# Hepatitis C virus cure from direct-acting antivirals and mortality: Are people with and without a history of injection drug use in the same boat? (ANRS CO22 Hepather cohort)

Tangui Barré, Marc Bourlière, Lucia Parlati, Clémence Ramier, Fabienne Marcellin, Camelia Protopopescu, Vincent Di Beo, Carole Cagnot, Celine Dorival, Jérôme Nicol, et al.

► To cite this version:

Tangui Barré, Marc Bourlière, Lucia Parlati, Clémence Ramier, Fabienne Marcellin, et al. Hepatitis C virus cure from direct-acting antivirals and mortality: Are people with and without a history of injection drug use in the same boat? (ANRS CO22 Hepather cohort). Drug and Alcohol Review, 2023, 43 (3), pp.718 - 731. 10.1111/dar.13802. inserm-04539690

HAL Id: inserm-04539690

https://inserm.hal.science/inserm-04539690

Submitted on 9 Apr 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Hepatitis C virus cure from direct-acting antivirals and mortality: Are people with and without a history of injection drug use in the same boat? (ANRS CO22 Hepather cohort)

Tangui Barré, Marc Bourlière, Lucia Parlati, Clémence Ramier, Fabienne Marcellin, Camelia Protopopescu, Vincent Di Beo, Carole Cagnot, Celine Dorival, Jérôme Nicol, et al.

► To cite this version:

Tangui Barré, Marc Bourlière, Lucia Parlati, Clémence Ramier, Fabienne Marcellin, et al. Hepatitis C virus cure from direct-acting antivirals and mortality: Are people with and without a history of injection drug use in the same boat? (ANRS CO22 Hepather cohort). Drug and Alcohol Review, 2023, 43 (3), pp.718 - 731. 10.1111/dar.13802. inserm-04539690

HAL Id: inserm-04539690

https://inserm.hal.science/inserm-04539690v1

Submitted on 9 Apr 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

# Hepatitis C virus cure from direct-acting antivirals and mortality: Are people with and without a history of injection drug use in the same boat? (ANRS CO22 Hepather cohort)

Tangui Barré<fnref n="1" /> ID

Marc Bourlière<fnref n="1" />,<fnref n="2" />

Lucia Parlati<fnref n="3" />

Clémence Ramier<fnref n="1" />

Fabienne Marcellin<fnref n="1" />

Camelia Protopopescu<fnref n="1" /> ID

Vincent Di Beo<fnref n="1" />

Carole Cagnot<fnref n="4" />

Celine Dorival<fnref n="5" />

Jérôme Nicol<fnref n="5" />

Fabien Zoulim<fnref n="6" />,<fnref n="7" />,<fnref n="8" />

Fabrice Carrat<fnref n="9" />

Patrizia Carrieri<fnref n="1" />

the ANRS/AFEF Hepather Study group

### Correspondence

Camelia Protopopescu, Aix Marseille
Univ, INSERM, IRD, Sciences
Economiques & Sociales de la Santé &
Traitement de l'Information Médicale,
ISSPAM, Marseille, France.
Email: camelia.protopopescu@inserm.fr

### Funding information

AbbVie; ANRS | Emerging infectious
diseases; Bristol-Myers Squibb; Gilead
Sciences; Janssen-Cilag; Merck Sharp and
Dohme United Kingdom; Roche; the
French ANR (Agence Nationale de la

### Abstract

**Introduction:** The risk of mortality in people with a history of injection drug use (PHID) is high, as is the prevalence of hepatitis C virus (HCV) infection. Although direct-acting antivirals (DAA) are effective in this population in terms of sustained virological response, it is not known whether PHID benefit as much as people with no history of injection drug use from DAA-related HCV cure in terms of reduced all-cause mortality.

