How can we investigate the role of topiramate in the treatment of cocaine use disorder more thoroughly?
Notice bibliographique
Résumé
We read with interest Darke & Farrell's 1 commentary on our meta-analysis of topiramate published in the eighth issue of 2016 2. To elaborate on some of the ideas raised by the commentary, we focus our response on the question of why some studies implied a benefit and others did not. Overall, although the current evidence is not strong enough to support the routine clinical use of topiramate for the treatment of cocaine use disorder, in certain circumstances it may be useful for researching in terms of helping people with cocaine use disorders to stay abstinent from cocaine use. A possible explanation for the negative findings among the studies may lay in different study designs and populations in the American 3-6 versus the Dutch 7 trials. The diverse study designs ranged from three double-blinded, placebo-controlled trials through the Dutch open label, non-placebo-controlled trial to a four-arm trial combined with contingency management (monetary vouchers), lasting for 18 weeks 7. Other issues with allocation concealment and attrition bias clearly weakened the study designs. Moreover, the outcome measures were not identical across trials that made them less amenable to meta-analysis. For instance, all trials used different craving scales: craving was assessed using the Brief Craving Scale 3, the Minnesota Cocaine Craving Scale 4, the Brief Substance Craving and Cocaine Selective Severity Assessment Scale 5, the Cocaine Selective Severity Assessment Scale 6 and via the adapted Obsessive Compulsive Drinking Scale 7. In terms of population diversity, most trials excluded people who had a concurrent use disorder on drugs other than cocaine; however, the excluded substance use disorders varied among the trials. For example, while Umbricht et al. 6 included people receiving methadone who also had a concurrent cocaine use disorder, Kampman et al. 4 included people with concurrent alcohol and cocaine use disorder. Apart from being an open-label design, the only Dutch trial also differed in several other ways: (i) the baseline cocaine use was higher, (ii) the maximal dose of topiramate was lower (200 mg/day) and (iii) the titration period was shorter (3 versus 8 weeks in the American trials). Furthermore, the included Dutch study implied that some type of adherence support intervention is necessary for pharmacotherapeutic approaches to managing cocaine use disorders 7. In this regard, as contingency management shows promise in the treatment of cocaine use disorder 8-10, it would be interesting to see how topiramate might perform in the context of an adherence-supporting contingency management intervention involving topiramate in comparison to placebo. Robust evaluations of this kind require uniform outcome measures and comparable populations that are amenable to pooling in meta-analyses and that may come later, as the literature on this molecule matures. Until such designs arrive, we will still keep ‘searching for the answer’ to the open question about the role of topiramate in the cocaine use disorder treatment, as posed in Darke & Farrell's commentary 1. None. The meta-analysis was not funded by an external source. The authors would like to thank the Addiction Medicine Fellowship program at St Paul's hospital for supporting this manuscript. Jan Klimas is supported by the ELEVATE grant: Irish Research Council International Career Development Fellowship, co-funded by Marie Curie Actions (ELEVATEPD/2014/6) and the European Commission grant (701698). This research was undertaken, in part, thanks to funding for a Tier 1 Canada Research Chair in Inner City Medicine, which supports E.W. D.W. is supported by a US National Institute on Drug Abuse Avenir Award (DP2 DA040256-01) and the Canadian Institutes of Health Research (MOP 79297).
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».