Pharmacotherapies for Adults With Alcohol Use Disorders: A Systematic Review and Network Meta-analysis
Bibliographic record
Abstract
BACKGROUND: We aimed to determine medications' comparative efficacy and safety for adults with alcohol use disorders. METHODS: We searched eleven electronic data sources for randomized clinical trials with at least 4 weeks of treatment reporting on alcohol consumption (total abstinence and reduced heavy drinking), dropouts, and dropouts due to adverse events. We conducted network meta-analyses using random-effects, frequentist models, and calculated summary rate ratios (RRs) with 95% confidence intervals (CIs). RESULTS: We included 156 trials (N = 27,334). Nefazodone (RR = 2.11; 95% CI, 1.42-3.13), aripiprazole (RR = 1.97; 95% CI, 1.36-2.88), carbamazepine (RR = 1.85; 95% CI, 1.03-3.32), and nalmefene (RR = 1.17; 95% CI, 1.01-1.35) were associated with the most dropouts. Baclofen (RR = 0.83; 95% CI, 0.70-0.97) and pregabalin (RR = 0.63; 95% CI, 0.43-0.94) caused fewer dropouts than placebo. Nalmefene (RR = 3.26; 95% CI, 2.34-4.55), fluvoxamine (RR = 3.08; 95% CI, 1.59-5.94), and topiramate (RR=2.18; 95% CI, 1.36-3.51) caused more dropouts from adverse events over placebo. Gamma-hydroxy-butyrate (RR = 1.90; 95% CI, 1.03-3.53), baclofen (RR = 1.80; 95% CI, 1.39-2.34), disulfiram (RR = 1.71; 95% CI, 1.39-2.10), gabapentin (RR = 1.66; 95% CI, 1.04-2.67), acamprosate (RR = 1.33; 95% CI, 1.15-1.54), and oral naltrexone (RR = 1.15; 95% CI, 1.01-1.32) improved total abstinence over placebo (Fig. 3C). For reduced heavy drinking, disulfiram (RR = 0.19; 95% CI, 0.10-0.35), baclofen (RR = 0.72; 95% CI, 0.57-0.91), acamprosate (RR = 0.78; 95% CI, 0.70-0.86), and oral naltrexone (RR = 0.81; 95% CI, 0.73-0.90) were efficacious against placebo. CONCLUSIONS: The current meta-analyses provide evidence that several medications for AUDs are effective and safe and encourage the expanded use of these medications in the clinical setting. Our review found that acamprosate (2-3 g/d), disulfiram (250-500 mg/d), baclofen (30 mg/d), and oral naltrexone (50 mg/d) had the best evidence for improving abstinence and heavy drinking for patients with AUD. PROSPERO: CRD42020208946.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.031 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".