The intriguing evolution of effect sizes in biomedical research over time: smaller but more often statistically significant.
The intriguing evolution of effect sizes in biomedical research over time: smaller but more often statistically significant.
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DOI：
10.1093/gigascience/gix121
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发表时间：
2018-01-01
期刊：
影响因子：
9.2
通讯作者：
Vergnes JN
中科院分区：
文献类型：
--
作者：
Monsarrat P;Vergnes JN
在医学中，效应量（ES）允许自变量（包括风险/保护因素或治疗干预）对因变量（例如，健康状况）进行量化。鉴于许多公共卫生决策和医疗保健政策是基于ES估计，重要的是要评估ES是如何在生物医学文献中使用，并调查其报告随着时间的推移的潜在趋势。通过大数据方法，文本挖掘过程自动从13 322 754篇PubMed摘要中提取了814 120个ES。符合条件的ES是风险比、比值比和危害比及其置信区间沿着。在这里，我们显示了1990年至2015年期间PubMed摘要中ES值的显着下降，同时，结果往往具有统计学意义。随着时间的推移，“风险”和“保护”值的ES值中位数均有所下降。这种趋势几乎存在于生物医学研究的所有领域，其中遗传学的下降趋势最为明显。在同一时期，具有统计学意义的ES的比例有规律地增加：在至少有1个ES的摘要中，1990-1995年有74%具有统计学意义，而2010-2015年为85%。然而，ES的减少可能是生物医学研究的内在演变，随之而来的统计学显著结果的增加更有趣。虽然生物医学研究中样本量的增加可能可以解释这些结果，但另一种解释可能在于科学研究的“发表或毁灭”背景下，研究报告中越来越倾向于耸人听闻的可能性。必须作出重要规定，提高生物医学研究的可信度，限制资源浪费。
In medicine, effect sizes (ESs) allow the effects of independent variables (including risk/protective factors or treatment interventions) on dependent variables (e.g., health outcomes) to be quantified. Given that many public health decisions and health care policies are based on ES estimates, it is important to assess how ESs are used in the biomedical literature and to investigate potential trends in their reporting over time. Through a big data approach, the text mining process automatically extracted 814 120 ESs from 13 322 754 PubMed abstracts. Eligible ESs were risk ratio, odds ratio, and hazard ratio, along with their confidence intervals. Here we show a remarkable decrease of ES values in PubMed abstracts between 1990 and 2015 while, concomitantly, results become more often statistically significant. Medians of ES values have decreased over time for both “risk” and “protective” values. This trend was found in nearly all fields of biomedical research, with the most marked downward tendency in genetics. Over the same period, the proportion of statistically significant ESs increased regularly: among the abstracts with at least 1 ES, 74% were statistically significant in 1990–1995, vs 85% in 2010–2015. whereas decreasing ESs could be an intrinsic evolution in biomedical research, the concomitant increase of statistically significant results is more intriguing. Although it is likely that growing sample sizes in biomedical research could explain these results, another explanation may lie in the “publish or perish” context of scientific research, with the probability of a growing orientation toward sensationalism in research reports. Important provisions must be made to improve the credibility of biomedical research and limit waste of resources.
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影响因子：
120.7
作者：
Chavalarias, David;Wallach, Joshua David;Ioannidis, John P. A.
通讯作者：
Ioannidis, John P. A.
影响因子：
15.8
作者：
Ioannidis, JPA
通讯作者：
Ioannidis, JPA
DOI：
10.1073/pnas.1302997110
发表时间：
2013-09-10
影响因子：
11.1
作者：
Fanelli, Daniele;Ioannidis, John P. A.
通讯作者：
Ioannidis, John P. A.
影响因子：
2
作者：
Ioannidis, John P. A.
通讯作者：
Ioannidis, John P. A.
影响因子：
4
作者：
Gehr, Bernhard T;Weiss, Christel;Porzsolt, Franz
通讯作者：
Porzsolt, Franz