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Enregistrement W2890969745 · doi:10.1111/add.14408

Commentary on Liang <i>et al</i>. (2018): The potential impact of medical cannabis on public health with respect to reducing prescription opioid use and associated harm

2018· letter· en· W2890969745 sur OpenAlexafffundabout
Jürgen Rehm

Notice bibliographique

RevueAddiction · 2018
Typeletter
Langueen
DomaineMedicine
ThématiqueCannabis and Cannabinoid Research
Établissements canadiensMental Health Research CanadaPublic Health OntarioUniversity of Toronto
Organismes subventionnairesInstitute of Neurosciences, Mental Health and AddictionCanadian Institutes of Health Research
Mots-clésMedical prescriptionMedicineCodeineMedicaidCannabisPsychiatryPublic healthOpioidPrescription Drug MisusePharmacologyHealth careOpioid use disorderInternal medicineMorphine

Résumé

récupéré en direct d'OpenAlex

Substitution of prescription opioid use by medical cannabis is not public health relevant, as it is restricted to substitution of a small subset of less potent opioids such as codeine. In addition, it substitutes one substance with abuse potential by another, and there are better alternatives available. Liang and colleagues 1 have presented a time–series analysis based on 21 years of state-level data of Medicaid records, in which they found that medical cannabis legalization was associated with substantial reductions in the number of Schedule III opioid prescriptions in the United States (−30%), their dosage (30%) and related Medicaid spending (−29%). Prescription opioids in Schedule III are characterized by lower abuse potential compared to opioids in Schedule II, with abuse of these opioids potentially leading to moderate or low physical dependence and/or high psychological dependence 2. In the analyses of Liang and colleagues 1, the Schedule III prescriptions made up only approximately 5% of all opioid prescriptions for the last year of analysis (2014), with codeine prescriptions comprising 99% of all Schedule III prescriptions. Codeine is used in the United States to treat mild to moderate pain and as a cough suppressant. Cannabis has been in use for both of these indications, and thus a substitution effect may be plausible. What would be the public health implications of a partial substitution? First, the overall substitution was not found to be affecting a large portion of the overall opioid prescription use. Secondly, however, codeine has an abuse potential. Although this abuse potential was evaluated to be lower compared to Schedule II opioids, abuse has been documented with both prescribed and over-the-counter codeine 3. Furthermore, codeine use may contribute as a gateway to other opioids, both prescription and illicit opioids, with high overdose potential 4, 5. Overall, the United States has, by far, globally the highest prescription opioid use per capita 6, and probably also the highest overall opioid use per capita in the world (i.e. combining prescription and illicit use), at least if indirectly inferred by opioid use disorders 7. The overall culture of medically overusing opioids has contributed markedly to this situation 8. What about cannabis? Its scheduling currently seems to be in flux, with many US states starting medical marijuana programs 9. However, while its consequences are not as detrimental as those of other drugs, in particular in terms of mortality 10, they are far from benign 11. Finally, the effectiveness of both codeine and cannabis for relieving moderate chronic pain seems to be limited, with no Cochrane Reviews supporting such a claim as primary drug of choice (e.g. 12, 13). Perhaps this judgement about effectiveness is premature for cannabis, with research to collect better evidence only now commencing, but it reflects the current evidence base. However, from a public health point of view, given the abuse potentials of both drugs involved, perhaps solutions should be sought with non-pharmacological therapies or with medications with less abuse potential than opioids or cannabis. The history of opioids in pain medication in North America should be a lesson. Despite limited evidence for effectiveness, prescription opioids were seen as a wonder drug, especially for pain management, with rapidly accelerating use to the point where they contributed markedly to a high level of opioid addiction on the population level and a major public health crisis 14, and decreasing life expectancies 15, 16. As a result, new national guidelines for opioid pain prescription stress non-pharmacological therapies and non-opioid medication as first-line treatment 17. We should not repeat this history with yet another wonder drug installed before proper evidence for effectiveness and well-documented unintentional consequences. Given the current evidence, there is no good reason not to start pain management with non-pharmacological therapies, but there are good reasons to limit the use of drugs with high abuse potential to the highest degree possible. None. The author acknowledges funding from the Canadian Institutes of Health Research, Institute of Neurosciences, Mental Health and Addiction (CRISM Ontario Node grant no. SMN-13950).

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,071
Score d'incertitude au seuil0,983

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,033
Tête enseignante GPT0,326
Écart entre enseignants0,294 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2018
Routes d'admission3
Résumé présentoui

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