**Methods:** Using Cox proportional hazards models based on the ANRS CO22 Hepather cohort data (n = 9735), we identified factors associated with all-cause

<footnote n="1">¹Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Recherche pour le Developpement, Sciences Economiques & Sociales de la Santé & Traitement de l'Information Médicale, Institut des Sciences de la Santé Publique d'Aix-Marseille, Marseille, France</footnote>

<footnote n="2">²Département d'hépatologie et gastroentérologie, Hôpital Saint Joseph, Marseille, France</footnote>

<footnote n="3">³Université de Paris Cité; Institut National de la Santé et de la Recherche Médicale; Assistance Publique-Hôpitaux de Paris, Département d'Hépatologie/Addictologie, Hôpital Cochin, Paris, France</footnote>

<footnote n="4">⁴ANRS | Emerging Infectious Diseases, Department of Clinical Research, Paris, France</footnote>

<footnote n="5">⁵Institut National de la Santé et de la Recherche Médicale, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Sorbonne Université, Paris, France</footnote>

<footnote n="6">⁶Institut National de la Santé et de la Recherche Médicale U1052, Centre National de la Recherche Scientifique, Unités Mixtes de Recherche-5286, Cancer Research Center of Lyon, Lyon, France</footnote>

<footnote n="7">⁷University of Lyon, Université Claude-Bernard, Lyon, France</footnote>

<footnote n="8">⁸Hospices Civils de Lyon, Lyon, France</footnote>

<footnote n="9">⁹Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Hôpital Saint-Antoine, Unité de Santé Publique, Assistance Publique-Hôpitaux de Paris, Paris, France</footnote>
# Hepatitis C virus cure from direct-acting antivirals and mortality: Are people with and without a history of injection drug use in the same boat? (ANRS CO22 Hepather cohort)

Tangui Barré<fnref n="1" />

<figure><img src="image_2.png" /></figure>

Marc Bourlière<fnref n="1" />,<fnref n="2" />

Lucia Parlati<fnref n="3" />

Clémence Ramier<fnref n="1" />

Fabienne Marcellin<fnref n="1" />

Camelia Protopopescu<fnref n="1" />

<figure><img src="image_3.png" /></figure>

Vincent Di Beo<fnref n="1" />

Carole Cagnot<fnref n="4" />

Celine Dorival<fnref n="5" />

Jérôme Nicol<fnref n="5" />

Fabien Zoulim<fnref n="6" />,<fnref n="7" />,<fnref n="8" />

Fabrice Carrat<fnref n="9" />

Patrizia Carrieri<fnref n="1" />

the ANRS/AFEF Hepather Study group

### Correspondence

Camelia Protopopescu, Aix Marseille
Univ, INSERM, IRD, Sciences
Economiques & Sociales de la Santé &
Traitement de l'Information Médicale,
ISSPAM, Marseille, France.
Email: camelia.protopopescu@inserm.fr

### Funding information

AbbVie; ANRS | Emerging infectious
diseases; Bristol-Myers Squibb; Gilead
Sciences; Janssen-Cilag; Merck Sharp and
Dohme United Kingdom; Roche; the
French ANR (Agence Nationale de la

### Abstract

**Introduction:** The risk of mortality in people with a history of injection drug use (PHID) is high, as is the prevalence of hepatitis C virus (HCV) infection. Although direct-acting antivirals (DAA) are effective in this population in terms of sustained virological response, it is not known whether PHID benefit as much as people with no history of injection drug use from DAA-related HCV cure in terms of reduced all-cause mortality.

**Methods:** Using Cox proportional hazards models based on the ANRS CO22 Hepather cohort data (n = 9735), we identified factors associated with all-cause

<footnote n="1">¹Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Recherche pour le Developpement, Sciences Economiques & Sociales de la Santé & Traitement de l'Information Médicale, Institut des Sciences de la Santé Publique d'Aix-Marseille, Marseille, France</footnote>

<footnote n="2">²Département d'hépatologie et gastroentérologie, Hôpital Saint Joseph, Marseille, France</footnote>

<footnote n="3">³Université de Paris Cité; Institut National de la Santé et de la Recherche Médicale; Assistance Publique-Hôpitaux de Paris, Département d'Hépatologie/Addictologie, Hôpital Cochin, Paris, France</footnote>

<footnote n="4">⁴ANRS | Emerging Infectious Diseases, Department of Clinical Research, Paris, France</footnote>

<footnote n="5">⁵Institut National de la Santé et de la Recherche Médicale, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Sorbonne Université, Paris, France</footnote>

<footnote n="6">⁶Institut National de la Santé et de la Recherche Médicale U1052, Centre National de la Recherche Scientifique, Unités Mixtes de Recherche-5286, Cancer Research Center of Lyon, Lyon, France</footnote>

<footnote n="7">⁷University of Lyon, Université Claude-Bernard, Lyon, France</footnote>

<footnote n="8">⁸Hospices Civils de Lyon, Lyon, France</footnote>

<footnote n="9">⁹Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Hôpital Saint-Antoine, Unité de Santé Publique, Assistance Publique-Hôpitaux de Paris, Paris, France</footnote>
Recherche), Grant/Award Number:
France 2030 #ANR-19-COHO-0002; the
French DGS (Direction Générale de la
Santé)

mortality among HCV-infected people. We tested for interaction effects between
drug injection status, HCV cure and other explanatory variables.

