MétaCan
Menu
Retour à la cohorte
Enregistrement W2997063435 · doi:10.1111/add.14887

Commentary on Barré <i>et al</i>. (2020): Identifying remaining barriers to hepatitis C treatment in the DAA era

2019· letter· en· W2997063435 sur OpenAlexaboutno aff
Rachel Sacks‐Davis, Daniela K van Santen, Joseph Doyle

Notice bibliographique

RevueAddiction · 2019
Typeletter
Langueen
DomaineMedicine
ThématiqueHepatitis C virus research
Établissements canadiensnon disponible
Organismes subventionnairesNational Health and Medical Research Council
Mots-clésMedicineHepatitis CHepatitis C virusIncidence (geometry)CohortInternal medicineVirologyVirus

Résumé

récupéré en direct d'OpenAlex

Untreated alcohol use disorder delays time to starting hepatitis C virus (HCV) treatment among people who inject drugs, even in the direct-acting anti-virals era. We need to identify and minimize remaining barriers to engaging in HCV care, including alcohol and other social factors. Significant increases in hepatitis C virus (HCV) treatment uptake have been observed since the introduction of broad access to direct-acting anti-viral (DAA) therapies in many countries 1. However, treatment uptake is now beginning to decline in some countries, and those not treated within the first years of DAA access may be more challenging to reach 2, 3. In the interferon era, HCV treatment uptake was extremely low; for example, estimates from France, Australia and Canada reported that 4, 2 and 1%, respectively, of those with hepatitis C viraemia were treated annually before 2014 4. Treatment uptake was particularly low among people who inject drugs (PWID), a key group at risk of HCV infection 5, 6. Substantial increases in treatment uptake among PWID since DAA availability have been reported in some contexts. For example, in Australia, treatment uptake among those participating in repeat cross-sectional studies at needle and syringe programmes increased from 10% in 2015 to 41% in 2017 7, and the incidence of HCV treatment initiation in a cohort of PWID in Montreal, Canada, increased from 1.6/100 person-years in 2011 to 12.7 in 2017 8. In this issue of Addiction, Barre and colleagues 9 found that treatment uptake in France among PWID who have a history of opioid substitution therapy (OST) remained similarly low in the interferon era (2012–13) and early DAA era (2014–15): treatment initiation among HCV-diagnosed PWID was approximately 6 per 100 person-years in both time-periods. Irrespective of treatment regimen, PWID with untreated alcohol use disorders were less likely to start HCV treatment than PWID living with chronic HCV without alcohol use disorders or on treatment for alcohol use disorder. That said, the magnitude of the reduced likelihood of treatment uptake among those with untreated alcohol use disorders appeared to be larger in the interferon era. These results are in the context of restricted access to DAA therapy in France until May 2016 10, when advanced liver disease was removed as a treatment criterion. Barre and colleagues approach involved analyzing untreated alcohol use disorder as a potential barrier to HCV treatment before and after DAA introduction, allowing comparison between these two time-periods. The resulting analysis provided insight into the probable reduction in the effect size of alcohol use disorder as a barrier to HCV treatment. At the same time it highlighted that, although the effect may have been attenuated, those with untreated alcohol use continue to be less likely to be treated for HCV in France than other PWID. The effect of untreated alcohol use disorder prior to and after the introduction of DAA could be compared even more directly, and this comparison could be quantified by considering DAA introduction as a potential effect modifier. The authors suggest that treatment of alcohol use disorders will improve access to therapy in this group. Whether or not that is the case, their analysis highlights the group with untreated alcohol use as a potential target for interventions aimed at improving linkage to care, and for qualitative research in order to identify potentially effective interventions. Barre and colleagues’ data, coupled with emerging evidence from the United States, Canada and Australia, reveal that barriers to treatment uptake persist in the DAA era. Treatment uptake has been associated with important social factors, other than alcohol use, including not being on OST, illicit drug use, unstable housing and geographic location of residence 7, 8, 11-14. These findings are sobering in an era of optimism that it will be possible to change HCV epidemiology by treating sufficient numbers of people with ongoing risk behaviours 15. In the DAA era, where treatment courses are short, all-oral, with minimal side-effects and adherence is far less important as a predictor of treatment outcomes 16, the provider-side rationale for reluctance to treat people who use alcohol and illicit drugs no longer applies but some barriers to treatment may persist nonetheless. Applying Barre and colleagues’ comparative approach to other potential remaining barriers to HCV treatment pre- and post- DAA introduction would provide insight into progress made since the introduction of DAAs, the remaining challenges and the potential targets for interventions to connect those remaining HCV infected with DAA treatment. A key point is that we all need to work better to educate prescribers to adopt a patient-centred approach to HCV treatment. Instead of waiting for PWID ‘to be ready’ for treatment, perhaps we should ask ourselves: ‘why are we not discussing treatment today’? This message continues to be relevant in the DAA era. R.S.-D. and D.K.v.S. have no conflicts to report. J.S.D. receives investigator-initiated research grants and honorarium from Gilead, Abbvie, Merck and Bristol Myers Squibb. The authors acknowledge the contribution to this work of the Victorian Operational Infrastructure Support Program received by the Burnet Institute. R.S.-D. and J.S.D. receive fellowship support from the Australian National Health and Medical Research Council.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,011
score de la tête « metaresearch » (Gemma)0,064
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,073
Score d'incertitude au seuil0,081

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0110,064
Méta-épidémiologie (sens strict)0,0020,002
Méta-épidémiologie (sens large)0,0030,004
Bibliométrie0,0020,002
Études des sciences et des technologies0,0060,006
Communication savante0,0080,008
Science ouverte0,0100,004
Intégrité de la recherche0,0730,068
Charge utile insuffisante (le modèle a refusé de juger)0,0240,018

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 Opus0,031
Tête enseignante GPT0,333
Écart entre enseignants0,303 · 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 source (Gemma direct ou Codex distillé), 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

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueAddictionMême sujetHepatitis C virus researchTravaux en français237 207