MétaCan
Menu
Back to cohort
Record 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 on OpenAlexaboutno aff
Rachel Sacks‐Davis, Daniela K van Santen, Joseph Doyle

Bibliographic record

VenueAddiction · 2019
Typeletter
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
FundersNational Health and Medical Research Council
KeywordsMedicineHepatitis CHepatitis C virusIncidence (geometry)CohortInternal medicineVirologyVirus

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.333
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueAddictionSame topicHepatitis C virus researchFrench-language works237,207