Comparative effectiveness of missed dose protocols of opioid agonist treatment in British Columbia, Canada: protocol for a population-based target trial emulation
Bibliographic record
Abstract
INTRODUCTION: Methadone and buprenorphine/naloxone are effective medications for people with opioid use disorder; however, interruptions in daily dosing are common and diminish the benefits of these medications. While clinical guidelines in most North American jurisdictions, including British Columbia (BC), recommend dose adjustment after treatment interruptions to varying levels of specificity, the evidence to support these recommendations is limited. We aim to estimate the comparative effectiveness of alternative dose adjustment strategies on subsequent overdose-related acute care visits and discontinuation of opioid agonist treatment in BC, Canada. METHODS AND ANALYSIS: Using a linkage of nine health administrative databases, we propose a population-level retrospective cohort study of adults aged 18 years or older in BC who initiated methadone or buprenorphine/naloxone between 1 January 2010 and 31 December 2022. We will specify parallel hypothetical trials, known as target trials, for methadone interruptions of 1-3 days, 4 days and 5-14 days, and buprenorphine/naloxone interruptions of 1-5 days and 6-14 days. Following the index interruption, the primary outcomes are the time to overdose-related acute care visits and treatment discontinuation (interruptions lasting >14 days), with time to all-cause acute care visits as a secondary outcome. The intention-to-treat effect will be estimated using both propensity score and instrumental variable approaches. A range of sensitivity analyses will assess the robustness of our results, including cohort and timeline restriction, alternative definitions of exposure and outcome and alternative estimation strategies. ETHICS AND DISSEMINATION: The protocol, cohort creation and analysis plan have been classified and approved as a quality improvement initiative by Providence Health Care Research Institute and the Simon Fraser University Office of Research Ethics. All data are deidentified, securely stored and accessed in accordance with provincial privacy regulations. Results will be disseminated to local advocacy groups and decision-makers, national and international clinical guideline developers, presented at international conferences and published in peer-reviewed journals electronically and in print.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: yes · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
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 | 0.122 | 0.161 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".