Mikolajczyk Rafael T, DiSilvestro Alexis, Zhang Jun
Epidemiology Branch, the National Institute of Child Health and Human Development, the National Institutes of Health, Bethesda, Maryland 20892-7510, USA.
Obstet Gynecol. 2008 Feb;111(2 Pt 1):413-9. doi: 10.1097/AOG.0b013e318160f38e.
To evaluate the quality of logistic regression reporting in the obstetrics and gynecology literature.
All original papers published in 2005 and 2006 in four leading obstetrics and gynecology journals were manually searched for the use of logistic regression. One hundred four articles that used logistic regression were randomly selected (13 from each journal and each year) and evaluated according to previously established criteria for reporting logistic regression analyses. Rates of compliance with these criteria were calculated separately for each journal and weighted according to the number of articles using logistic regression in each of the journals in the same period to obtain an overall estimate.
Logistic regression was used in 34.2% of all original research articles (724 of 2,234) in the four journals for the study period. Statistical significance of estimates was reported in 96% of examined articles. Criteria of variable selection for the logistic regression model were reported in 76% of articles, and coding of variables was described in 83%. Overfitting (models with too many variables for the number of outcome events) occurred in 57% of studies. The majority of examined articles insufficiently reported information for the remaining criteria-testing for interactions (18%), conformity to a linear gradient of continuous variables (9%), goodness of fit (3.6%), assessment of multi-collinearity (0.46%), and validation of the model (0%).
Logistic regression has become a standard statistical method in obstetrics and gynecology literature. Although some standards are mostly fulfilled, there is still considerable room for improvement.
III.
评估妇产科文献中逻辑回归报告的质量。
人工检索2005年和2006年在四种主要妇产科期刊上发表的所有原创论文，以查找逻辑回归的使用情况。随机选择104篇使用逻辑回归的文章（每年从每种期刊中选13篇），并根据先前确立的逻辑回归分析报告标准进行评估。分别计算每种期刊符合这些标准的比例，并根据同期每种期刊中使用逻辑回归的文章数量进行加权，以获得总体估计值。
在研究期间，这四种期刊中所有原创研究文章的34.2%（2234篇中的724篇）使用了逻辑回归。在96%的被检查文章中报告了估计值的统计学显著性。76%的文章报告了逻辑回归模型的变量选择标准，83%的文章描述了变量编码。57%的研究出现了过度拟合（变量数量相对于结局事件数量过多的模型）。对于其余标准——交互作用检验（18%）、连续变量是否符合线性梯度（9%）、拟合优度（3.6%）、多重共线性评估（0.46%）和模型验证（0%），大多数被检查文章报告的信息不足。
逻辑回归已成为妇产科文献中的一种标准统计方法。虽然一些标准大多得到满足，但仍有很大的改进空间。
III级。
