# Evolution of patients’ socio-behavioral characteristics in the context of DAA: Results from the French ANRS CO13 HEPAVIH cohort of HIV-HCV co-infected patients

Issifou Yaya, Perrine Roux, Fabienne Marcellin, Linda Wittkop, Laure Esterle, Bruno Spire, Stéphanie Domínguez, Boni Armand Elegbe, Lionel Piroth, Philippe Sogni, et al.

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Issifou Yaya, Perrine Roux, Fabienne Marcellin, Linda Wittkop, Laure Esterle, et al. Evolution of patients’ socio-behavioral characteristics in the context of DAA: Results from the French ANRS CO13 HEPAVIH cohort of HIV-HCV co-infected patients. PLoS ONE, 2018, 13 (7), pp.e0199874. 10.1371/journal.pone.0199874. hal-02146246

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RESEARCH ARTICLE

# Evolution of patients' socio-behavioral characteristics in the context of DAA: Results from the French ANRS CO13 HEPAVIH cohort of HIV-HCV co-infected patients

Issifou Yaya¹,²*, Perrine Roux¹,², Fabienne Marcellin¹,², Linda Wittkop³,⁴, Laure Esterle³, Bruno Spire¹,², Stéphanie Dominguez⁵, Boni Armand Elegbe¹,², Lionel Piroth⁶, Philippe Sogni⁷, Dominique Salmon-Ceron⁸, Maria Patrizia Carrieri¹,², the ANRS CO13 HEPAVIH Study Group¹¶

1 Aix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Economiques & Sociales de la Santé & Traitement de l'Information Médicale, Marseille, France, 2 ORS PACA, Observatoire régional de la santé Provence-Alpes-Côte d'Azur, Marseille, France, 3 Univ. Bordeaux, ISPED, INSERM, Bordeaux Population Health Research Center, team MORPH3EUS, UMR 1219, CIC-EC 1401, Bordeaux, France, 4 CHU de Bordeaux, Pole de santé publique, Service d'information médicale, Bordeaux, France, 5 INSERM U955, AP-HP, Groupe Henri-Mondor Albert-Chenevier, Immunologie Clinique et Maladies Infectieuses, Créteil, France, 6 Département d'Infectiologie, Centre Hospitalier Universitaire and INSERM CIC 1432, Université de Bourgogne, Dijon, France, 7 Université Paris Descartes, INSERM U-1223, Institut Pasteur, Service d'Hépatologie, hôpital Cochin, Assistance Publique-Hôpitaux de Paris, Paris, France, 8 Université Paris Descartes, Service Maladies Infectieuses et Tropicales, AP-HP, Hôpital Cochin, Paris, France

¶ The ANRS CO13 HEPAVIH Study Group is presented in the Acknowledgments section.

* issifou.yaya@inserm.fr

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## OPEN ACCESS

**Citation:** Yaya I, Roux P, Marcellin F, Wittkop L, Esterle L, Spire B, et al. (2018) Evolution of patients' socio-behavioral characteristics in the context of DAA: Results from the French ANRS CO13 HEPAVIH cohort of HIV-HCV co-infected patients. PLoS ONE 13(7): e0199874. https://doi.org/10.1371/journal.pone.0199874

**Editor:** Yury E. Khudyakov, Centers for Disease Control and Prevention, UNITED STATES

**Received:** September 7, 2017

**Accepted:** June 15, 2018

**Published:** July 5, 2018

**Copyright:** © 2018 Yaya et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

**Data Availability Statement:** Data for the statistical analysis are available from the scientific committee of the ANRS CO13-HEPAVIH cohort. The contact information for an institutional body to which data requests may be sent is as follows: Maria-Patrizia Carrieri, AMU, INSERM U1252, ORS PACA, IHU, 19-21 Boulevard Jean Moulin 13005, Marseille, France; E-mail: maria-patrizia.carrieri@inserm.fr.

**Funding:** This work was supported by the French National Agency for Research on AIDS and Viral

## Abstract

### Background

Direct-acting antivirals (DAA) have dramatically increased HCV cure rates with minimal toxicity in HIV-HCV co-infected patients. This study aimed to compare the socio-behavioral characteristics of patients initiating pegylated-interferon (PEG-IFN)-based HCV treatment with those of patients initiating DAA-based treatment.

### Methods

ANRS CO13 HEPAVIH is a national multicenter prospective cohort started in 2005, which enrolled 1,859 HIV-HCV co-infected patients followed up in French hospital outpatient units. Both clinical/biological and socio-behavioral data were collected during follow-up. We selected patients with socio-behavioral data available before HCV treatment initiation.

### Results

A total of 580 patients were included in this analysis. Of these, 347 initiated PEG-IFN-based treatment, and 233 DAA-based treatment. There were significant differences regarding patient mean age (45 years±6 for the PEG-IFN group vs. 52 years±8 for the DAA group, p<0.001), unstable housing (21.4% vs. 11.2%, p = 0.0016), drug use (44.7% vs. 29.6%, p = 0.0003), regular or daily use of cannabis (24.3% vs. 15.6%, p = 0.0002), a history of drug
Hepatitis (ANRS), with the participation of Abbott France; Glaxo-Smith-Kline; Roche; Schering-Plough; and INSERM's 'Programme Cohortes TGIR'. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There was no additional external funding received for this study.

**Competing interests:** LW reports grants from ANRS, during the conduct of the study; grants from Inserm Aviesan, personal fees from BMS, Janssen, Gilead and MSD outside the submitted work; LP reports personal fees from Bristol Myers Squibb, Gilead, Viiv Healthcare, MSD, Pfizer, Gilead, Janssen Cilag, outside the submitted work. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

injection (68.9% vs 39.0%, p<0.0001) and significant liver fibrosis (62.4% vs 72.3%, p = 0.0293). In multivariable analysis, patients initiating DAA-based treatment were older than their PEG-IFN-based treatment counterparts (aOR = 1.17; 95%CI [1.13; 1.22]). Patients receiving DAA treatment were less likely to report unstable housing (0.46 [0.24; 0.88]), can-nabis use (regular or daily use:0.50 [0.28; 0.91]; non-regular use: 0.41 [0.22; 0.77]), and a history of drug injection (0.19 [0.12; 0.31]).

## Conclusion

It is possible that a majority of patients who had socio-economic problems and/or a history of drug injection and/or a non-advanced disease stage were already treated for HCV in the PEG-IFN era. Today, patients with unstable housing conditions are prescribed DAA less frequently than other populations. As HCV treatment is prevention, improving access to DAA remains a major clinical and public health strategy, in particular for individuals with high-risk behaviors.

## Introduction

Chronic hepatitis C virus (HCV) infection is an endemic disease that affects approximately 71 million people worldwide [1], with significant regional variability. In recent decades, great progress has been made in treating chronic HCV infection. First-generation treatments were mainly composed of pegylated interferon (PEG-IFN) and ribavirin and were administered for at least 48 weeks. The response rate was 60-70% for genotypes 2 and 3 but lower for genotypes 1 and 4 [2]. Moreover, PEG-IFN-based treatments had significant side effects including flu-like symptoms, asthenia, neuropsychiatric symptoms, hematological toxicity, rashes, and more lifetime complications [3,4].

The recent emergence of a new generation of treatments—direct-acting antivirals (DAA)—constitutes a revolution in HCV care. DAA are more effective and better tolerated than PEG-IFN and ribavirin, and in 8 to 24 weeks a sustained virological response (SVR) is obtained in over 90% of treated patients, including previously difficult-to-treat patients and HIV-HCV co-infected patients [5-8].

However, the costs of DAA are very high, and access varies across global regions. Even in countries with a universal health system, restricted access is not uncommon [9,10]. Germany and the United Kingdom are two countries that immediately implemented universal access to DAA treatment [11], and all patients infected with HCV are treated unconditionally. In both the PEG-IFN and DAA eras, in some countries, the most common barriers to initiating HCV treatment in HIV-HCV co-infected patients include psychoactive substance use, and social instability such as homelessness or imprisonment [12].