**Results:** DAA-related HCV cure was associated with a 66% (adjusted hazard ratio [95% confidence interval]: 0.34 [0.29–0.39]) lower risk of all-cause mortality, irrespective of drug injection status. Detrimental effects of unhealthy alcohol use on mortality were identified in PHID only.

**Discussion and Conclusions.** DAA-related HCV cure led to comparable benefits in terms of reduced mortality in PHID and people with no history of injection drug use. Policies and strategies to enhance DAA uptake among PHID are needed to lower mortality in this population.

Clinical trial registration details: [ClinicalTrials.gov](http://ClinicalTrials.gov): NCT01953458.

### KEYWORDS

direct-acting antivirals, drug injection, France, hepatitis C virus, mortality

### Key Points

* The risk of mortality in people with a history of injection drug use (PHID) is high.

* Hepatitis C virus prevalence is high in PHID.

* Drug injection status had no effect on hepatitis C virus cure effect on mortality.

* Detrimental effects of alcohol use on mortality were identified in PHID only.

## 1 | INTRODUCTION

Compared with the general population, people with a history of injection drug use (PHID) have a higher risk of death, although mortality rates vary according to context [1, 2]. For instance, in their meta-analysis, Larney et al. estimated the all-cause standardised mortality ratio of people using extramedical opioids at 10 [2]. The prevalence of the hepatitis C virus (HCV) infection, one factor for higher death risk, may be as high as 60% among PHID [3, 4]. Moreover, drug-related deaths represent a large proportion of mortality in active PHID in industrialised countries [5-7]. Opioid substitution therapy can reduce mortality rates in this population [6, 8] by lowering the risks of HCV transmission and opioid overdose [9].

Although direct-acting antivirals (DAA) for HCV treatment have been associated with a sharp decrease in both liver disease prevalence and all-cause mortality in PHID [10, 11], no data exist comparing the impact of DAA-related HCV cure on mortality between PHID and people with no history of injection drug use. Testing the existence of such a putative difference may help orient and assess future public health strategies regarding DAA scale-up.

We tested the hypothesis that DAA-related HCV cure has a similar impact on all-cause mortality in both populations using data from the French ANRS C022 Hepather cohort.

## 2 | METHODS

### 2.1 | Participants

The ANRS CO22 Hepather is a French national, multicentre, prospective, observational cohort of adult patients infected with hepatitis B virus and/or HCV (NCT01953458). HCV-positive patients were defined as patients with positive HCV-RNA or positive anti-HCV antibodies, according to data retrieved from medical records. Patients with HIV coinfection and those who were currently receiving treatment (or had completed treatment within the last 3 months) were not included in the cohort (exclusion criteria). Implemented in 2012, enrolment in the cohort study took place in 32 hospital centres throughout France with a 10-year follow-up. Participants were recruited consecutively during a medical visit at their centre. The cohort design is described extensively elsewhere [12].

Patients included in the cohort received DAA treatment after enrolment, if eligible.

First- and second-generation DAA have been implemented throughout France since 2011 and 2014, respectively. Access was initially restricted (i.e., based on liver disease severity) until 2017 [13], when universal access was granted.

Written informed consent was obtained from each cohort participant before enrolment. The protocol was designed in accordance with the Declaration of Helsinki and the French law for biomedical research. It was approved by the Comité de Protection des Personnes Ile
Recherche), Grant/Award Number:
France 2030 #ANR-19-COHO-0002; the
French DGS (Direction Générale de la
Santé)

mortality among HCV-infected people. We tested for interaction effects between
drug injection status, HCV cure and other explanatory variables.

**Results:** DAA-related HCV cure was associated with a 66% (adjusted hazard ratio [95% confidence interval]: 0.34 [0.29–0.39]) lower risk of all-cause mortality, irrespective of drug injection status. Detrimental effects of unhealthy alcohol use on mortality were identified in PHID only.

