Bias in the reporting of sex and age in biomedical research on mouse models
Bias in the reporting of sex and age in biomedical research on mouse models
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DOI：
10.7554/elife.13615
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发表时间：
2016-03-03
期刊：
影响因子：
7.7
通讯作者：
Nenadic, Goran
中科院分区：
文献类型：
--
作者：
Florez-Vargas, Oscar;Brass, Andy;Nenadic, Goran
在以动物为基础的生物医学研究中，所研究动物的性别和年龄通过改变其易感性、表现和对治疗的反应来影响疾病表型。实验方法和材料的准确报告，包括动物的性别和年龄，是必不可少的，这样其他研究人员就可以在这些研究结果的基础上进行研究。在这里，我们使用文本挖掘来研究15,311篇研究论文，其中小鼠是研究的重点。我们发现，报告小鼠性别和年龄的论文比例在过去二十年中有所增加：然而，2014年发表的论文中只有约50%报告了这两个变量。我们还比较了六个临床前研究领域的报告质量，发现这些领域存在不同程度的性别偏倚：在心血管疾病模型中观察到最强烈的男性偏倚，在传染病模型中发现最强烈的女性偏倚。这些结果表明，文本挖掘的能力有助于正在进行的关于研究可重复性的辩论，并确认需要继续努力改进实验方法和材料的报告。
In animal-based biomedical research, both the sex and the age of the animals studied affect disease phenotypes by modifying their susceptibility, presentation and response to treatment. The accurate reporting of experimental methods and materials, including the sex and age of animals, is essential so that other researchers can build on the results of such studies. Here we use text mining to study 15,311 research papers in which mice were the focus of the study. We find that the percentage of papers reporting the sex and age of mice has increased over the past two decades: however, only about 50% of the papers published in 2014 reported these two variables. We also compared the quality of reporting in six preclinical research areas and found evidence for different levels of sex-bias in these areas: the strongest male-bias was observed in cardiovascular disease models and the strongest female-bias was found in infectious disease models. These results demonstrate the ability of text mining to contribute to the ongoing debate about the reproducibility of research, and confirm the need to continue efforts to improve the reporting of experimental methods and materials.