Commentary on Nolan<i>et al</i>. (2014): Opiate substitution treatment and hepatitis C virus prevention: building an evidence base?
Notice bibliographique
Résumé
The beneficial effects of opiate substitution treatment (OST) for people who inject drugs (PWID) encompass multiple domains and outcomes. This includes decreasing HIV acquisition risk by half 1, reducing drug-related mortality 2, 3, possibly enhancing adherence to HIV anti-retroviral treatment 4, diminishing crime 5 and the societal costs associated with drug use 6, increasing quality of life 5 and sometimes employment status 7, 8. However, until recently, the evidence for OST or any harm reduction intervention reducing the risk of hepatitis C virus (HCV) acquisition was classified as insufficient 9, 10. This situation began to change 3 years ago, when a pooled UK analysis of selected observational studies suggested for the first time that OST could reduce HCV acquisition risk among PWID by more than 50% and that the combination of OST and high-coverage needle and syringe distribution could reduce HCV acquisition risk by up to 80% 11. In recent months there has been a further strengthening of the evidence base, with results from the Vancouver Injecting Drug Use Study (VIDUS) published in this issue of Addiction 12 and two other prospective studies of PWID from Australia 13 and San Francisco, USA 14, each reporting that OST can reduce the risk of HCV acquisition by 50–80% (Table 1). Despite a similar effect size across all four studies, an important difference between the Australian paper 13 and the analyses from Vancouver and San Francisco is that White et al. included PWID only for whom OST was potentially indicated—i.e. those who reported primarily injecting heroin or other opioids 13. In contrast, both the Vancouver and San Francisco papers were inclusive of all cohort participants, including those for whom OST may not be indicated (such as methamphetamine and cocaine injectors), so the protective effects may be underestimated. While it is encouraging that the size of the protective effect is consistent across the studies in multiple sites, we recognize that these studies are all observational and at greater risk of selection bias and confounding than randomized controlled trials. For instance, in the Nolan study 12 there was a considerable difference in the HCV prevalence among people receiving and not receiving OST at baseline (24 versus 76%), as well as differences in drug-using patterns, which may suggest that the difference in risk may not entirely be due to the direct effects of OST on injecting behaviours. Importantly, methadone and buprenorphine are essential medicines that cannot be randomized in future studies and so the evidence base will have to be built from non-randomized observational studies such as these. What are the implications of these results for designing HCV prevention strategies? First, as highlighted by a recent modelling analysis 15, OST averts infections, with projections from the United Kingdom suggesting that current high coverage levels of OST (50% of PWID are currently on OST in the United Kingdom) may have contributed to reducing the chronic HCV prevalence from 57 to the 40% chronic prevalence it is now. OST may also have an accumulating effect—the longer the average duration on OST the greater the impact on reducing HCV risk 12 and drug-related mortality 2. Indeed, because economic analyses suggest that OST could be cost-saving when societal benefits are accounted for 6, or at least highly cost-effective if only health benefits are considered 6, then it seems that there should be no argument against scaling-up OST in all settings. There is a long way to go until we achieve the high levels of OST coverage that currently exist in some settings, such as the United Kingdom and Australia. Data from the last systematic review of intervention coverage among PWID suggested that the world-wide coverage of OST was, at best, 8% 16, and although many countries have since initiated OST programmes, in most settings recent data continue to show inadequate coverage of OST 17. This raises the spectre of the potentially enormous global prevention gap. For example, adapted results from our previous modelling analysis 15 suggest that scaling-up OST world-wide could avert between 1 and 2 million HCV infections during the next 10 years if it was scaled-up from less than 10 to 50% coverage (8 million) of all PWID. Although these calculations warrant more detailed modelling to capture the heterogeneities in different epidemics, they none the less highlight the potential substantial prevention benefit of scaling up OST. It is important to note, however, that although recent results (Table 1) suggest that OST is an essential component of any future HCV prevention strategy, it is not the only answer to HCV prevention. HCV prevalence remains persistently high in many countries despite high coverage of OST and needle and syringe distribution. It is likely that only by also scaling-up antiviral treatment and prophylactic vaccine development for HCV that prevalence can be significantly reduced 18, 19. None.
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) | 0,001 | 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 | 0,001 |
| 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 ».