In May 2016 the French Ministry of Health announced universal access to DAA [13]. Before this announcement, initiating DAA treatment was subject to a multidisciplinary consultation meeting (RCP) which evaluated its relevance on a case by case basis [14]. Clinical criteria were usually the basis for selecting patients for DAA treatment. We do not know to what extent other patient characteristics, especially those that may limit patients' acceptability of, engagement in, or adherence to treatment, influenced selection for DAA initiation [10,15]. Injecting drug use is a well described factor which can delay HCV treatment initiation [16]. It has also been reported that HCV-infected patients with psychiatric disorders are less likely to
benefit from HCV treatment. In France, Roux et al [17] also reported that people who inject drugs (PWID) (currently or in the past) were less likely to be treated for HCV in the PEG-IFN era. However, a previous study using data collected during the ANRS CO13 HEPAVIH cohort showed no relationship between a history of injecting drug use and access to PEG-IFN+ ribavirin treatment [18]. While the HCV infection epidemic in France, and more generally in Europe, has mainly been driven by injecting drug use [19], recent data suggest the epidemiology of HCV infection in HIV patients is changing [20]. Given that national HCV guidelines strongly recommend access to HCV treatment for HIV patients [14] and that free access to DAA has been possible since May 2016 in France, we aimed to compare the socio-behavioral characteristics of patients initiating HCV treatment in the ANRS CO13 HEPAVIH cohort between those receiving PEG-IFN-based treatment and those receiving DAA, our hypothesis being that patients' characteristics may play an important role in caregiver-patient relationships, as well as in access to and retention in the HCV and HIV care systems.

Our objective was not simply to identify possible barriers to accessing DAA treatment, but also to highlight the change in the profile of HIV-HCV co-infected patients initiating HCV treatment.

# Methods

## Study design and population

ANRS CO13 HEPAVIH is a multicenter observational cohort initiated in France in 2005 among HIV-HCV co-infected patients to characterize the natural history of co-infection in terms of both morbidity and mortality and their determinants, and to better understand the interactions between the two viruses and treatments [21]. ANRS CO13 HEPAVIH recruited outpatients from 32 clinical centers in France who were aged 18 or over, had both chronic hepatitis C and HIV infection, had detectable plasma HCV RNA, were positive for anti-HCV antibodies, and agreed to participate in the cohort (a signed letter of informed consent being provided).

Patient recruitment for this cohort included three phases:

* The first phase between December 2005 and December 2008 recruited adult HIV-positive patients, who were also either chronically infected by HCV at enrollment or had a negative HCV RNA test by PCR six months after ending HCV treatment (PEG-IFN),

* The second phase, from September 2011 to March 2016, recruited both individuals who spontaneously cleared HCV before the enrolment, and HIV-HCV infected patients who initiated HCV treatment with triple therapy (PEG-IFN + ribavirin + either telaprevir or boceprevir),

* The third phase, from May 2014 to November 2015, was an additional recruitment phase, where patients who were already receiving, or were scheduled to receive DAA within six months, were recruited.

In France, PEG-IFN+ ribavirin first became available in 2000. Boceprevir and Telaprevir became available in 2010. All three regimens were replaced from 2014 onwards with DAA.

In the present study, we included all cohort patients who had received or were still receiving HCV treatment, whether PEG-IFN-based in the first phase of the cohort or DAA-based in the third phase (Fig 1).

We preferred to exclude Phase 2 patients from this comparison for two reasons: first, a very small sample were eligible for this study, mainly patients in a severe state of illness and patients who were very unresponsive to Phase 1 treatment (ie PEG-IFN+Ribavirin) due to the high
<figure><img src="image_5.png" /><figcaption>Fig 1. Flow chart of the patients included in the study.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0199874.g001

toxicity of this treatment. In addition, patients in the Phase 2 did not complete the annual self-administered questionnaires.

## Data collection

For patients included in the first recruitment phase, clinical visits were scheduled annually for non-cirrhotic patients and every six months for cirrhotic patients. Collection of socio-behavioral data using self-administered questionnaires (SAQ) was scheduled annually. For patients initiating HCV treatment, additional visits were scheduled, before, during and after the end of treatment. For patients included in the third recruitment phase receiving DAA, clinical and biological data were collected at treatment initiation, at the end of treatment, and six months
after the end of treatment, using medical questionnaires. These data included weight, blood pressure, clinical stage of HIV infection, blood count, immuno-virological data, hepatic and renal assessment values, HCV RNA PCR measurements, and data on HCV and HIV treatments (drug, dosage, indication, initiation date and date of treatment end).

Socio-behavioral data were collected from SAQ at treatment initiation and at the end of treatment. The SAQ included items concerning patients' socio-demographic characteristics and information on patients' use of psychoactive drugs, tobacco, and alcohol (AUDIT-C).

## Variables

**Alcohol consumption.** Alcohol consumption was measured using the AUDIT-C questionnaire. This scale is composed of three questions each of which having four possible answers (i.e., a score ranging from 0 to 4; total scale score ranging from 0 to 12). Hazardous alcohol consumption was defined as having a AUDIT-C score ≥ 4 for men or ≥ 3 for women [22]. Binge drinking was defined as consuming six or more alcoholic drinks on any one occasion during the previous month.

**Drug use.** Patients were asked about their consumption of the following psychoactive substances during the previous four weeks: cannabis, cocaine, crack, heroin, ecstasy, amphetamines, LSD. With regard to cannabis consumption, patients were classified into three categories: "No use", "non-regular use" and "regular or daily use."

**Tobacco consumption.** Tobacco smoking (smoking status, history of smoking, number of cigarettes per day) was assessed during face-to-face interviews with physicians for patients in the first and second recruitment phases and using self-administered questionnaires for patients from the third phase.

**Unstable housing conditions.** Patients who were neither tenant nor owner of their housing were considered to have unstable housing.

For the evaluation of liver fibrosis, we used the FIB4 index obtained by the following formula [23]

$$ \text{Fib4 index} = \frac{\text{Age (year)} * \text{AST (U/L)}}{\text{Platelets count (10}^9/\text{L)} * \sqrt{\text{ALT (U/L)}}} $$

Severe fibrosis or cirrhosis was defined as a FIB-4 index score >3.25. A FIB-4 score between 1.45 and 3.25 corresponded to moderate fibrosis and <1.45 to no clinically significant fibrosis [24]. A FIB-4 score above 1.45 corresponded to significant fibrosis.

## Statistical analyses

Statistical analyses were performed using SAS software, version 9.4 (SAS Institute, Cary, North Carolina). The main characteristics of patients at HCV treatment initiation were compared between patients initiating PEG-IFN-based treatment (Phase 1) and those initiating DAA (Phase 3) (chi-square test for categorical variables, Student's t test for continuous variables). We used data from the SAQ completed at the visit closest to the date of treatment initiation for patients receiving PEG-IFN treatment (Fig 1). For patients receiving DAA, we used data collected during the visit scheduled at the beginning of treatment.

A multivariable analysis was then performed with logistic regression models, using a binary variable indicating the type of treatment received (PEG-IFN vs DAA) as the dependent variable. All significant variables with a p-value of <0.20 in the univariate analyses were introduced into the multivariable regression model to estimate the adjusted effect and derive the adjusted odds ratio (aOR) for each of the dependent variables. A 95% confidence level was also estimated for each aOR.
In order to verify the robustness of the results and exclude possible recruitment phase bias, i.e. the possibility that patients recruited in the third phase had a different pattern of socio-behavioral characteristics from the patients in the first phase, a sensitivity analysis was conducted which included only patients followed up in clinical centers involved in all three phases of the cohort.

## Ethics statement

This study was approved by the "Comité de Protection des Personnes (CPP)" (Ref N° 2234 on April 19th, 2005) and the "Commission Nationale de l'Information et des Libertés de France (CNIL)" on September 6th, 2005. Participant provided signed, informed consent.

