Zhang Ying-Ying, Zhou Xiao-Bin, Wang Qiu-Zhen, Zhu Xiao-Yan
Department of Epidemiology and Health Statistics Department of Public Health, Medical College of Qingdao University, Qingdao, China.
Medicine (Baltimore). 2017 May;96(21):e6972. doi: 10.1097/MD.0000000000006972.
Multivariable logistic regression (MLR) has been increasingly used in Chinese clinical medical research during the past few years. However, few evaluations of the quality of the reporting strategies in these studies are available.To evaluate the reporting quality and model accuracy of MLR used in published work, and related advice for authors, readers, reviewers, and editors.A total of 316 articles published in 5 leading Chinese clinical medical journals with high impact factor from January 2010 to July 2015 were selected for evaluation. Articles were evaluated according 12 established criteria for proper use and reporting of MLR models.Among the articles, the highest quality score was 9, the lowest 1, and the median 5 (4-5). A total of 85.1% of the articles scored below 6. No significant differences were found among these journals with respect to quality score (χ = 6.706, P = .15). More than 50% of the articles met the following 5 criteria: complete identification of the statistical software application that was used (97.2%), calculation of the odds ratio and its confidence interval (86.4%), description of sufficient events (>10) per variable, selection of variables, and fitting procedure (78.2%, 69.3%, and 58.5%, respectively). Less than 35% of the articles reported the coding of variables (18.7%). The remaining 5 criteria were not satisfied by a sufficient number of articles: goodness-of-fit (10.1%), interactions (3.8%), checking for outliers (3.2%), collinearity (1.9%), and participation of statisticians and epidemiologists (0.3%). The criterion of conformity with linear gradients was applicable to 186 articles; however, only 7 (3.8%) mentioned or tested it.The reporting quality and model accuracy of MLR in selected articles were not satisfactory. In fact, severe deficiencies were noted. Only 1 article scored 9. We recommend authors, readers, reviewers, and editors to consider MLR models more carefully and cooperate more closely with statisticians and epidemiologists. Journals should develop statistical reporting guidelines concerning MLR.
在过去几年中，多变量逻辑回归（MLR）在中国临床医学研究中的应用越来越广泛。然而，对这些研究中报告策略质量的评估却很少。为了评估已发表作品中MLR的报告质量和模型准确性，并为作者、读者、审稿人和编辑提供相关建议。我们选取了2010年1月至2015年7月在5种影响因子较高的中国领先临床医学期刊上发表的316篇文章进行评估。文章根据12条已确立的MLR模型正确使用和报告标准进行评估。在这些文章中，质量得分最高为9分，最低为1分，中位数为5分（4 - 5分）。共有85.1%的文章得分低于6分。这些期刊在质量得分方面没有发现显著差异（χ = 6.706，P = .15）。超过50%的文章符合以下5条标准：完全识别所使用的统计软件应用（97.2%）、计算比值比及其置信区间（86.4%）、描述每个变量足够的事件数（>10）、变量选择和拟合程序（分别为78.2%、69.3%和58.5%）。不到35%的文章报告了变量编码（18.7%）。其余5条标准没有足够数量的文章满足：拟合优度（10.1%）、交互作用（3.8%）、异常值检查（3.2%）、共线性（1.9%）以及统计学家和流行病学家的参与（0.3%）。符合线性梯度的标准适用于186篇文章；然而，只有7篇（3.8%）提及或进行了测试。所选文章中MLR的报告质量和模型准确性并不令人满意。事实上，存在严重不足。只有1篇文章得分为9分。我们建议作者、读者、审稿人和编辑更仔细地考虑MLR模型，并与统计学家和流行病学家更密切地合作。期刊应制定关于MLR的统计报告指南。
