Taylor-LaPole Alyssa M, Cunny Helen C, Shockley Keith R
Virginia Wesleyan University, Virginia Beach, VA, 23455, USA.
Office of Program Operations, Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, 27709, USA.
J Young Investig. 2022 Jul;25(7):1-12. Epub 2022 Jul 25.
Parametric statistical tests used to assess body weight changes in rodent experiments assume a normal distribution, and the actual distribution of the rodent body weights is often assumed to be approximately normal. In order for statistical tests to be deemed appropriate without routinely confirming the normal distribution for rodent body weight data, the tests must be powerful enough to detect meaningful changes even when a population deviates from a normal distribution. Here, we present a novel analysis to assess the normality of rodent body weight data for control animals in 1,386 National Toxicology Program (NTP) studies and determined how robust a set of procedures are to detect departures from normality. The distributions of terminal body weight measurements from 90 day and chronic NTP studies were evaluated for normality using graphical and statistical testing methods. The percent of studies with terminal body weights that were not normally distributed in normality tests was typically higher in 90-day studies for Fischer 344/N (F344/N) rats and B6C3F1/N (B6C3F1) mice than Harlan Sprague-Dawley (HSD) rats across all routes of administration evaluated (feed, drinking water, gavage or inhalation). Through simulation studies, the t-test indicated adequate power to detect a difference in body weights in male B6C3F1 mice and F344/N rats in 90-day studies, even under a skew normal distribution. According to these results, common parametric tests display enough power to accurately detect body weight differences from populations not following a normal distribution, confirming the general notion that the study designs are appropriately powered. In addition to providing adequate power, the False Positive Rate (FPR) was controlled around 5% in all simulations. These results suggest that parametric tests are robust enough to give reliable results of body weight analysis in NTP studies where this is an important endpoint. Therefore, parametric testing approaches are appropriate to detect body weight changes in NTP studies when body weight distributions do not deviate too far from normality. Future steps will look at the distributions of non-terminal body weights in chronic studies, organ weights, and other species and strains of rodents.
用于评估啮齿动物实验中体重变化的参数统计检验假定数据呈正态分布，并且通常假定啮齿动物体重的实际分布近似正态。为了在不经常确认啮齿动物体重数据正态分布的情况下使统计检验被认为是合适的，这些检验必须足够强大，即使总体偏离正态分布也能检测到有意义的变化。在此，我们提出一种新颖的分析方法，以评估1386项国家毒理学计划（NTP）研究中对照动物的啮齿动物体重数据的正态性，并确定一组程序检测偏离正态性的稳健程度。使用图形和统计检验方法评估了来自90天和慢性NTP研究的终末体重测量值的分布是否呈正态。在所有评估的给药途径（饲料、饮用水、灌胃或吸入）中，Fischer 344/N（F344/N）大鼠和B6C3F1/N（B6C3F1）小鼠的90天研究中，终末体重在正态性检验中呈非正态分布的研究百分比通常高于Harlan Sprague-Dawley（HSD）大鼠。通过模拟研究，t检验表明在90天研究中，即使在偏态正态分布下，也有足够的检验效能来检测雄性B6C3F1小鼠和F344/N大鼠的体重差异。根据这些结果，常见的参数检验显示出足够的检验效能来准确检测来自非正态分布总体的体重差异，证实了研究设计具有适当检验效能的普遍观点。除了提供足够的检验效能外，所有模拟中的假阳性率（FPR）都控制在5%左右。这些结果表明，参数检验足够稳健，能够在NTP研究中给出可靠的体重分析结果，而体重是一个重要的终点指标。因此，当体重分布与正态分布偏差不太严重时，参数检验方法适用于检测NTP研究中的体重变化。未来的步骤将研究慢性研究中非终末体重的分布、器官重量以及其他啮齿动物物种和品系。