## Results

### Participants' characteristics

A total of 580 HIV-HCV co-infected patients treated for chronic hepatitis C during the follow-up were included in the study (Fig 1). Mean age was estimated at 47.8 years±7.6 (range 23 to 71 years). Most were male (75.9%; 439/578) and just under a fifth (17.4%; 99/569) had unstable housing (Table 1).

Of the total patient sample, 233 (40.2%) were on DAA. These individuals were significantly older than those who received PEG-IFN treatment (p = 0.0001) (Table 1). A significantly higher proportion of patients who received PEG-IFN treatment (21.4%) had unstable housing conditions (vs those receiving DAA (11.2%)) (p = 0.0016). (Table 1).

### Addictive behaviors

Just under two-thirds (65.1%; 364/559) of the study population were active tobacco smokers. No significant difference was observed between the two groups (Table 1).

Of the total study population, 27.8% (155/557) reported hazardous alcohol consumption and 27.2% (151/555) binge drinking. No significant difference was detected between the two groups of patients regarding hazardous alcohol consumption (29.1% among PEG-IFN-treated patients vs 25.7% among DAA-treated patients, p = 0.3866) and binge drinking (27.3% vs 27.0%, p = 0.9362) (Table 1).

In terms of drug use, two-fifths of the total population (38.6%; 224/580) were drug users. One-fifth were regular or daily cannabis users: 20.7% (107/516) (Table 1). Almost three-fifths (56.7%; 317/559) had a history of drug injection. Although, the proportion of patients who reported drug use was significantly higher in the PEG-IFN group (44.7% vs 29.6%, p = 0.0003), the consumption of drugs other than cannabis did not differ between both treatment groups (p = 0.98). The proportion of patients who reported regular cannabis consumption was significantly lower in the DAA group (15.6% vs 24.3%, p = 0.0002). Moreover, the proportion of patients with a history of drug injection was significantly higher in the PEG-IFN group (68.9% vs 39.0%; p<0.0001) (Table 1). Finally, the proportion of patients with a history of drug injection was significantly higher among those who had unstable housing than among those who did not (71.7% vs 54.4%, p = 0.0016).

In terms of clinical characteristics, two-thirds of the study population (65.5%) had significant liver fibrosis. The proportion of patients with significant fibrosis was higher in the DAA group (72.3% vs 62.4%, p = 0.0293) (Table 1).

### Multivariable analysis

In the multivariable analysis, only age, unstable housing, cannabis use and a history of drug injection remained associated with the type of HCV treatment received.
<table><caption>Table 1. Comparison of patients' socio-behavioral profiles at HCV treatment initiation in the ANRS CO13 HEPAVIH cohort (N = 580).</caption><thead><tr><th rowspan="2">Patients' characteristics</th><th rowspan="2">N (%)</th><th colspan="3">Univariate analysis</th><th rowspan="2">Multivariable analysis<br>aOR [95% CI]</th></tr><tr><th>PEG-IFN treatment N (%)</th><th>DAA treatment N (%)</th><th>p-value</th></tr></thead><tbody><tr><td>HCV treatment</td><td>580</td><td>-</td><td>-</td><td>-</td><td></td></tr><tr><td>Peg-IFN</td><td>347 (59.8)</td><td></td><td></td><td></td><td></td></tr><tr><td>DAA</td><td>233 (40.2)</td><td></td><td></td><td></td><td></td></tr><tr><td>Age</td><td>572</td><td>347</td><td>225</td><td>0.0001</td><td>1.17 [1.13; 1.22]</td></tr><tr><td>Mean (SD)</td><td>47.8 (7.6)</td><td>45.1 (6.2)</td><td>52.00 (7.8)</td><td></td><td></td></tr><tr><td>Median (IQR)</td><td>48 (43–52)</td><td>45 (42–49)</td><td>52 (49–56)</td><td></td><td></td></tr><tr><td>Gender</td><td>578</td><td>347</td><td>231</td><td>0.270</td><td></td></tr><tr><td>Male</td><td>439 (75.9)</td><td>258 (74.4)</td><td>181 (78.4)</td><td></td><td></td></tr><tr><td>Female</td><td>139 (24.1)</td><td>89 (25.6)</td><td>50 (21.6)</td><td></td><td></td></tr><tr><td>Living in a couple</td><td>573</td><td>345</td><td>228</td><td>0.835</td><td></td></tr><tr><td>Yes</td><td>277 (48.3)</td><td>168 (48.7)</td><td>109 (47.8)</td><td></td><td></td></tr><tr><td>No</td><td>296 (51.7)</td><td>177 (51.3)</td><td>119 (52.2)</td><td></td><td></td></tr><tr><td>Unstable housing<sup>1</sup></td><td>569</td><td>345</td><td>224</td><td>0.0016</td><td></td></tr><tr><td>Yes</td><td>99 (17.4)</td><td>74 (21.4)</td><td>25 (11.2)</td><td></td><td>0.46 [0.24; 0.88]</td></tr><tr><td>No</td><td>470 (82.6)</td><td>271 (78.6)</td><td>199 (88.8)</td><td></td><td>1</td></tr><tr><td>Plasma HIV-RNA &lt;50 copies/ml</td><td>442</td><td>345</td><td>97</td><td>0.0003</td><td></td></tr><tr><td>Yes</td><td>372 (84.2)</td><td>279 (80.9)</td><td>93 (95.9)</td><td></td><td></td></tr><tr><td>No</td><td>70 (15.8)</td><td>66 (19.1)</td><td>4 (4.1)</td><td></td><td></td></tr><tr><td>CD4 count-cells/mm<sup>3</sup></td><td>442</td><td>342</td><td>100</td><td>0.0007</td><td></td></tr><tr><td>Mean (SD)</td><td>511 (278)</td><td>474 (251)</td><td>641 (325)</td><td></td><td></td></tr><tr><td>Median (IQR)</td><td>462 (303–656)</td><td>430 (287–599)</td><td>628 (411–838)</td><td></td><td></td></tr><tr><td>HCV viral load, log<sub>10</sub> UI/ml</td><td>364</td><td>265</td><td>99</td><td>&lt;0.001</td><td></td></tr><tr><td>Mean (SD)</td><td>13.6 (2.1)</td><td>13.6 (2.3)</td><td>13.7 (1.5)</td><td></td><td></td></tr><tr><td>Median (IQR)</td><td>13.9 (12.8–15.0)</td><td>14 (12.7–15.2)</td><td>13.8 (13–14.7)</td><td></td><td></td></tr><tr><td>Tobacco smoking</td><td>559</td><td>328</td><td>231</td><td>0.0896</td><td></td></tr><tr><td>Yes</td><td>364 (65.1)</td><td>223 (68.0)</td><td>141 (61.0)</td><td></td><td></td></tr><tr><td>No</td><td>195 (34.9)</td><td>105 (32.0)</td><td>88 (39.0)</td><td></td><td></td></tr><tr><td>Hazardous alcohol consumption<sup>2</sup></td><td>557</td><td>347</td><td>210</td><td>0.3866</td><td></td></tr><tr><td>Yes</td><td>155 (27.8)</td><td>101 (29.1)</td><td>54 (25.7)</td><td></td><td></td></tr><tr><td>No</td><td>402 (72.2)</td><td>246 (70.9)</td><td>156 (74.3)</td><td></td><td></td></tr><tr><td>Binge drinking<sup>3</sup></td><td>555</td><td>344</td><td>211</td><td>0.9362</td><td></td></tr><tr><td>Yes</td><td>151 (27.2)</td><td>94 (27.3)</td><td>57 (27.0)</td><td></td><td></td></tr><tr><td>No</td><td>404 (72.8)</td><td>250 (72.7)</td><td>154 (73.0)</td><td></td><td></td></tr><tr><td>Drug use<sup>4</sup></td><td>580</td><td>347</td><td>233</td><td>0.0003</td><td></td></tr><tr><td>Yes</td><td>224 (38.6)</td><td>155 (44.7)</td><td>69 (29.6)</td><td></td><td></td></tr><tr><td>No</td><td>356 (61.4)</td><td>192 (55.3)</td><td>164 (70.4)</td><td></td><td></td></tr><tr><td>Cannabis use</td><td>516</td><td>305</td><td>211</td><td>0.0002</td><td></td></tr><tr><td>No use</td><td>314 (60.9)</td><td>163 (53.4)</td><td>151 (71.6)</td><td></td><td>1</td></tr><tr><td>Non- regular use</td><td>95 (18.4)</td><td>68 (22.3)</td><td>27 (12.8)</td><td></td><td>0.41 [0.22; 0.77]</td></tr><tr><td>Regular or daily use</td><td>107 (20.7)</td><td>74 (24.3)</td><td>33 (15.6)</td><td></td><td>0.50 [0.28; 0.91]</td></tr><tr><td>Cocaine use</td><td>580</td><td>347</td><td>233</td><td>0.7647</td><td></td></tr><tr><td>Yes</td><td>37 (6.4)</td><td>23 (6.6)</td><td>14 (6.0)</td><td></td><td></td></tr><tr><td>No</td><td>543 (93.6)</td><td>324 (93.4)</td><td>219 (94.0)</td><td></td><td></td></tr><tr><td>Crack use</td><td>580</td><td>347</td><td>233</td><td>0.6875</td><td></td></tr><tr><td>Yes</td><td>4 (0.7)</td><td>2 (0.6)</td><td>2 (0.9)</td><td></td><td></td></tr><tr><td>No</td><td>576 (99.3)</td><td>345 (99.4)</td><td>231 (99.1)</td><td></td><td></td></tr></tbody></table>

