data, it is possible to distinguish the effect of lack of homogeneity, laboratory bias and method repeatability, on the measurement uncertainty. Significance and Impact of the Study: A statistic tool is provided to solve problems related to lack of stability of microbiological test material and to separate the effects of sample inhomogeneity from the performance of the individual laboratory.