Is Naltrexone Effective and Safe for Treating Amphetamine-Type Stimulant Use Disorder? A Systematic Review and Meta-analysis
Bibliographic record
Abstract
OBJECTIVES: We conducted a systematic review and meta-analysis (PROSPERO ID: CRD42023401796) of randomized placebo-controlled trials evaluating the effectiveness and safety of naltrexone as a standalone pharmacotherapy for amphetamine-type stimulant use disorder (ATSUD). METHODS: We searched EMBASE, MEDLINE, EBM Reviews, PsycINFO, CINAHL, Google Scholar, and trial registries on April 11, 2023, and updated on September 24, 2024, to identify randomized placebo-controlled trials evaluating the effectiveness of naltrexone for the treatment of ATSUD. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines were followed for reporting the study. Risk of bias and quality of evidence were assessed with the Cochrane Risk-of-bias Assessment tool and the Grading of Recommendations, Assessment, Development, and Evaluation. Risk ratios (RRs) or Peto odds ratio were estimated for binary outcomes as appropriate. Standardized mean differences were calculated for continuous outcomes. RESULTS: Five studies (n = 419 participants) were eligible. We found no significant difference between naltrexone and placebo for amphetamine-type stimulant use (RR = 0.903, 95% confidence interval [CI] = 0.698 to 1.167, P = 0.44, I2 = 96.1%; 4 studies), study retention (RR = 1.055, 95% CI = 0.942 to 1.182, P = 0.35, I2 = 45.0%; 4 studies), end-of-treatment craving (standardized mean difference = 0.069, 95% CI = -0.272 to 0.410, P = 0.69, I2 = 0.0%; 2 studies), and serious adverse events (odds ratio = 1.086, 95% CI = 0.414 to 2.849, P = 0.87, I2 = 0.0%; 3 studies). The quality of evidence was low to very low. CONCLUSIONS: The available evidence does not support the use of standalone naltrexone to treat ATSUD. Significant research efforts must be put toward to identify effective pharmacotherapies to complement psychosocial interventions for ATSUD.
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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 | 0.039 | 0.084 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.029 | 0.050 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".