Determination of sample sizes for demonstrating efficacy of radiation countermeasures.
In response to the ever increasing threat of radiological and nuclear terrorism, active development of nontoxic new drugs and other countermeasures to protect against and/or mitigate adverse health effects of radiation is ongoing. Although the classical LD(50) study used for many decades as a first step in preclinical toxicity testing of new drugs has been largely replaced by experiments that use fewer animals, the need to evaluate the radioprotective efficacy of new drugs necessitates the conduct of traditional LD(50) comparative studies (FDA, 2002, Federal Register 67, 37988-37998). There is, however, no readily available method to determine the number of animals needed for establishing efficacy in these comparative potency studies. This article presents a sample-size formula based on Student's t for comparative potency testing. It is motivated by the U.S. Food and Drug Administration's (FDA's) requirements for robust efficacy data in the testing of response modifiers in total body irradiation experiments where human studies are not ethical or feasible. Monte Carlo simulation demonstrated the formula's performance for Student's t, Wald, and likelihood ratio tests in both logistic and probit models. Importantly, the results showed clear potential for justifying the use of substantially fewer animals than are customarily used in these studies. The present article may thus initiate a dialogue among researchers who use animals for radioprotection survival studies, institutional animal care and use committees, and drug regulatory bodies to reach a consensus on the number of animals needed to achieve statistically robust results for demonstrating efficacy of radioprotective drugs.
Kodell
Ralph L
RL
Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205, USA. rlkodell@uams.edu
Lensing
Shelly Y
SY
Landes
Reid D
RD
Kumar
K Sree
KS
Hauer-Jensen
Martin
M
D000818:Animals; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods*; D015995:Prevalence; D011832:Radiation Injuries / Q000188:drug therapy* / Q000453:epidemiology*; D011835:Radiation Protection / Q000379:methods*; D011837:Radiation-Protective Agents / Q000008:administration & dosage*; D018401:Sample Size; D016896:Treatment Outcome
D011837:Radiation-Protective Agents