**Discussion and Conclusions.** DAA-related HCV cure led to comparable benefits in terms of reduced mortality in PHID and people with no history of injection drug use. Policies and strategies to enhance DAA uptake among PHID are needed to lower mortality in this population.

Clinical trial registration details: [ClinicalTrials.gov](http://ClinicalTrials.gov): NCT01953458.

### KEYWORDS

direct-acting antivirals, drug injection, France, hepatitis C virus, mortality

### Key Points

* The risk of mortality in people with a history of injection drug use (PHID) is high.

* Hepatitis C virus prevalence is high in PHID.

* Drug injection status had no effect on hepatitis C virus cure effect on mortality.

* Detrimental effects of alcohol use on mortality were identified in PHID only.

## 1 | INTRODUCTION

Compared with the general population, people with a history of injection drug use (PHID) have a higher risk of death, although mortality rates vary according to context [1, 2]. For instance, in their meta-analysis, Larney et al. estimated the all-cause standardised mortality ratio of people using extramedical opioids at 10 [2]. The prevalence of the hepatitis C virus (HCV) infection, one factor for higher death risk, may be as high as 60% among PHID [3, 4]. Moreover, drug-related deaths represent a large proportion of mortality in active PHID in industrialised countries [5-7]. Opioid substitution therapy can reduce mortality rates in this population [6, 8] by lowering the risks of HCV transmission and opioid overdose [9].

Although direct-acting antivirals (DAA) for HCV treatment have been associated with a sharp decrease in both liver disease prevalence and all-cause mortality in PHID [10, 11], no data exist comparing the impact of DAA-related HCV cure on mortality between PHID and people with no history of injection drug use. Testing the existence of such a putative difference may help orient and assess future public health strategies regarding DAA scale-up.

We tested the hypothesis that DAA-related HCV cure has a similar impact on all-cause mortality in both populations using data from the French ANRS C022 Hepather cohort.

## 2 | METHODS

### 2.1 | Participants

The ANRS CO22 Hepather is a French national, multicentre, prospective, observational cohort of adult patients infected with hepatitis B virus and/or HCV (NCT01953458). HCV-positive patients were defined as patients with positive HCV-RNA or positive anti-HCV antibodies, according to data retrieved from medical records. Patients with HIV coinfection and those who were currently receiving treatment (or had completed treatment within the last 3 months) were not included in the cohort (exclusion criteria). Implemented in 2012, enrolment in the cohort study took place in 32 hospital centres throughout France with a 10-year follow-up. Participants were recruited consecutively during a medical visit at their centre. The cohort design is described extensively elsewhere [12].

Patients included in the cohort received DAA treatment after enrolment, if eligible.

First- and second-generation DAA have been implemented throughout France since 2011 and 2014, respectively. Access was initially restricted (i.e., based on liver disease severity) until 2017 [13], when universal access was granted.

Written informed consent was obtained from each cohort participant before enrolment. The protocol was designed in accordance with the Declaration of Helsinki and the French law for biomedical research. It was approved by the Comité de Protection des Personnes Ile
de France 3 Ethics Committee (Paris, France) and the French Regulatory Authority.

## 2.2 | Study population

The present study population comprised patients with chronic HCV infection at enrolment in Hepather. We excluded patients with hepatitis B virus co-infection, persons whose drug injection status was unavailable, and individuals whose only available visit was the enrolment visit.

## 2.3 | Data collection

At cohort enrolment, physicians led a face-to-face interview and completed a structured questionnaire according to participating patients' answers. Anthropological measurements, urine and blood samples were also taken.

The questionnaire collected clinical, socio-demographic and behavioural data including sex, age, country of birth, average monthly household income, the number of adults and children in the household, HCV transmission mode, lifetime tobacco use, and past and current alcohol consumption (number of standard drinks per day). Data on past and current drug injection as well as past and current opioid substitution therapy were also collected.

Detailed clinical (including body height, weight and comorbidities) and biological data were gathered during the enrolment visit using an electronic case-report form. Clinical data were updated annually during follow-up visits and in spontaneous reports for particular events (e.g., decompensated cirrhosis, DAA treatment initiation). HCV treatments were retrieved from medical records. Vital status was ascertained through medical records at clinical centres. No linkage with mortality registry was done.

## 2.4 | Study outcome and study period

The study outcome was the time between enrolment and all-cause death. The study period started at the enrolment visit and ended at the latest news date (i.e., the most recent available follow-up visit or death). Participants were censored at 9 years of follow-up.