(Continued)
<table><caption>**Table 1.** (Continued)</caption><thead><tr><th rowspan="2">Patients' characteristics</th><th rowspan="2">N (%)</th><th colspan="3">Univariate analysis</th><th>Multivariable analysis</th></tr><tr><th>PEG-IFN treatment N (%)</th><th>DAA treatment N (%)</th><th>p-value</th><th>aOR [95% CI]</th></tr></thead><tbody><tr><td><strong>Heroin/subutex use</strong></td><td><strong>580</strong></td><td><strong>347</strong></td><td><strong>233</strong></td><td>0.1554</td><td></td></tr><tr><td>Yes</td><td>17 (2.9)</td><td>13 (3.8)</td><td>4 (1.7)</td><td></td><td></td></tr><tr><td>No</td><td>563 (97.1)</td><td>334 (96.3)</td><td>229 (98.3)</td><td></td><td></td></tr><tr><td><strong>Ecstasy use</strong></td><td><strong>596</strong></td><td><strong>347</strong></td><td><strong>233</strong></td><td>0.1091</td><td></td></tr><tr><td>Yes</td><td>19 (3.3)</td><td>8 (2.3)</td><td>11 (4.7)</td><td></td><td></td></tr><tr><td>No</td><td>561 (96.7)</td><td>339 (97.7)</td><td>222 (95.3)</td><td></td><td></td></tr><tr><td><strong>Amphetamines use</strong></td><td><strong>580</strong></td><td><strong>347</strong></td><td><strong>233</strong></td><td><strong>0.0302</strong></td><td></td></tr><tr><td>Yes</td><td>6 (1.0)</td><td>1 (0.3)</td><td>5 (2.2)</td><td></td><td></td></tr><tr><td>No</td><td>574 (99.0)</td><td>346 (99.7)</td><td>228 (97.8)</td><td></td><td></td></tr><tr><td><strong>LSD use</strong></td><td><strong>580</strong></td><td><strong>347</strong></td><td><strong>233</strong></td><td>0.5345</td><td></td></tr><tr><td>Yes</td><td>4 (0.7)</td><td>3 (0.9)</td><td>1 (0.4)</td><td></td><td></td></tr><tr><td>No</td><td>576 (99.3)</td><td>344 (99.1)</td><td>232 (99.6)</td><td></td><td></td></tr><tr><td><strong>Significant liver fibrosis<sup>5</sup></strong></td><td><strong>502</strong></td><td><strong>343</strong></td><td><strong>159</strong></td><td>0.0293</td><td></td></tr><tr><td>Yes</td><td>329 (65.5)</td><td>214 (62.4)</td><td>115 (72.3)</td><td></td><td></td></tr><tr><td>No</td><td>173 (34.5)</td><td>129 (37.6)</td><td>44 (27.7)</td><td></td><td></td></tr><tr><td><strong>Severe liver fibrosis or cirrhosis<sup>5</sup></strong></td><td><strong>502</strong></td><td><strong>343</strong></td><td><strong>159</strong></td><td>0.049</td><td></td></tr><tr><td>Yes</td><td>112 (22.3)</td><td>68 (19.8)</td><td>44 (27.7)</td><td></td><td></td></tr><tr><td>No</td><td>390 (77.7)</td><td>275 (80.2)</td><td>115 (72.3)</td><td></td><td></td></tr><tr><td><strong>Drug injection history</strong></td><td><strong>559</strong></td><td><strong>331</strong></td><td><strong>228</strong></td><td>&lt;0.0001</td><td></td></tr><tr><td>Yes</td><td>317 (56.7)</td><td>228 (68.9)</td><td>89 (39.0)</td><td></td><td><strong>0.19 [0.12; 0.31]</strong></td></tr><tr><td>No</td><td>242 (43.3)</td><td>103 (31.1)</td><td>139 (61.0)</td><td></td><td><strong>1</strong></td></tr></tbody></table>

In our study sample, for each 1-year increase in age, patients were 17% more likely (aOR = 1.17 95% CI [1.13; 1.22]) to receive DAA treatment. In contrast, patients with unstable housing were less likely to receive DAA treatment (0.46 [0.24; 0.88]) than PEG-IFN based regimens. With respect to cannabis consumption (reference group: non-users), patients who used cannabis regularly or daily were 50% less likely to receive DAA treatment than PEG-IFN based regimens (0.50 [0.28; 0.91]), while non-regular users were 59% less likely (0.41 [0.22; 0.77]) to receive DAA treatment. Similarly, patients with a history of injecting drug use were 81% less likely to receive DAA treatment (0.19 [0.12; 0.31]) than to receive PEG-IFN based regimens (Table 1).

## Sensitivity analysis

In order to eliminate any possible selection bias arising from the fact that some centers followed a greater number of HIV-HCV co-infected patients who used drugs, we performed a sensitivity analysis which excluded clinical centers not involved in all 3 phases of the cohort. Accordingly, only 27 clinical centers were included in the sensitivity analysis which led to 26 patients (4.4%) being excluded. The results of the sensitivity analysis confirmed those of the main multivariable analysis (data not shown).

<footnote n="1">¹ Unstable housing was defined as not being owner or tenant of one's housing.</footnote>

<footnote n="2">² Hazardous alcohol consumption was defined as having an AUDIT-C score ≥ 4 for men or ≥ 3 for women</footnote>

<footnote n="3">³ Binge drinking was defined as consuming six or more alcoholic drinks on any one occasion during the previous month.</footnote>

<footnote n="4">⁴ Drug use was defined as the use of at least one of the following psychoactive substances during the previous four weeks: cannabis, cocaine, crack, heroin, ecstasy, amphetamines, LSD.</footnote>

<footnote n="5">⁵ Significant liver fibrosis was defined as a FIB-4 score >1.45, and severe fibrosis or cirrhosis as a FIB-4 score >3.25.</footnote>
Discussion

Our analysis of data from the ANRS CO13 HEPAVIH cohort is the first to compare character-
istics of patients treated with first-generation HCV regimens with that of patients treated with
DAA. Interestingly, patients with unstable housing and a history of drug injection (factors
which both characterize vulnerable groups) and patients with regular cannabis use were all less
likely to receive DAA treatment than PEG-IFN-based regimens. Moreover, the sensitivity
analysis, which removed the possible recruitment effect, confirmed these results.

