Predicting group cognitive-behavioral therapy outcome of binge eating disorder using empirical classification

The purpose of this study was to use empirical classification based on Latent Profile Analysis to identify subgroups of binge eating disorder (BED) and to evaluate the extent to which these subgroups were predictive of treatment outcome in group cognitive-behavioral therapy (CBT). The Eating Disorder Examination (EDE), Structured Clinical Interview for DSM-IV, and Inventory of Depressive Symptomatology-Self-Report were administered to 259 participants at baseline in a 15-session CBT trial (190 of whom received active treatment). The best fitting model included three profiles: dietary restraint only (DRO; n = 96; 51%); low dietary restraint (LDR; n = 52; 27%); and dietary restraint plus psychopathology (DRP; n = 42; 22%). Regression analyses revealed that after controlling for baseline score and treatment condition, EDE Global scores were lower for the DRO compared to the LDR profile at one year follow-up (p = .047). Class assignment was not predictive of EDE binge eating frequency or abstinence at end of treatment or follow-up. These results suggest that meaningful empirical classes based on eating disorder symptoms, psychopathology, dietary restraint, and BMI can be identified in BED and that these classes may be useful in predicting long-term group CBT outcome.