Integrative data analysis of self-efficacy in 4 clinical trials for alcohol use disorder.

BACKGROUND: Self-efficacy has been proposed as a key predictor of alcohol treatment outcomes and a potential mechanism of success in achieving abstinence or drinking reductions following alcohol treatment. Integrative data analysis, where data from multiple studies are combined for analyses, can be used to synthesize analyses across multiple alcohol treatment trials by creating a commensurate measure and controlling for differential item functioning (DIF) to determine whether alcohol treatments improve self-efficacy. METHOD: The current study used moderated nonlinear factor analysis (MNLFA) to examine the effect of treatment on self-efficacy across four different treatment studies (N = 3720; 72.5% male, 68.4% non-Hispanic white). Self-efficacy was measured using the Alcohol Abstinence Self-Efficacy Scale (AASE) in the COMBINE Study (n = 1383) and Project MATCH (n = 1726), and the Drug Taking Confidence Questionnaire (DTCQ) in two studies of Telephone Continuing Care (TEL Study 1: n = 303; TEL Study 2: n = 212). DIF was examined across time, study, treatment condition, marital status, age, and sex. RESULTS: We identified 12 items from the AASE and DTCQ to create a commensurate measure of self-efficacy using MNLFA. All active treatments, including cognitive-behavioral treatment, a combined behavioral intervention, medication management, motivation enhancement treatment, telephone continuing care, twelve-step facilitation, and relapse prevention, were associated with significant increases in self-efficacy from baseline to posttreatment that were maintained for up to a year. Importantly, treatment as usual in community settings, which consisted of weekly group therapy that included addiction counseling and twelve-step recovery support, was not associated with significant increases in self-efficacy. CONCLUSIONS: Alcohol self-efficacy increases following treatment and numerous evidence-based treatments are associated with significant increases in self-efficacy, which are maintained over time. Community treatment that focuses solely on addiction counseling and twelve-step support may not promote increases in self-efficacy.

Temporal Stability of Heavy Drinking Days and Drinking Reductions Among Heavy Drinkers in the COMBINE Study.

BACKGROUND: Recently, the Food and Drug Administration (FDA) proposed to expand the options for primary end points in the development of medications for alcohol use disorder to include either abstinence from alcohol or a nonabstinent outcome: no heavy drinking days (with a heavy drinking day defined as more than 3 drinks per day for women and more than 4 drinks per day for men [>3/>4 cutoff]). The FDA also suggested that 6 months would be the most appropriate length for a clinical trial to demonstrate the stability of this nonabstinent drinking outcome. However, few alcohol clinical trials have examined the stability of nonheavy drinking during and after treatment. METHODS: In a secondary analysis of the COMBINE study data (n = 1,383), we examined transitions in heavy drinking days during the course of treatment (months 1 through 4), during the transition out of treatment (months 4 through 7), and up to 12 months afterward (months 13 through 16) using latent variable mixture models. RESULTS: Heavy drinking and nonheavy drinking were relatively stable in consecutive months (minimum agreement [kappa] = 0.64 for months 1 to 2). Most individuals were stable low-risk drinkers/abstainers or heavy drinkers by the end of treatment, as characterized by a 10% probability (or less) of transitioning out of either a no heavy drinking state or a heavy drinking state. More than two-thirds of the heavy drinkers who exceeded the heavy drinking threshold during treatment reported, on average, a 64% reduction in drinking frequency and a 38% reduction in drinking intensity from pretreatment drinking levels. CONCLUSIONS: The results show stability of no heavy drinking as an outcome within the first 4 months of treatment and that the >3/>4 drink cutoff may mask substantial reductions in alcohol consumption among some patients. Future studies should explore the clinical utility of reduction end points.

Missing Data in Alcohol Clinical Trials with Binary Outcomes.

BACKGROUND: Missing data are common in alcohol clinical trials for both continuous and binary end points. Approaches to handle missing data have been explored for continuous outcomes, yet no studies have compared missing data approaches for binary outcomes (e.g., abstinence, no heavy drinking days). This study compares approaches to modeling binary outcomes with missing data in the COMBINE study. METHODS: We included participants in the COMBINE study who had complete drinking data during treatment and who were assigned to active medication or placebo conditions (N = 1,146). Using simulation methods, missing data were introduced under common scenarios with varying sample sizes and amounts of missing data. Logistic regression was used to estimate the effect of naltrexone (vs. placebo) in predicting any drinking and any heavy drinking outcomes at the end of treatment using 4 analytic approaches: complete case analysis (CCA), last observation carried forward (LOCF), the worst case scenario (WCS) of missing equals any drinking or heavy drinking, and multiple imputation (MI). In separate analyses, these approaches were compared when drinking data were manually deleted for those participants who discontinued treatment but continued to provide drinking data. RESULTS: WCS produced the greatest amount of bias in treatment effect estimates. MI usually yielded less biased estimates than WCS and CCA in the simulated data and performed considerably better than LOCF when estimating treatment effects among individuals who discontinued treatment. CONCLUSIONS: Missing data can introduce bias in treatment effect estimates in alcohol clinical trials. Researchers should utilize modern missing data methods, including MI, and avoid WCS and CCA when analyzing binary alcohol clinical trial outcomes.

Guidelines for the Reporting of Treatment Trials for Alcohol Use Disorders.

BACKGROUND: The primary goals in conducting clinical trials of treatments for alcohol use disorders (AUDs) are to identify efficacious treatments and determine which treatments are most efficacious for which patients. Accurate reporting of study design features and results is imperative to enable readers of research reports to evaluate to what extent a study has achieved these goals. Guidance on quality of clinical trial reporting has evolved substantially over the past 2 decades, primarily through the publication and widespread adoption of the Consolidated Standards of Reporting Trials statement. However, there is room to improve the adoption of those standards in reporting the design and findings of treatment trials for AUD. METHODS: This paper provides a narrative review of guidance on reporting quality in AUD treatment trials. RESULTS: Despite improvements in the reporting of results of treatment trials for AUD over the past 2 decades, many published reports provide insufficient information on design or methods. CONCLUSIONS: The reporting of alcohol treatment trial design, analysis, and results requires improvement in 4 primary areas: (i) trial registration, (ii) procedures for recruitment and retention, (iii) procedures for randomization and intervention design considerations, and (iv) statistical methods used to assess treatment efficacy. Improvements in these areas and the adoption of reporting standards by authors, reviewers, and editors are critical to an accurate assessment of the reliability and validity of treatment effects. Continued developments in this area are needed to move AUD treatment research forward via systematic reviews and meta-analyses that maximize the utility of completed studies.