Logistic regression models in obstetrics and gynecology literature.
OBJECTIVE
To evaluate the reporting of multivariable logistic regression analyses and assess variations in quality over time in the obstetrics and gynecology literature.


METHODS
Methodologic criteria for reporting logistic regression analyses were developed to identify problems affecting accuracy, precision, and interpretation of this approach to multivariable statistical analysis. These criteria were applied to 193 articles that reported multivariable logistic regression in the issues of four generic obstetrics and gynecology journals in 1985, 1990, and 1995. Rates of compliance with the methodologic criteria and their time trends were analyzed.


RESULTS
The proportion of articles using logistic regression analysis increased over time: 1.7% in 1985, 2.8% in 1990, and 6.5% in 1995 (P < .001 for trend). Violations and omissions of methodologic criteria for reporting logistic models were common. The research question, in terms of dependent and independent variables, was not clearly reported in 32.1%. The process of variable selection was inadequately described in 51.8% of the articles. Among articles with ranked independent variables, 85.1% did not report assessment of conformity to linear gradient. Tests for goodness of fit were not given in 93.2% of articles. The contribution of the independent variables could not be evaluated in 36.2% of the articles because of a lack of coding of the variables. Interactions between variables were not assessed in 86.4% of articles. Analysis of variations in the quality of logistic regression analyses over time showed no increase in reporting of the criteria concerning variable selection and goodness of fit. However, the proportion of articles reporting one quality criterion concerning interpretation of the substantive significance of independent variables showed a trend toward improvement: 42.3% in 1985, 73.6% in 1990, and 75.4% in 1995 (P = .004 for trend).


CONCLUSIONS
The reporting of multivariable logistic regression models in the obstetrics and gynecology literature is poor, and the time trends of improvement in quality of reporting are not particularly encouraging.
Khan
K S
KS
Academic Department of Obstetrics and Gynecology, University of Birmingham, United Kingdom. k.s.khan@bham.ac.uk
Chien
P F
PF
Dwarakanath
L S
LS
D006176:Gynecology; D016015:Logistic Models; D009774:Obstetrics; D011643:Publishing / Q000706:statistics & numerical data*