Influence of statistical methods on lower limits of dose estimation in biological dosimetry

In cases of radiological or nuclear events, biological dosimetry enables decisions whether an individual was exposed to ionizing radiation and the estimation of the dose. Several statistical methods are used to assess uncertainties. The stringency of the applied method has an impact on the lowest dose that can be detected. To obtain reliable and comparable results, it is crucial to harmonize the applied statistical methods.

The decision threshold and detection limit of the statistical methods were derived for variable cell numbers. The coverage of the 95% confidence intervals as well as the false-positive and false-negative rates of the methods were compared based on simulations. The evaluated methods included a graphical method, the propagation of errors and a Bayesian method.

The minimum resolvable doses, the doses at the detection limit and the coverage were relatively variable between the compared methods. The Bayesian method showed the best coverage, lowest resolvable doses and had false-positive rates close to 5%. The graphical method with the combination of two 83% confidence intervals also showed promising results. The other methods were either too conservative or underestimated the uncertainties for some doses or cell numbers.

The assessment of the lower dose limits is a central part of biological dosimetry and the applied statistical methods have a strong influence on the interpretation of the results. Simulations enable comparisons between methods and provide important information for the harmonization and standardization of the uncertainty assessment.