Scientific and political challenges in North America's first randomized controlled trial of heroin-assisted treatment for severe heroin addiction: Rationale and design of the NAOMI study
Bibliographic record
Abstract
BACKGROUND: Heroin addiction is a chronic relapsing disease, best treated with opioid-agonist substitution therapy such as methadone maintenance. However, a subset of the most severely affected individuals do not benefit sufficiently from this treatment. The North American Opiate Medication Initiative (NAOMI) is a randomized clinical trial (RCT) to evaluate the hypothesis that pharmaceutical-grade heroin, diacetylmorphine (DAM) is more effective in retaining patients and improving their outcomes than Methadone Maintenance Treatment (MMT) among those with chronic, refractory injection opioid dependence. PURPOSE/METHODS: The study aimed at randomizing 253 participants to two intervention arms: (1) MMT alone or (2) injectable opioids (DAM or hydromorphone) plus adjunctive MMT if deemed appropriate. The planned study duration was 3 years, with a 1-year intake period, 1 year of treatment, and an additional year of follow-up. The NAOMI trial was initiated in March 2005 at two Canadian sites (Vancouver and Montreal). This was the first multicenter RCT in North America to compare the relative efficacy of these different therapeutic strategies. We discuss the rationale behind the NAOMI study design, as well as the scientific and political issues and methodological challenges arising from the conduct of a trial that involves the prescription of a controlled substance to individuals with dependence on that substance. LIMITATIONS: Restrictive entry criteria led to the exclusion of many otherwise eligible participants, slowing recruitment into the study. Inability to offer DAM treatment beyond 12 months led to artificial boundary effects in the trial. CONCLUSIONS: Addiction treatment research navigates between science and politics, and evidence-based medicine is many times confronted by moral beliefs. Political considerations influence study design to a further degree than in RCTs treating less-stigmatized disorders with more-reputable medications.
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 | 0.402 | 0.345 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.012 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".