Given that there is no medical argument to delay providing a patient with DAA, as these
treatments extremely effective and safe, universal access to DAA should help to better control
the HCV epidemic [25]. In 2016, French policy makers stated universal access to HCV therapy,
given that all patients with chronic hepatitis C at any stage of liver fibrosis, and from all vulner-
able groups (i.e., HIV-HCV co-infected patients, people who use drugs, etc.), have the right to
access HCV treatment and care according to the recommendations by the French High
Authority in Health (HAS) (cf: http://www.has-sante.fr/portail/upload/docs/application/pdf/
2016-05/aad_avis_25052016_ct_25052016.pdf).

Our primary focus was to understand whether there were any differences between
HIV-HCV co-infected patients treated with DAA and those treated with PEG-IFN based regi-
mens in terms of socio-behavioral characteristics.

The association we found between less access to DAA and unstable housing is consistent
with prior studies [15] which reported that unstable housing is a barrier to initiation of chronic
hepatitis C treatment, as it could compromise adherence to treatment. People with unstable
housing are also more likely to have poorer financial and psychosocial statuses. Therefore,
they are not only at a high risk of HCV infection [26], but are also exposed to discrimination,
social isolation and sometimes rejection. Given this, the fear of rejection might affect patient-
provider relationships, and this may not regularly seek medical care and often miss follow-up
visits in HIV medical centers. Patients with unstable housing are known to be less likely to
have a long-term commitment to continued medical care for HIV and other comorbidities,
including HCV infection [27]. There is also the risk that some health workers mistrust of
patients may contribute to delayed access to care, including HCV treatment with DAA. In
addition to factors related to the price of DAA, to caregivers and to the healthcare system itself
[28,29], in our study, it is possible that the majority of HIV-HCV co-infected patients with
unstable housing conditions were treated and cured in the era of PEG-IFN. That could be the
result of policy efforts to treating vulnerable populations.

PWID constitute a key group where the prevalence of chronic hepatitis C is high, due to
shared injection equipment [30]. In French and international (cf http://www.eacsociety.org/
files/guidelines_8_0-english_web.pdf) guidelines, HCV treatment with DAA is strongly rec-
ommended for HIV-HCV co-infected patients and drug users, irrespective of disease stage, as
it constitutes an important tool for prevention of HCV transmission. Previous studies on HCV
mono-infected and HIV-HCV co-infected PWID showed high rates of sustained virological
response (SVR) to HCV treatment in these populations, and also showed that PWID did not
exhibit lower rates of adherence to treatment than other patients [31-33]. Another issue with
PWID is the risk of reinfection after SVR to HCV treatment. Despite the relatively low rate of
reinfection among co-infected patients, estimated at 1%-5%, in one study [34], this rate can
still have an impact at the population level and compromise the global eradication of HCV
[35]. Although one study highlighted that HIV-HCV co-infected PWID in France are not less
likely to be treated with PEG-IFN based regimens [18], another French study [17] found the
opposite. Our results showed that this population is less represented among DAA-treated
patients, which could suggest they have less access to this new treatment [36]. In a Canadian
HIV-HCV co-infected cohort, Saeed et al. [37], found great disparities in DAA initiation, and highlighted that marginalized populations, including PWID, were less likely to initiate HCV treatment in the DAA era.

Some physicians may tend to delay HCV treatment in active users of psychoactive substances, including cannabis, because of concerns about poor adherence to treatment and the high risk of re-infection after treatment [38,39]. However, research has shown that patients using cannabis often do so to relieve a range of troublesome side effects of PEG-IFN-treatment [40]. In addition, regular cannabis use is frequent in former injecting drug users and more particularly in former opioid-dependent individuals, as it relieves opioid withdrawal symptoms and HIV-HCV-related symptoms [41,42]. In the present study, we also found that the proportion of cannabis users was lower in individuals receiving DAA, suggesting either that cannabis users had already been treated with PEG-IFN based treatment or that cannabis users have reduced access to DAA. Cannabis use is an additional proxy of history of drug use or unstable lifestyles. Most drug users in our study were treated with PEG-IFN or with DAA. Yet, to be effective, the management of these patients has to go beyond simply providing medical treatment. Substance abuse requires integrated, multidisciplinary care. Promoting stable housing through a "housing first" approach also seems to be crucial [43,44]. The results of this study also showed that older patients were more likely to receive DAA treatment than PEG-IFN-based regimens. This population included individuals who did not respond to PEG-IFN, and others whose advanced stage of liver disease (advanced fibrosis or cirrhosis, hepatocellular carcinoma) was a criterion to schedule treatment. This was highlighted by the difference in liver fibrosis found when comparing the two groups in univariate analysis. According to the natural history of chronic hepatitis C in patients infected with HIV, the occurrence of severe complications, including liver fibrosis or cirrhosis, is strongly associated with patient age [42] and this could influence HCV treatment SVR rates [45,46].

The results from our cohort study need to be further explored in a qualitative manner, from the perspective of both patients and caregivers [19], in order to better identify their beliefs and perceptions and to acquire a greater understanding of the reasons for delayed DAA initiation in some groups. The sensitivity analysis confirmed results from the main multivariable analysis. Current guidelines for access to HCV treatment in France stipulate that HIV-HCV co-infected patients and all vulnerable populations, including PWID, should be treated. However, our results suggest that this is not yet a reality. Indeed, since DAA are more effective and less toxic than PEG-IFN-based treatments, they should be accessible to more PWID, especially those who are most socially vulnerable, as this population is the reservoir of the HCV epidemic, facilitating HCV transmission in their network through risky practices [34].

Overall, the high prices which pharmaceutical firms ask for DAA may influence health policy decisions, and force clinicians to delay treatment initiation until liver fibrosis is already quite advanced. That could explain the fact that vulnerable and marginalized populations were less represented in patients receiving DAA. Such decisions are unacceptable now that chronic hepatitis C is a curable disease and that DAA have been proven to be cost-effective [47]. Before the advent of DAA, access to treatment for chronic hepatitis C was very selective in France, with priority being given to patients at an advanced stage of the disease and those with complications including liver fibrosis and hepatocellular carcinoma. It was the consensus that everyone has the right to benefit from HCV medical care [48] which led to the French government adopting a policy of universal HCV care in May 2016.

Overall, the results of this study highlighted a change over time in the profile of HIV-HCV co-infected patients treated for HCV infection in France. This evolution reflects improvements in the treatment of hepatitis C in France, as patients from the most vulnerable populations can now access treatment and therefore be cured.
Our study has limitations. First, we compared access to HCV treatment between patients treated at two different calendar periods, and consequently there may have been changes in the epidemiological characteristics of patients recruited. However, to tackle this potential bias, we performed a sensitivity analysis which confirmed the results found. Second, behaviors were based on self-reports which can be affected by social desirability bias. Nevertheless, even if some under-reporting were present, it is unlikely that this would vary over time and affect the comparison between access to treatment in the PEG-IFN and DAA period. Finally, given that is an observational cohort, it may be not appropriate to extrapolate these findings to all HIV-HCV co-infected patients in France.

## Conclusion

In this study, people with unstable housing conditions, those with a history of drug injection and cannabis users were all less represented among patients who initiated DAA treatment than among those who initiated PEG-IFN-based regimens. It is possible that a majority of these patients had previously been treated for HCV in the PEG-IFN era. This reflects a change in the epidemiological profile of HIV-HCV co-infected patients receiving HCV treatment in France. As HCV treatment is prevention, improving access to DAA, in particular to individuals with high-risk behaviors, remains a major clinical and public health strategy.

## Acknowledgments

We thank all the members of the ANRS CO13-HEPAVIH Study Group**. We especially thank all physicians and nurses involved in the follow-up of the cohort and all patients who took part in this study. Finally, out thanks to Jude Sweeney for the English revision and editing of our manuscript.

