Outcome predictors for problem drinkers treated with combined cognitive behavioral therapy and naltrexone

Abstract

Background: The opioid antagonist naltrexone, combined with cognitive behavioural therapy (CBT), has proven efficacious for patients with alcohol dependence, but studies examining how this treatment works in a naturalistic treatment setting are lacking. Objectives: This study examined predictors of the outcome of targeted naltrexone and CBT in a real-life outpatient setting. Participants were 315 patients who attended a treatment program providing CBT combined with the targeted use of naltrexone. Methods: Mixture models for estimating developmental trajectories were used to examine change in patients’ alcohol consumption and symptoms of alcohol craving from treatment entry until the end of the treatment (20 weeks) or dropout. Predictors of treatment outcome were examined with analyses of multinomial logistic regression. Minimal exclusion criteria were applied to enhance the generalizability of the findings. Results: Regular drinking pattern, having no history of previous treatments, and high-risk alcohol consumption level before the treatment were associated with less change in alcohol use during the treatment. The patients with low-risk alcohol consumption level before the treatment had the most rapid reduction in alcohol craving. Patients who drank more alcohol during the treatment had lower adherence with naltrexone. Conclusion: Medication non-adherence is a major barrier to naltrexone’s effectiveness in a real-life treatment setting. Patients with more severe alcohol problems may need more intensive treatment for achieving better treatment outcome in real-word treatment settings.

• Alcohol dependence
• cognitive behavioural therapy
• naltrexone
• problem drinking
• predictors

Acknowledgements

The authors would like to thank CEO Jukka Keski-Pukkila, from ContrAl Clinics, Finland for his permission to use the data for the current study. The appreciation is extended to Panu Keski-Pukkila who helped with gathering the data and to Benita Jakobson and David Sinclair for their help in planning the study.

This study was partly funded by the Finnish Addiction Society and Lundbeck A/S (SV-M).

Supplementary material available online

Supplementary Table 1: Baseline Patient Characteristics (n = 315)

Supplementary Table 2: The intercorrelations between predictive variables

Supplementary content can be viewed and downloaded at http://informahealthcare.com/ada.