Landes Reid D, Lensing Shelly Y, Hauer-Jensen Martin
a Department of Biostatistics , University of Arkansas for Medical Sciences , Little Rock , Arkansas , USA.
b Division of Radiation Health , University of Arkansas for Medical Sciences, and Central Arkansas Veterans Healthcare System , Little Rock , Arkansas , USA.
J Biopharm Stat. 2019;29(2):348-358. doi: 10.1080/10543406.2018.1535500. Epub 2018 Oct 23.
The relative potency of one agent to another is commonly represented by the ratio of two quantal response parameters; for example, the LD of animals receiving a treatment to the LD of control animals, where LD is the dose of toxin that is lethal to 50% of animals. Though others have considered interval estimators of LD, here, we extend Bayesian, bootstrap, likelihood ratio, Fieller's and Wald's methods to estimate intervals for relative potency in a parallel-line assay context. In addition to comparing their coverage probabilities, we also consider their power in two types of dose designs: one assigning treatment and control the same doses vs. one choosing doses for treatment and control to achieve same lethality targets. We explore these methods in realistic contexts of relative potency of radiation countermeasures. For larger experiments (e.g., ≥100 animals), the methods return similar results regardless of the interval estimation method or experiment design. For smaller experiments (e.g., < 60 animals), Wald's method stands out among the others, producing intervals that hold closely to nominal levels and providing more power than the other methods in statistically efficient designs. Using this simple statistical method within a statistically efficient design, researchers can reduce animal numbers.
一种药剂相对于另一种药剂的相对效力通常由两个质反应参数的比值表示;例如,接受治疗的动物的半数致死量(LD)与对照动物的半数致死量之比,其中LD是对50%的动物致死的毒素剂量。尽管其他人已经考虑了LD的区间估计,但在这里,我们扩展了贝叶斯、自助法、似然比、菲勒法和沃尔德法,以估计平行线试验背景下相对效力的区间。除了比较它们的覆盖概率,我们还考虑它们在两种剂量设计中的功效:一种是给治疗组和对照组分配相同的剂量,另一种是为治疗组和对照组选择剂量以达到相同的致死率目标。我们在辐射防护措施相对效力的实际背景下探索这些方法。对于较大规模的实验(例如,≥100只动物),无论采用哪种区间估计方法或实验设计,这些方法都会得出相似的结果。对于较小规模的实验(例如,<60只动物),沃尔德法在其他方法中脱颖而出,产生的区间与名义水平紧密相符,并且在统计效率高的设计中比其他方法具有更高的功效。在统计效率高的设计中使用这种简单的统计方法,研究人员可以减少动物数量。