**The ANRS CO13-HEPAVIH Study Group

Scientific Committee: D. Salmon (co-Principal investigator), L. Wittkop (co-Principal Investigator), P. Sogni (co-Principal Investigator), L. Esterle (project manager), P. Trimoulet, J. Izopet, L. Serfaty, V. Paradis, B. Spire, P. Carrieri, M.A. Valantin, G. Pialoux, J. Chas, I. Poizot-Martin, K. Barange, A. Naqvi, E. Rosenthal, A. Bicart-See, O. Bouchaud, A. Gervais, C. Lascoux-Combe, C. Goujard, K. Lacombe, C. Duvivier, D. Vittecoq, D. Neau, P. Morlat, F. Bani-Sadr, L. Meyer, F. Boufassa, S. Dominguez, B. Autran, A.M. Roque, C. Solas, H. Fontaine, D. Costagliola, L. Piroth, A. Simon, D. Zucman, F. Boué, P. Miailhes, E. Billaud, H. Aumaître, D. Rey, G. Peytavin, V. Petrov-Sanchez, A. Pailhé.

Clinical Centres (ward / participating physicians): APHP Cochin, Paris (Médecine Interne et Maladies Infectieuses: D. Salmon, R. Usubillaga; Hépato-gastro-entérologie: P. Sogni; Anatomo-pathologie: B. Terris; Virologie: P. Tremeaux); APHP Pitié-Salpétrière, Paris (Maladies Infectieuses et Tropicales: C. Katlama, M.A. Valantin, H. Stitou; Hépato-gastro-entérologie: Y. Benhamou; Anatomo-pathologie: F. Charlotte; Virologie: S. Fourati); APHP Pitié-Salpétrière, Paris (Médecine Interne: A. Simon, P. Cacoub, S. Nafissa); APHM Sainte-Marguerite, Marseille (Service d'Immuno-Hématologie Clinique: I. Poizot-Martin, O. Zaegel, H. Laroche; Virologie: C. Tamalet); APHP Tenon, Paris (Maladies Infectieuses et Tropicales: G. Pialoux, J. Chas,; Anatomo-pathologie: P. Callard, F. Bendjaballah; Virologie: C. Le Pendeven); CHU Purpan, Toulouse (Maladies Infectieuses et Tropicales: B. Marchou; Hépato-gastro-entérologie: L. Alric, K. Barange, S. Metivier; Anatomo-pathologie: J. Selves; Virologie: F. Larroquette); CHU Archet, Nice (Médecine Interne: E. Rosenthal; Infectiologie: A. Naqvi, V. Rio; Anatomo-pathologie: J. Haudebourg, M.C. Saint-Paul; Virologie: C. Partouche); APHP Avicenne, Bobigny (Médecine Interne-Unité VIH: O. Bouchaud; Anatomo-pathologie: M. Ziol; Virologie: Y. Baazia); Hôpital Joseph Ducuing, Toulouse (Médecine Interne: M. Uzan, A. Bicart-See,
D. Garipuy, M.J. Ferro-Collados; Anatomo-pathologie: J. Selves; Virologie: F. Nicot); APHP Bichat-Claude-Bernard, Paris (Maladies Infectieuses: A. Gervais, Y. Yazdanpanah; Anatomo-pathologie: H. Adle-Biassette; Virologie: G. Alexandre); APHP Saint-Louis, Paris (Maladies infectieuses: C. Lascoux-Combe, J.M. Molina; Anatomo-pathologie: P. Bertheau; Virologie: M.L. Chaix, C. Delaugerre, S. Maylin); APHP Saint-Antoine (Maladies Infectieuses et Tropicales: K. Lacombe, J. Bottero; J. Krause P.M. Girard, Anatomo-pathologie: D. Wendum, P. Cervera, J. Adam; Virologie: C. Viala); APHP Bicêtre, Paris (Médecine Interne: C. Goujard, Y. Quertainmont, E. Teicher; Virologie: C. Pallier; Maladies Infectieuses: D. Vittecoq); APHP Necker, Paris (Maladies Infectieuses et Tropicales: O. Lortholary, C. Duvivier, C. Rouzaud, J. Lourenco, F. Touam, C. Louisin; Virologie: V. Avettand-Fenoel, A. Mélard); CHU Pellegrin, Bordeaux (Maladies Infectieuses et Tropicales: D. Neau, A. Ochoa, E. Blanchard, S. Castet-Lafarie, C. Cazanave, D. Malvy, M. Dupon, H. Dutronc, F. Dauchy, L. Lacaze-Buzy; Anatomo-pathologie: P. Bioulac-Sage; Virologie: P. Trimoulet, S. Reigadas); Hôpital Saint-André, Bordeaux (Médecine Interne et Maladies Infectieuses: Médecine Interne et Maladies Infectieuses: P. Morlat, D. Lacoste, F. Bonnet, N. Bernard, M. Hessamfar, J. F. Paccalin, C. Martell, M. C. Pertusa, M. Vandenhende, P. Merciéer, D. Malvy, T. Pistone, M.C. Receveur, M. Méchain, P. Duffau, C Rivoisy, I. Faure, S. Caldato; Anatomo-pathologie: P. Bioulac-Sage; Virologie: P. Trimoulet, S. Reigadas); Hôpital du Haut-Levêque, Bordeaux (Médecine Interne: J.L. Pellegrin, J. F. Viallard, E. Lazzaro, C. Greib; Anatomo-pathologie: P. Bioulac-Sage; Virologie: P. Trimoulet, S. Reigadas); Hôpital FOCH, Suresnes (Médecine Interne: D. Zucman, C. Majerholc; Virologie: E. Farfour); APHP Antoine Béclère, Clamart (Médecine Interne: F. Boué, J. Polo Devoto, I. Kansau, V. Chambrin, C. Pignon, L. Berroukeche, R. Fior, V. Martinez; Virologie: C. Deback); CHU Henri Mondor, Créteil (Immunologie Clinique: Y. Lévy, S. Dominguez, J.D. Lelièvre, A.S. Lascaux, G. Melica); CHU Hôtel Dieu, Nantes (Maladies Infectieuses et Tropicales: E. Billaud, F. Raffi, C. Allavena, V. Reliquet, D. Boutoille, C. Biron; Virologie: A. Rodallec, L. Le Guen); Hôpital de la Croix Rousse, Lyon (Maladies Infectieuses et Tropicales: P. Miailhes, D. Peyramond, C. Chidiac, F. Ader, F. Biron, A. Boibieux, L. Cotte, T. Ferry, T. Perpoint, J. Koffi, F. Zoulim, F. Bailly, P. Lack, M. Maynard, S. Radenne, M. Amiri; Virologie: C. Scholtes, T.T. Le-Thi); CHU Dijon, Dijon (Département d'infectiologie: L. Piroth, P. Chavanet, M. Duong Van Huyen, M. Buisson, A. Waldner-Combernoux, S. Mahy, R. Binois, A.L. Simonet-Lann, D. Croisier-Bertin); CH Perpignan, Perpignan (Maladies infectieuses et tropicales: H. Aumaître); CHU Robert Debré, Reims (Médecine interne, maladies infectieuses et immunologie clinique: F. Bani-Sadr, D. Lambert, Y Nguyen, J.L. Berger); CHRU Strasbourg (Le Trait d'Union: D Rey, M Partisani, ML Batard, C Cheneau, M Priester, C Bernard-Henry, E de Mautort, Virologie: P Gantner et S Fafi-Kremer), APHP Bichat-Claude Bernard (Pharmacologie: G. Peytavin)

Data collection: F. Roustant, I. Kmiec, L. Traore, S. Lepuil, S. Parlier, V. Sicart-Payssan, E. Bedel, F. Touam, C. Louisin, M. Mole, C. Bolliot, M. Mebarki, A. Adda-Lievin, F.Z. Makhoukhi, O. Braik, R. Bayoud, M.P. Pietri, V. Le Baut, D. Bornarel, C. Chesnel, D. Beniken, M. Pachard, S. Akel, S. Caldato, C. Lions, L. Chalal, Z. Julia, H. Hue, A. Soria, M. Cavellec, S. Breau, A. Joulie, P. Fisher, C. Ondo Eyene, S. Ogoudjobi, C. Brochier, V. Thoirain-Galvan.

