Ponkilainen V T, Uimonen M, Raittio L, Kuitunen I, Eskelinen A, Reito A
Department of Surgery, Central Finland Hospital District, Jyväskylä, Finland.
Department of Surgery, Central Finland Hospital District, Jyväskylä, Finland.
Osteoarthritis Cartilage. 2021 Jul;29(7):939-945. doi: 10.1016/j.joca.2021.03.020. Epub 2021 Apr 29.
The aim of this study was to evaluate the methods used for including or excluding covariates in a multivariable model and to find out how common is the Table 2 Fallacy in studies recently published in high-quality orthopaedic journals.
A systematic review was conducted in the MEDLINE database. We included all studies that presented the results of a multivariable model in a table and published in seven orthopaedic journals with the highest ranked impact factors in 2019.
Table 2 Fallacy was found in 67% (129/193) of the evaluated studies in which a multivariable model was used. Only 16% (31/193) of all studies had included the variables based on causal inference. Furthermore, only three of these studies used causal diagrams to illustrate the causal inference. Altogether, 35% (67/193) of the studies included variables based on statistical methods.
Confounder selection and the interpretation of the results of the multivariable model showed notable challenges in orthopaedic studies recently published in the top orthopaedic journals. Based on the results of our review, it seems that more education in statistics and increased knowledge is required to decrease the occurrence of these statistical issues in orthopaedic research.
本研究旨在评估多变量模型中纳入或排除协变量所使用的方法，并了解在近期发表于高质量骨科期刊的研究中，“表2谬误”的常见程度。
在MEDLINE数据库中进行了一项系统评价。我们纳入了所有在表格中呈现多变量模型结果且发表于2019年影响因子排名最高的七本骨科期刊的研究。
在使用多变量模型的评估研究中，67%（129/193）存在“表2谬误”。在所有研究中，仅有16%（31/193）基于因果推断纳入变量。此外，这些研究中只有三项使用因果图来说明因果推断。总体而言，35%（67/193）的研究基于统计方法纳入变量。
在近期发表于顶级骨科期刊的骨科研究中，混杂因素的选择和多变量模型结果的解释显示出显著挑战。根据我们的综述结果，似乎需要更多的统计学教育和知识增长，以减少这些统计问题在骨科研究中的发生。
