动物实验是疾病机制和寻找可能药物研究的基础，但动物实验现在面临的问题越来越多，有来自动物保护组织的各种责骂，也有来自许多临床研究者各种不信任的评价，因为毕竟有许多动物实验结果无法被别人重复，更多研究结果无法获得临床验证。从伦理学角度考虑,使用最少量的动物从事研究没有错,但数量太少也容易导致假阴性结果的发生,浪费实验动物就更不符合道德标准了。总之，如何提高动物实验的可信度就成为一个非常重要的问题。那么，有没有一个可行的能参考的执行标准？

2012年，美国国家神经功能障碍和中风讲习班对这个问题进行深入讨论，并得出初步结论。这个结论曾经以Perspective形式发表在《自然》上。他们提出的标准包括随机化、盲法、样本量估计和数据处理等四个方面。

一、随机化

1.    动物应该进行随机分组，并报告采用的随机方法。

2.    数据采集和分析应该进行随机或适当分割。

二、盲（法）化

3.    观察者不能了解具体每只动物的分组。

4.    观察和实验操作者不能清楚具体动物分组。

5.    效应评价者不能清楚具体动物分组。

三、样本量

6.    动物数量必须在实验设计阶段确定，应报告具体的统计学计算方法。

7.    中途临时中断的研究评估必须采用多重统计方法。

四、数据处理

8.    停止数据采集应该预先制定计划。

9.    数据的采用和排除必须预先指定标准。

10.异常值定义应该在实验设计阶段进行，剔除任何数据必须如实报告。

11.实验终点必须预先设定。如果有多个终点，必须选择合适的统计学校正方法。

12.因意外和正常操作损失导致的数据丢失必须报告。

13.实验设计和分析过程必须考虑到可能存在假阳性结果。

14.观察者应该报告观察时间，如果观察条件变化则要确定结果的可重复性。

http://www.nature.com/nature/journal/v490/n7419/box/nature11556_BX1.html

原文参考

nature11556[1].pdf

Randomization

•Animals should be assigned randomly to the various experimental groups, and the method of randomization reported.

•Data should be collected and processed randomly or appropriately blocked.

Blinding

•Allocation concealment: the investigator should be unaware of the group to which the next animal taken from a cage will be allocated.

•Blinded conduct of the experiment: animal caretakers and investigators conducting the experiments should be blinded to the allocation sequence.

•Blinded assessment of outcome: investigators assessing, measuring or quantifying experimental outcomes should be blinded to the intervention.

Sample-size estimation

•An appropriate sample size should be computed when the study is being designed and the statistical method of computation reported.

•Statistical methods that take into account multiple evaluations of the data should be used when an interim evaluation is carried out.

Data handling

•Rules for stopping data collection should be defined in advance.

•Criteria for inclusion and exclusion of data should be established prospectively.

•How outliers will be defined and handled should be decided when the experiment is being designed, and any data removed before analysis should be reported.

•The primary end point should be prospectively selected. If multiple end points are to be assessed, then appropriate statistical corrections should be applied.

•Investigators should report on data missing because of attrition or exclusion.

•Pseudo replicate issues need to be considered during study design and analysis.

•Investigators should report how often a particular experiment was performed and whether results were substantiated by repetition under a range of conditions.