Comparative effectiveness of alternative initial doses of opioid agonist treatment for individuals with opioid use disorder: a protocol for a retrospective population-based study using target trial emulation in British Columbia, Canada
Bibliographic record
Abstract
INTRODUCTION: Selecting an optimal initial dosage of opioid agonist treatment (OAT) balances effectiveness and safety, as initial doses that are too low may be insufficient, potentially prompting clients to seek unregulated drugs to alleviate withdrawal symptoms, which may increase the likelihood of treatment discontinuation. Conversely, initial doses that are too high carry a risk of overdose. As opioid tolerance levels have risen in the fentanyl era, linked population-level data capturing initial doses in the real world provide a valuable opportunity to refine existing guidance on optimal OAT dosing at treatment initiation. Our objective is to determine the comparative effectiveness of alternative initial doses of methadone, buprenorphine-naloxone and slow-release oral morphine at OAT initiation, as observed in clinical practice in British Columbia (BC), Canada. METHODS AND ANALYSIS: We propose a population-level retrospective observational study with a linkage of nine provincial health administrative databases in BC, Canada (1 January 2010 to 31 December 2022). Our study includes two time-to-event primary outcomes: OAT discontinuation and all-cause mortality during follow-up. We propose 'initiator' target trial analyses for each medication using both propensity score weighting and instrumental variable analyses to compare the effect of different initial OAT doses on the hazard of time-to-OAT discontinuation and all-cause mortality. A range of sensitivity analyses will be used to assess the robustness of the results. 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 Ethics Board and the Simon Fraser University Office of Research Ethics. 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
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 | 0.075 | 0.074 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".