ArticleAddiction (Abingdon, England)2019
Post-marketing studies of pharmaceutical opioid abuse-deterrent formulations: a framework for research design and reporting.
Article in Addiction (Abingdon, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Abuse-deterrent formulations and opioid-related harms in North Carolina, 2010-2018.American journal of epidemiology · 2025Article
- Transparency in the secondary use of health data: assessing the status quo of guidance and best practices.Royal Society open science · 2025Article
- Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS).Pharmaceuticals (Basel, Switzerland) · 2022Article
- Observational
- Effectiveness and framing of pharmaceutical opioid abuse-deterrent formulations.Addiction (Abingdon, England) · 2019Article
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Authors and funding
7 authors.
Funding
Abstract
BACKGROUND AND
aimsOpioid formulations with properties to deter abuse (abuse-deterrent formulations; ADFs) have been developed as one response to the prescription opioid 'epidemic'. As for all medicines, ADFs undergo evaluation of safety and efficacy prior to registration for marketing. However, reduced extra-medical use (the primary intended outcome of ADFs and reason for their introduction) can only be established in post-marketing observational studies, comparing them to opioid formulations without abuse-deterrent properties. This has implications for various features of study design and analysis. We discuss proposals for the design, conduct, governance and reporting of post-marketing studies on the effectiveness of pharmaceutical and opioid ADFs.
methodsA review of current guidance documents, public work-shops and forums and our own experience with post-marketing studies of ADFs. RESULTS AND
conclusionsResearch questions for post-marketing studies on ADFs of opioids should reasonably be framed around detecting any probable intended or unintended clinical and/or meaningful changes in specific aspects of extra-medical use (e.g. injection use) and harms. Outcomes reported by prevalence and frequency of occurrence and disaggregated by specific product and route of administration can illustrate the magnitude of ADF impact. We argue that a multi-faceted approach is required, using data from both general population and sentinel high-risk cohorts and from primary and secondary data sources. The comparator (historical non-ADF formulation of that opioid, equivalent current generic or similar opioid product), duration of monitoring and analytical approach require justification and should be sufficient to add weight to conclusions of causality. To maximize transparency, we recommend explicit declarations of funding and conflict of interest, establishment of an advisory committee, publication of study protocol and access to study results.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.