ArticleAlcoholism, clinical and experimental research2014
Predictors of abstinence from heavy drinking during treatment in COMBINE and external validation in PREDICT.
Article in Alcoholism, clinical and experimental research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Genetic contributions to alcohol use disorder treatment outcomes: a genome-wide pharmacogenomics study.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2021Pooled it
- Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice.Schizophrenia bulletin · 2021Pooled it
- Digital Cognitive Behavioral Therapy Reduces Heavy Drinking Among a Non-Treatment Sample of People With Alcohol Use Disorder: A Feasibility Trial With CBT4CBT.Alcohol, clinical & experimental research · 2026Trial
- Predictors of abstinence, no heavy drinking days, and a 2-level reduction in World Health Organization drinking levels during treatment for alcohol use disorder in the COMBINE study.Alcoholism, clinical and experimental research · 2022Trial
- Mindfulness-based relapse prevention for alcohol dependence: Findings from a randomized controlled trial.Journal of substance abuse treatment · 2019Trial
- Continuous Abstinence During Early Alcohol Treatment is Significantly Associated with Positive Treatment Outcomes, Independent of Duration of Abstinence.Alcohol and alcoholism (Oxford, Oxfordshire) · 2017Trial
- Predictors of Abstinence From Heavy Drinking During Follow-Up in COMBINE.Journal of studies on alcohol and drugs · 2015Trial
- An analysis of moderators in the COMBINE study: Identifying subgroups of patients who benefit from acamprosate.European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology · 2015Trial
- Combination of Drugs in the Treatment of Alcohol Use Disorder: A Meta-Analysis and Meta-Regression Study.Brain sciences · 2025Review
- Classical blood biomarkers identify patients with higher risk for relapse 6 months after alcohol withdrawal treatment.European archives of psychiatry and clinical neuroscience · 2021Article
- Loneliness and Alcohol use among College Students During the COVID-19 Pandemic in Rural Appalachia.Chronic stress (Thousand Oaks, Calif.)Article
- A modified classification tree method for personalized medicine decisions.Statistics and its interfaceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundThe 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.
methodsWe 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.
resultsThe 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.
conclusionsThe 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.