The Risk of Determining Risk with Multivariable Models

John Concato(Yale University), Alvan R. Feinstein(Yale University), Theodore R. Holford(Yale University)
Annals of Internal Medicine
February 1, 1993
Cited by 1,128

Abstract

PURPOSE: To review the principles of multivariable analysis and to examine the application of multivariable statistical methods in general medical literature. DATA SOURCES: A computer-assisted search of articles in The Lancet and The New England Journal of Medicine identified 451 publications containing multivariable methods from 1985 through 1989. A random sample of 60 articles that used the two most common methods--logistic regression or proportional hazards analysis--was selected for more intensive review. DATA EXTRACTION: During review of the 60 randomly selected articles, the focus was on generally accepted methodologic guidelines that can prevent problems affecting the accuracy and interpretation of multivariable analytic results. RESULTS: From 1985 to 1989, the relative frequency of multivariable statistical methods increased annually from about 10% to 18% among all articles in the two journals. In 44 (73%) of 60 articles using logistic or proportional hazards regression, risk estimates were quantified for individual variables ("risk factors"). Violations and omissions of methodologic guidelines in these 44 articles included overfitting of data; no test of conformity of variables to a linear gradient; no mention of pertinent checks for proportional hazards; no report of testing for interactions between independent variables; and unspecified coding or selection of independent variables. These problems would make the reported results potentially inaccurate, misleading, or difficult to interpret. CONCLUSIONS: The findings suggest a need for improvement in the reporting and perhaps conducting of multivariable analyses in medical research.


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