## 2.5 | Explanatory variables

The main explanatory variable was drug injection status (i.e., PHID vs. people with no history of injection drug use), measured at the enrolment visit. Participants who self-reported past and/or active drug injection, past

and/or current opioid substitution therapy, or infection with HCV through injection drug use were defined as PHID. Active drug injection was defined as self-reporting 'current' injection drug use. Those statuses were not externally or objectively further validated. Participants who reported none of these elements were defined as people with no history of injection drug use.

Other explanatory variables tested were: sex, age, place of birth, living in poverty, alcohol use, tobacco use (the number of pack-years), body mass index (categorised according to World Health Organization cut-offs [14]), diabetes, advanced liver fibrosis (FIB-4 score >3.25 [15]), hypertension and HCV cure. HCV cure was defined as an undetectable viral load at 24 weeks after the end of HCV treatment. Living in poverty was defined as a standard of living lower than the 2015 French poverty threshold (1015 euros per month) [16]. Unhealthy alcohol use was defined as >2 and >3 standard drinks per day for women and men, respectively, in accordance with the French National Authority for Health [17]. All variables were measured at enrolment, except for HCV cure, which was time-varying.

## 2.6 | Statistical analyses

The characteristics of the two sub-populations (PHID and people with no history of injection drug use) were compared using Pearson's chi-squared test or Student *t* test.

Mortality rates were computed, separately in PHID and people with no history of injection drug use, as the number of deaths occurring during the study period divided by the total number of person-years of follow-up. Mortality rates were compared between the two sub-populations using Fisher's exact test for incidence rates differences. Standardised mortality ratios (SMR) were then computed for each sub-population as the ratio between the mortality rate and the age- and sex-specific mortality rate in the general population (2019 data [18]).

Cox proportional hazards models were then used to identify factors associated with all-cause mortality. We tested for interaction between drug injection status and HCV cure (according to our hypothesis), as well as interactions between drug injection status and sex, age and alcohol use. As women who inject drugs face specific challenges [19], their benefits of HCV cure may differ from those observed for their men counterparts. We may expect age to interact with drug injection status, as younger PHID may engage in more risky behaviours [20]. Lastly, alcohol-related risks are more common and exacerbated in PHID [21].

Variables with a *p*-value <0.20 (Wald test) in the univariable analyses were eligible for the multivariable analysis. Interaction terms were tested using bivariate analyses with the same *p*-value criterion. A backward selection
de France 3 Ethics Committee (Paris, France) and the French Regulatory Authority.

## 2.2 | Study population

The present study population comprised patients with chronic HCV infection at enrolment in Hepather. We excluded patients with hepatitis B virus co-infection, persons whose drug injection status was unavailable, and individuals whose only available visit was the enrolment visit.

## 2.3 | Data collection

At cohort enrolment, physicians led a face-to-face interview and completed a structured questionnaire according to participating patients' answers. Anthropological measurements, urine and blood samples were also taken.

The questionnaire collected clinical, socio-demographic and behavioural data including sex, age, country of birth, average monthly household income, the number of adults and children in the household, HCV transmission mode, lifetime tobacco use, and past and current alcohol consumption (number of standard drinks per day). Data on past and current drug injection as well as past and current opioid substitution therapy were also collected.

Detailed clinical (including body height, weight and comorbidities) and biological data were gathered during the enrolment visit using an electronic case-report form. Clinical data were updated annually during follow-up visits and in spontaneous reports for particular events (e.g., decompensated cirrhosis, DAA treatment initiation). HCV treatments were retrieved from medical records. Vital status was ascertained through medical records at clinical centres. No linkage with mortality registry was done.

## 2.4 | Study outcome and study period

The study outcome was the time between enrolment and all-cause death. The study period started at the enrolment visit and ended at the latest news date (i.e., the most recent available follow-up visit or death). Participants were censored at 9 years of follow-up.

## 2.5 | Explanatory variables

The main explanatory variable was drug injection status (i.e., PHID vs. people with no history of injection drug use), measured at the enrolment visit. Participants who self-reported past and/or active drug injection, past

and/or current opioid substitution therapy, or infection with HCV through injection drug use were defined as PHID. Active drug injection was defined as self-reporting 'current' injection drug use. Those statuses were not externally or objectively further validated. Participants who reported none of these elements were defined as people with no history of injection drug use.

