Study logistics that can impact medical countermeasure efficacy testing in mouse models of radiation injury

PURPOSE

To address confounding issues that have been noted in planning and conducting studies to identify biomarkers of radiation injury, develop animal models to simulate these injuries, and test potential medical countermeasures to mitigate/treat damage caused by radiation exposure.

METHODS

The authors completed an intensive literature search to address several key areas that should be considered before embarking on studies to assess efficacy of medical countermeasure approaches in mouse models of radiation injury. These considerations include: (1) study variables; (2) animal selection criteria; (3) animal husbandry; (4) medical management; and (5) radiation attributes.

RESULTS

It is important to select mouse strains that are capable of responding to the selected radiation exposure (e.g. genetic predispositions might influence radiation sensitivity and proclivity to certain phenotypes of radiation injury), and that also react in a manner similar to humans. Gender, vendor, age, weight, and even seasonal variations are all important factors to consider. In addition, the housing and husbandry of the animals (i.e. feed, environment, handling, time of day of irradiation and animal restraint), as well as the medical management provided (e.g. use of acidified water, antibiotics, routes of administration of drugs, consideration of animal numbers, and euthanasia criteria) should all be addressed. Finally, the radiation exposure itself should be tightly controlled, by ensuring a full understanding and reporting of the radiation source, dose and dose rate, shielding and geometry of exposure, while also providing accurate dosimetry. It is important to understand how all the above factors contribute to the development of radiation dose response curves for a given animal facility with a well-defined murine model.

CONCLUSIONS

Many potential confounders that could impact the outcomes of studies to assess efficacy of a medical countermeasure for radiation-induced injuries are addressed, and recommendations are made to assist investigators in carrying out research that is robust, reproducible, and accurate.

Practical advice on calculating confidence intervals for radioprotection effects and reducing animal numbers in radiation countermeasure experiments

The dose of a substance that causes death in P% of a population is called an LDP, where LD stands for lethal dose. In radiation research, a common LDP of interest is the radiation dose that kills 50% of the population by a specified time, i.e., lethal dose 50 or LD50. When comparing LD50 between two populations, relative potency is the parameter of interest. In radiation research, this is commonly known as the dose reduction factor (DRF). Unfortunately, statistical inference on dose reduction factor is seldom reported. We illustrate how to calculate confidence intervals for dose reduction factor, which may then be used for statistical inference. Further, most dose reduction factor experiments use hundreds, rather than tens of animals. Through better dosing strategies and the use of a recently available sample size formula, we also show how animal numbers may be reduced while maintaining high statistical power. The illustrations center on realistic examples comparing LD50 values between a radiation countermeasure group and a radiation-only control. We also provide easy-to-use spreadsheets for sample size calculations and confidence interval calculations, as well as SAS® and R code for the latter.