Lew M
Department of Pharmacology, University of Melbourne, Parkville, Victoria, Australia.
Br J Pharmacol. 2007 Oct;152(3):295-8. doi: 10.1038/sj.bjp.0707370. Epub 2007 Jul 9.
This paper is intended to assist pharmacologists in making the most of statistical analysis and in avoiding common errors that can lead to false conclusions.
A scenario is presented where a pathway inhibitor increased blood pressure responses to an agonist by about one third. The fictional experimenter concludes that the inhibitor enhanced the responses to the agonist, but has not applied any statistical analysis. Questions are asked of the reader, and a discussion of the author's answers is presented.
The agonist responses have unequal standard errors, as often seen in data like these concentration-response curves with responses expressed as change from baseline. The uneven variability (heteroscedasticity) violates an assumption of conventional parametric statistical analyses, but can be corrected by data transformation. Expressing the data as absolute blood pressure and then transforming it to log blood pressure eliminated the heteroscedasticity, but made evident an effect of the inhibitor on baseline blood pressure.
Statistical analysis is a sensible precaution against mistakes, but cannot protect against all erroneous conclusions. In this scenario, the inhibitor reduced the blood pressure and increased responses to the agonist. However, it is likely that the latter effect was a consequence of the former and thus no conclusion can be safely drawn about any direct interaction between the agonist and the pathway inhibitor from this experiment. Where results are awkward to interpret because of confounding factors such as an altered baseline, statistical analysis may not be very useful in supporting a safe conclusion.
本文旨在帮助药理学家充分利用统计分析，并避免可能导致错误结论的常见错误。
呈现了一个场景，即一种通路抑制剂使对激动剂的血压反应增加了约三分之一。虚构的实验者得出结论认为该抑制剂增强了对激动剂的反应，但未进行任何统计分析。向读者提出问题，并给出作者的答案讨论。
激动剂反应具有不相等的标准误差，这在这些以相对于基线的变化表示反应的浓度-反应曲线数据中很常见。不均匀的变异性（异方差性）违反了传统参数统计分析的一个假设，但可以通过数据转换来校正。将数据表示为绝对血压，然后将其转换为对数血压消除了异方差性，但揭示了抑制剂对基线血压的影响。
统计分析是防止错误的明智预防措施，但不能防止所有错误结论。在这种情况下，抑制剂降低了血压并增加了对激动剂的反应。然而，后者的效应很可能是前者的结果，因此从该实验中无法安全地得出关于激动剂与通路抑制剂之间任何直接相互作用的结论。由于诸如基线改变等混杂因素导致结果难以解释时，统计分析可能对支持可靠结论不是很有用。
