title: Predictors of abstinence from heavy drinking during treatment in COMBINE and external validation in PREDICT.
abstract: BACKGROUND
  The goal of the current study was to use tree-based methods (Zhang and Singer, 2010, Recursive Partitioning and Applications, 2nd ed. Springer, New York) to identify predictors of abstinence from heavy drinking in COMBINE (Anton et al. JAMA 2006; 295:2003), the largest study of pharmacotherapy for alcoholism in the United States to date, and to validate these results in PREDICT (Mann et al. Addict Biol 2012; 18:937), a parallel study conducted in Germany.
  
  
  METHODS
  We compared a classification tree constructed according to purely statistical criteria to a tree constructed according to a combination of statistical criteria and clinical considerations for prediction of no heavy drinking during treatment in COMBINE. We considered over 100 baseline predictors. The tree approach was compared to logistic regression. The trees and a deterministic forest identified the most important predictors of no heavy drinking for direct testing in PREDICT.
  
  
  RESULTS
  The tree built using both clinical and statistical considerations consisted of 4 splits based on consecutive days of abstinence (CDA) prior to randomization, age, family history of alcoholism, and confidence to resist drinking in response to withdrawal and urges. The tree based on statistical considerations with 4 splits also split on CDA and age but also on gamma-glutamyl transferase level and drinking goal. Deterministic forest identified CDA, age, and drinking goal as the most important predictors. Backward elimination logistic regression among the top 18 predictors identified in the deterministic forest analyses identified only age and CDA as significant main effects. Longer CDA and goal of complete abstinence were associated with better outcomes in both data sets.
  
  
  CONCLUSIONS
  The most reliable predictors of abstinence from heavy drinking were CDA and drinking goal. Trees provide binary decision rules and straightforward graphical representations for identification of subgroups based on response and may be easier to implement in clinical settings.
authors.affiliation: Yale University School of Public Health and School of Medicine, New Haven, CT 06520, USA.
authors.forename: Ralitza
authors.initials: R
authors.lastname: Gueorguieva
authors.affiliation: Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA.
authors.forename: Ran
authors.initials: R
authors.lastname: Wu
authors.affiliation: Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06519, USA.
authors.forename: Patrick G
authors.initials: PG
authors.lastname: O'Connor
authors.affiliation: Kaiser Permanente Division of Research, Oakland, CA 94612, USA.|Department of Psychiatry, University of California at San Francisco, San Francisco, CA 94143, USA.
authors.forename: Constance
authors.initials: C
authors.lastname: Weisner
authors.affiliation: Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA.
authors.forename: Lisa M
authors.initials: LM
authors.lastname: Fucito
authors.affiliation: Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, 68159, Germany.
authors.forename: Sabine
authors.initials: S
authors.lastname: Hoffmann
authors.affiliation: Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, 68159, Germany.
authors.forename: Karl
authors.initials: K
authors.lastname: Mann
authors.affiliation: Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA.
authors.forename: Stephanie S
authors.initials: SS
authors.lastname: O'Malley
mesh_terms: D000077443:Acamprosate; D000367:Age Factors; D064829:Alcohol Abstinence / Q000706:statistics & numerical data*; D000427:Alcohol Deterrents / Q000627:therapeutic use*; D000428:Alcohol Drinking / Q000097:blood / Q000628:therapy*; D001521:Behavior Therapy; D003131:Combined Modality Therapy; D018849:Controlled Clinical Trials as Topic; D003663:Decision Trees; D005858:Germany; D006040:Goals; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D009271:Naltrexone / Q000627:therapeutic use*; D011237:Predictive Value of Tests; D016032:Randomized Controlled Trials as Topic; D015203:Reproducibility of Results; D013654:Taurine / Q000031:analogs & derivatives* / Q000627:therapeutic use; D013997:Time Factors; D016896:Treatment Outcome; D014481:United States; D005723:gamma-Glutamyltransferase / Q000097:blood
chemical_list: D000427:Alcohol Deterrents; D013654:Taurine; D009271:Naltrexone; D005723:gamma-Glutamyltransferase; D000077443:Acamprosate
keywords: Alcohol Dependence; Classification Tree; Clinical Trial; Deterministic Forest; Logistic Regression