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


  • We appreciate the financial assistance provided by the National Institute of Allergy and Infectious Diseases (grant numbers AI36295 and AI49720).


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. J Clin Psychol 67:1–9, 2011.