Management, statistical analyses: E. Boerg, P. Carrieri, V. Conte, L. Dequae-Merchadou, M. Desvallees, N. Douiri, L. Esterle, C. Gilbert, S. Gillet, R. Knight, F. Marcellin, L. Michel, M. Mora, C. Protopopescu, P. Roux, B. Spire, S. Tezkratt, I. Yaya, T. Barré, T. Rojas, V. Villes, M. Baudoin, M. Santos.

Author Contributions

**Conceptualization:** Issifou Yaya, Maria Patrizia Carrieri.
**Data curation:** Issifou Yaya, Boni Armand Elegbe.

**Formal analysis:** Issifou Yaya.

**Methodology:** Issifou Yaya.

**Software:** Issifou Yaya, Boni Armand Elegbe.

**Supervision:** Maria Patrizia Carrieri.

**Writing – original draft:** Issifou Yaya.

**Writing – review & editing:** Issifou Yaya, Perrine Roux, Fabienne Marcellin, Linda Wittkop, Laure Esterle, Bruno Spire, Stéphanie Dominguez, Lionel Piroth, Philippe Sogni, Dominique Salmon-Ceron, Maria Patrizia Carrieri.

## References

1. WHO | Hepatitis C [Internet]. WHO. [cited 2018 Jun 21]. Available from: http://www.who.int/news-room/fact-sheets/detail/hepatitis-c

2. Zeuzem S, Berg T, Moeller B, Hinrichsen H, Mauss S, Wedemeyer H, et al. Expert opinion on the treatment of patients with chronic hepatitis C. J Viral Hepat. 2009; 16:75–90. https://doi.org/10.1111/j.1365-2893.2008.01012.x PMID: 18761607

3. Ward RP, Kugelmas M. Using pegylated interferon and ribavirin to treat patients with chronic hepatitis C. Am Fam Physician. 2005; 72:655–62. PMID: 16127955

4. Lee SS, Bain VG, Peltekian K, Krajden M, Yoshida EM, Deschenes M, et al. Treating chronic hepatitis C with pegylated interferon alfa-2a (40 KD) and ribavirin in clinical practice. Aliment Pharmacol Ther. 2006; 23:397–408. https://doi.org/10.1111/j.1365-2036.2006.02748.x PMID: 16422999

5. Pawlotsky J-M. Hepatitis C treatment: the data flood goes on-an update from the liver meeting 2014. Gastroenterology. 2015; 148:468–79. https://doi.org/10.1053/j.gastro.2015.01.002 PMID: 25576860

6. Sulkowski MS, Gardiner DF, Rodriguez-Torres M, Reddy KR, Hassanein T, Jacobson I, et al. Daclatasvir plus sofosbuvir for previously treated or untreated chronic HCV infection. N Engl J Med. 2014; 370:211–21. https://doi.org/10.1056/NEJMoa1306218 PMID: 24428467

7. Sogni P, Gilbert C, Lacombe K, Piroth L, Rosenthal E, Miailhes P, et al. All-oral Direct-acting Antiviral Regimens in HIV/Hepatitis C Virus–coinfected Patients With Cirrhosis Are Efficient and Safe: Real-life Results From the Prospective ANRS CO13–HEPAVIH Cohort. Clin Infect Dis. 2016; 63:763–70. https://doi.org/10.1093/cid/ciw379 PMID: 27317796

8. Piroth L, Wittkop L, Lacombe K, Rosenthal E, Gilbert C, Miailhes P, et al. Efficacy and safety of direct-acting antiviral regimens in HIV/HCV-co-infected patients–French ANRS CO13 HEPAVIH cohort. J Hepatol [Internet]. Available from: http://www.sciencedirect.com/science/article/pii/S0168827817301071

9. Cachay ER, Hill L, Wyles D, Colwell B, Ballard C, Torriani F, et al. The Hepatitis C Cascade of Care among HIV Infected Patients: A Call to Address Ongoing Barriers to Care. PLoS ONE [Internet]. 2014 [cited 2017 May 16];9. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103859/

10. Craxì L, Sacchini D, Refolo P, Minacori R, Daloiso V, Ricci G, et al. Prioritization of high-cost new drugs for HCV: making sustainability ethical. Eur Rev Med Pharmacol Sci. 2016; 20:1044–51. PMID: 27049255

11. Agence France Presse (AFP). Hépatite C: des traitements très efficaces mais qui profitent à très peu [Internet]. ladepeche.fr. 2016 [cited 2017 Jun 15]. Available from: http://www.ladepeche.fr/article/2016/01/12/2254185-hepatite-traitements-tres-efficaces-profitent-tres-peu.html

12. Clark BT, Garcia-Tsao G, Fraenkel L. Patterns and predictors of treatment initiation and completion in patients with chronic hepatitis C virus infection. Patient Prefer Adherence. 2012; 6:285–95. https://doi.org/10.2147/PPA.S30111 PMID: 22536063

13. Discours de Marisol Touraine—Journée de lutte contre les hépatites virales [Internet]. Ministère Solidar. Santé. 2016 [cited 2016 Jun 15]. Available from: http://solidarites-sante.gouv.fr/archives/archives-presse/archives-discours/article/discours-de-marisol-touraine-journée-de-lutte-contre-les-hepatites-virales

14. Dhumeaux D. Prise en charge thérapeutique et suivi de l'ensemble des personnes infectées par le virus de l'hépatite C. RAPPORT DE RECOMMANDATIONS 2016 [Internet]. Paris: ANRS—AFEF; 2016 p. 108. Available from: http://solidarites-sante.gouv.fr/IMG/pdf/rapport_.pdf
15. Saeed S, Strumpf EC, Walmsley SL, Rollet-Kurhajec K, Pick N, Martel-Laferrière V, et al. How Generalizable Are the Results From Trials of Direct Antiviral Agents to People Coinfected With HIV/HCV in the Real World? Clin Infect Dis Off Publ Infect Dis Soc Am. 2016; 62:919–26.

16. Zeremski M, Zibbell JE, Martinez AD, Kritz S, Smith BD, Talal AH. Hepatitis C virus control among persons who inject drugs requires overcoming barriers to care. World J Gastroenterol WJG. 2013; 19:7846–51. https://doi.org/10.3748/wjg.v19.i44.7846 PMID: 24307778

17. Roux P, Demoulin B, Sogni P, Carrieri MP, Dray-Spria R, Spire B, et al. La co-infection par le virus de l'hépatite C chez les personnes infectées par le VIH: données de l'enquête ANRS-Vespa2. Bull Épidémiologique Hebd. 2013;314–20.

18. Salmon-Ceron D, Cohen J, Winnock M, Roux P, Sadr FB, Rosenthal E, et al. Engaging HIV-HCV co-infected patients in HCV treatment: the roles played by the prescribing physician and patients' beliefs (ANRS CO13 HEPAVIH cohort, France). BMC Health Serv Res. 2012; 12:59. https://doi.org/10.1186/1472-6963-12-59 PMID: 22409788

19. Wiessing L, Ferri M, Grady B, Kantzanou M, Sperle I, Cullen KJ, et al. Hepatitis C Virus Infection Epidemiology among People Who Inject Drugs in Europe: A Systematic Review of Data for Scaling Up Treatment and Prevention. PLOS ONE. 2014; 9:e103345. https://doi.org/10.1371/journal.pone.0103345 PMID: 25068274

20. Taylor LE, Swan T, Mayer KH. HIV coinfection with hepatitis C virus: evolving epidemiology and treatment paradigms. Clin Infect Dis Off Publ Infect Dis Soc Am. 2012; 55 Suppl 1:S33–42.

