Assessment methods for inter-laboratory comparisons of the dicentric assay

Abstract

Purpose

To test the performance of different algorithms that can be used in inter-laboratory comparisons based on dicentric chromosome analysis, and to evaluate the impact of considering a priori values different to calculate individual laboratory performance based on the ionizing radiation dose estimation.

Methods

Mean and standard deviation estimations in inter-laboratory comparisons are tested on simulated data and data from previously published inter-laboratory comparisons using three robust algorithms, Algorithm A, Algorithm B and Q/Hampel, all programmed in R-project language and implemented in a Shiny application. The simulated data were generated assuming three different probabilities to contaminate inter-laboratory comparisons samples with atypical dose values. Comparison between different algorithms was also done using published exercises where blood samples were irradiated at 0 and 0.7 Gy that represent a challenge for the assessment of an inter-laboratory comparison.

Results

The best performance was obtained with the Q/Hampel algorithm for the estimation of the dose mean and with the Algorithm B for the estimation of the dose standard deviation under the conditions tested in the simulations. The Q/Hampel algorithm showed the best performance when non-irradiated samples were evaluated and there was a high proportion of identical values. The presence identical values cause the Algorithm B to fail. Real examples illustrating the need to consider standard deviation priors, and the need to use algorithms resistant to a high proportion of identical values are presented.

Conclusions

Q/Hampel algorithm is a serious candidate to estimate the dose mean in the inter-laboratory comparisons, and to estimate both parameters when the proportion of identical values equals or higher than the half of the results. When the proportion of identical values is less than the half of the results, the Algorithm B should be considered as a candidate to estimate the standard deviation in the inter-laboratory comparisons with small number of laboratories. We remark that special attention is needed to establish prior definitions of standard deviation in the assessment of inter-laboratory dicentric assay comparisons.

Keywords:

• Dicentric assay
• laboratory comparisons
• robust algorithms
• Shiny application

Acknowledgements

The authors thank Eric Gregoire for the data analyzed in Table 6. The authors also thank the reviewer for their valuable suggestions. The opinions and assertions expressed herein are those of the authors and do not necessarily reflect the official policy or position of their institutions.

Disclosure statement

No conflict of interest was reported by the authors.

Additional information

Notes on contributors

Jorge Ernesto González Mesa

Jorge Ernesto González Mesa, pharmacist, is the research director at the Center for Radiation Protection and Hygiene (CPHR) of Cuba.

Bret Holladay

Bret Holladay, PhD, is an assistant professor in the Statistics Department at California Polytechnic State University, San Luis Obispo, USA.

Manuel Higueras

Manuel Higueras, PhD, is an associate professor within the Mathematics and Computation Department at the La Rioja University

Marina Di Giorgio

Marina Di Giorgio, biologist, is the head and technical director of the biological dosimetry, radiopathology and internal dosimetry laboratories at the Nuclear Regulatory Authority (ARN) of Argentina.

Joan Francesc Barquinero

Joan Francesc Barquinero, PhD, is a Professor (Docent) of Human Genetics and Senior Researcher at the Department of Animal Biology, Plant Biology and Ecology, Faculty of Biosciences, Autonomous University of Barcelona, Cerdanyola del Valles, Spain.