Data mining: comparing the empiric CFS to the Canadian ME/CFS case definition

Abstract:

This article contrasts two case definitions for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). We compared the empiric CFS case definition (Reeves et al., 2005) and the Canadian ME/CFS clinical case definition (Carruthers et al., 2003) with a sample of individuals with CFS versus those without. Data mining with decision trees was used to identify the best items to identify patients with CFS. Data mining is a statistical technique that was used to help determine which of the survey questions were most effective for accurately classifying cases. The empiric criteria identified about 79% of patients with CFS and the Canadian criteria identified 87% of patients. Items identified by the Canadian criteria had more construct validity. The implications of these findings are discussed.

© 2011 Wiley Periodicals, Inc.

 

Source: Jason LA, Skendrovic B, Furst J, Brown A, Weng A, Bronikowski C. Data mining: comparing the empiric CFS to the Canadian ME/CFS case definition. J Clin Psychol. 2012 Jan;68(1):41-9. doi: 10.1002/jclp.20827. Epub 2011 Aug 5. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3228898/ (Full article)