21. Loko M-A, Salmon D, Carrieri P, Winnock M, Mora M, Merchadou L, et al. The French national prospective cohort of patients co-infected with HIV and HCV (ANRS CO13 HEPAVIH): Early findings, 2006–2010. BMC Infect Dis. 2010; 10:303. https://doi.org/10.1186/1471-2334-10-303 PMID: 20969743

22. Bradley KA, DeBenedetti AF, Volk RJ, Williams EC, Frank D, Kivlahan DR. AUDIT-C as a brief screen for alcohol misuse in primary care. Alcohol Clin Exp Res. 2007; 31:1208–17. https://doi.org/10.1111/j.1530-0277.2007.00403.x PMID: 17451397

23. Sterling RK, Lissen E, Clumeck N, Sola R, Correa MC, Montaner J, et al. Development of a simple non-invasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology. 2006; 43:1317–25. https://doi.org/10.1002/hep.21178 PMID: 16729309

24. Focà E, Fabbiani M, Prosperi M, Quiros Roldan E, Castelli F, Maggiolo F, et al. Liver fibrosis progression and clinical outcomes are intertwined: role of CD4+ T-cell count and NRTI exposure from a large cohort of HIV/HCV-coinfected patients with detectable HCV-RNA. Medicine (Baltimore) [Internet]. 2016; 95. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5265753/

25. Vickerman P, Martin N, Turner K, Hickman M. Can needle and syringe programmes and opiate substitution therapy achieve substantial reductions in hepatitis C virus prevalence? Model projections for different epidemic settings. Addict Abingdon Engl. 2012; 107:1984–95.

26. Aidala AA, Wilson MG, Shubert V, Gogolishvili D, Globerman J, Rueda S, et al. Housing Status, Medical Care, and Health Outcomes Among People Living With HIV/AIDS: A Systematic Review. Am J Public Health. 2016; 106:e1–23.

27. Kim C, Kerr T, Li K, Zhang R, Tyndall MW, Montaner JS, et al. Unstable housing and hepatitis C incidence among injection drug users in a Canadian setting. BMC Public Health. 2009; 9:270. https://doi.org/10.1186/1471-2458-9-270 PMID: 19640297

28. Afdhal NH, Zeuzem S, Schooley RT, Thomas DL, Ward JW, Litwin AH, et al. The new paradigm of hepatitis C therapy: integration of oral therapies into best practices. J Viral Hepat. 2013; 20:745–60. https://doi.org/10.1111/jvh.12173 PMID: 24168254

29. Lynch SM, Wu GY. Hepatitis C Virus: A Review of Treatment Guidelines, Cost-effectiveness, and Access to Therapy. J Clin Transl Hepatol. 2016; 4:310–9. https://doi.org/10.14218/JCTH.2016.00027 PMID: 28097100

30. Alter MJ. Epidemiology of hepatitis C virus infection. World J Gastroenterol WJG. 2007; 13:2436–41. https://doi.org/10.3748/wjg.v13.i17.2436 PMID: 17552026

31. Hellard M, Sacks-Davis R, Gold J. Hepatitis C treatment for injection drug users: a review of the available evidence. Clin Infect Dis Off Publ Infect Dis Soc Am. 2009; 49:561–73.

32. Mravčík V, Strada L, Štolfa J, Bencko V, Groshkova T, Reimer J, et al. Factors associated with uptake, adherence, and efficacy of hepatitis C treatment in people who inject drugs: a literature review. Patient Prefer Adherence. 2013; 7:1067–75. https://doi.org/10.2147/PPA.S49113 PMID: 24204126

33. Bruggmann P, Grebely J. Prevention, treatment and care of hepatitis C virus infection among people who inject drugs. Int J Drug Policy. 2015; 26 Suppl 1:S22–26.

34. Grebely J, Oser M, Taylor LE, Dore GJ. Breaking Down the Barriers to Hepatitis C Virus (HCV) Treatment Among Individuals With HCV/HIV Coinfection: Action Required at the System, Provider, and Patient Levels. J Infect Dis. 2013; 207:S19–25. https://doi.org/10.1093/infdis/jis928 PMID: 23390301
35. Martin NK, Vickerman P, Grebely J, Hellard M, Hutchinson SJ, Lima VD, et al. Hepatitis C virus treatment for prevention among people who inject drugs: Modeling treatment scale-up in the age of direct-acting antivirals. Hepatol Baltim Md. 2013; 58:1598-609.

36. Taylor LE, Swan T, Matthews GV. Management of Hepatitis C Virus/HIV Coinfection Among People Who Use Drugs in the Era of Direct-Acting Antiviral-Based Therapy. Clin Infect Dis Off Publ Infect Dis Soc Am. 2013; 57:S118-24.

37. Saeed S, Strumpf EC, Moodie EE, Young J, Nitulescu R, Cox J, et al. Disparities in direct acting antivirals uptake in HIV-hepatitis C co-infected populations in Canada. J Int AIDS Soc [Internet]. 2017 [cited 2018 Feb 21];20. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5810331/

38. Robaeys G, Van Vlierberghe H, Matheï C, Van Ranst M, Bruckers L, Buntinx F, et al. Similar compliance and effect of treatment in chronic hepatitis C resulting from intravenous drug use in comparison with other infection causes. Eur J Gastroenterol Hepatol. 2006; 18:159-66. PMID: 16394797

39. Sylvestre D. Hepatitis C treatment in drug users: perception versus evidence. Eur J Gastroenterol Hepatol. 2006; 18:129-30. PMID: 16394792

40. Hopwood M, Treloar C. The drugs that dare not speak their name: Injecting and other illicit drug use during treatment for hepatitis C infection. Int J Drug Policy. 2007; 18:374-80. https://doi.org/10.1016/j.drugpo.2006.12.018 PMID: 17854725

41. Bouhnik A-D, Carrieri MP, Rey D, Spire B, Gastaut J-A, Gallais H, et al. Drug injection cessation among HIV-infected injecting drug users. Addict Behav. 2004; 29:1189-97. https://doi.org/10.1016/j.addbeh.2004.01.006 PMID: 15236822

42. Scavone JL, Sterling RC, Van Bockstaele EJ. Cannabinoid and opioid interactions: implications for opiate dependence and withdrawal. Neuroscience. 2013; 248:637-54. https://doi.org/10.1016/j.neuroscience.2013.04.034 PMID: 23624062

43. O'Campo P, Stergiopoulos V, Nir P, Levy M, Misir V, Chum A, et al. How did a Housing First intervention improve health and social outcomes among homeless adults with mental illness in Toronto? Two-year outcomes from a randomised trial. BMJ Open [Internet]. 2016 [cited 2017 May 16];6. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5030577/

44. Cherner RA, Aubry T, Sylvestre J, Boyd R, Pettey D. Housing First for Adults with Problematic Substance Use. J Dual Diagn. 2017;0.

45. Sadler MD, Lee SS. Revolution in hepatitis C antiviral therapy. Br Med Bull. 2015; 113:31-44. https://doi.org/10.1093/bmb/ldv004 PMID: 25680808

46. Benítez-Gutiérrez L, Barreiro P, Labarga P, de Mendoza C, Fernandez-Montero JV, Arias A, et al. Prevention and management of treatment failure to new oral hepatitis C drugs. Expert Opin Pharmacother. 2016; 17:1215-23. https://doi.org/10.1080/14656566.2016.1182156 PMID: 27149603

47. Wong WWL, Lee KM, Singh S, Wells G, Feld JJ, Krahn M. Drug therapies for chronic hepatitis C infection: a cost-effectiveness analysis. CMAJ Open. 2017; 5:E97-108. https://doi.org/10.9778/cmajo.20160161 PMID: 28401125

48. Craxì L, Cammà C, Craxì A. HCV: the best cure possible or the best possible cure? J Viral Hepat. 2015; 22:627-9. https://doi.org/10.1111/jvh.12411 PMID: 26135025