Impact of baseline methamphetamine/amphetamine use on discontinuation of methadone and buprenorphine/naloxone among people with prescription‐type opioid use disorder in Canada
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Although concurrent stimulant use is common among people with opioid use disorder (OUD), there is little evidence on its impacts on opioid agonist therapy (OAT) outcomes. This study sought to determine the impact of baseline methamphetamine/amphetamine use on discontinuation of OAT among individuals with prescription-type OUD (POUD) initiating methadone or buprenorphine/naloxone as part of a pragmatic randomized trial in Canada. METHODS: Secondary analysis of a pan-Canadian pragmatic trial conducted between 2017 and 2020 comparing supervised methadone versus flexible take-home dosing buprenorphine/naloxone models of care. Cox proportional hazard models were used to evaluate the effect of baseline methamphetamine/amphetamine use (measured by urine drug test [UDT]) on two discontinuation outcomes (i.e., assigned OAT discontinuation, any OAT discontinuation). RESULTS: Two hundred nine (n = 209) participants initiated OAT, of which 96 (45.9%) had positive baseline methamphetamine/amphetamine UDT. Baseline methamphetamine/amphetamine use was associated with shorter median times in assigned OAT (21 vs. 168 days, hazard ratio [aHR] = 2.45, 95% confidence interval [CI] = 1.60-3.76) and any OAT (25 days vs. 168 days, aHR = 2.06, CI = 1.32-3.24). No interaction between methamphetamine/amphetamine and assigned OAT was observed for either outcome (p > .05). CONCLUSION AND SCIENTIFIC SIGNIFICANCE: This study offers novel insights on the impact of methamphetamine/amphetamine use on OAT outcomes among people with POUD. Methamphetamine/amphetamine use was common and was associated with increased risk of OAT discontinuation. Supplementary interventions, including treatment for stimulant use, are needed to improve retention in OAT and optimize treatment outcomes in this population.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".