Other explanatory variables tested were: sex, age, place of birth, living in poverty, alcohol use, tobacco use (the number of pack-years), body mass index (categorised according to World Health Organization cut-offs [14]), diabetes, advanced liver fibrosis (FIB-4 score >3.25 [15]), hypertension and HCV cure. HCV cure was defined as an undetectable viral load at 24 weeks after the end of HCV treatment. Living in poverty was defined as a standard of living lower than the 2015 French poverty threshold (1015 euros per month) [16]. Unhealthy alcohol use was defined as >2 and >3 standard drinks per day for women and men, respectively, in accordance with the French National Authority for Health [17]. All variables were measured at enrolment, except for HCV cure, which was time-varying.

## 2.6 | Statistical analyses

The characteristics of the two sub-populations (PHID and people with no history of injection drug use) were compared using Pearson's chi-squared test or Student *t* test.

Mortality rates were computed, separately in PHID and people with no history of injection drug use, as the number of deaths occurring during the study period divided by the total number of person-years of follow-up. Mortality rates were compared between the two sub-populations using Fisher's exact test for incidence rates differences. Standardised mortality ratios (SMR) were then computed for each sub-population as the ratio between the mortality rate and the age- and sex-specific mortality rate in the general population (2019 data [18]).

Cox proportional hazards models were then used to identify factors associated with all-cause mortality. We tested for interaction between drug injection status and HCV cure (according to our hypothesis), as well as interactions between drug injection status and sex, age and alcohol use. As women who inject drugs face specific challenges [19], their benefits of HCV cure may differ from those observed for their men counterparts. We may expect age to interact with drug injection status, as younger PHID may engage in more risky behaviours [20]. Lastly, alcohol-related risks are more common and exacerbated in PHID [21].

Variables with a *p*-value <0.20 (Wald test) in the univariable analyses were eligible for the multivariable analysis. Interaction terms were tested using bivariate analyses with the same *p*-value criterion. A backward selection
<figure><img src="image_3.png" /><figcaption>**FIGURE 1** Flow-chart of the study population (ANRS CO22 Hepather cohort). HCV, hepatitis C virus.</figcaption></figure>

procedure was used to build the final multivariable model, based on a *p*-value <0.05 for statistical significance. Proportional-hazard assumption was graphically verified using log-log survivor plots adjusted for the other variables in the final model, using the *stphplot* Stata command.

All analyses were performed with Stata version 17.0 for Windows (StataCorp LP, College Station, TX, USA).

# 3 | RESULTS

## 3.1 | Study population characteristics and mortality rates

The study population comprised 9735 cohort participants (Figure 1), of whom 53.9% were male (Table 1) and 29.0% were PHID (including 82 active injectors, or 0.8% of the whole study population). Median (interquartile range) age at enrolment was 56 (49–64) years. It was 51 (47–56) in PHID and 59 (51–68) in people with no history of injection drug use (*p* < 0.001). Median (interquartile range) follow-up time was 6.10 (4.16–7.31) years, corresponding to 54,672.83 person-years. During the study period, of the 1121 deaths which occurred, 279 (24.9%) were among PHID (including seven active injectors) (Table 2).

At the last available visit, 1375 (14.1%) participants were not HCV cured. Among them, 52.1% did not receive any treatment. Among the 659 participants already treated but not cured, 321 received second generation DAA, 44 received first generation DAA, and 294 received interferon-based treatments without DAA. There was no difference between PHID and people with no history of injection drug use in terms of having received first,

second generation DAA or other treatments (*p* = 0.063, data not shown).

The crude mortality rate (95% confidence interval) was significantly higher in people with no history of injection drug use than in PHID (2.16 [2.02–2.31] and 1.79 [1.59–2.01] per 100 person-years, respectively, *p* = 0.006). The SMR was lower in people with no history of injection drug use than in PHID (1.81 [1.69–1.94] and 3.30 [2.94–3.71], respectively). The same was true when considering only post-cure period (Table 2).

## 3.2 | Factors associated with all-cause mortality in people with and without a history of injection drug use

Table 3 provides the factors associated with all-cause mortality in the study population. After multivariable adjustment, HCV cure was associated with a 66% (adjusted hazard ratio [95% confidence interval] 0.34 [0.29–0.39], *p* < 0.001) lower risk of mortality. Drug injection status was not significantly associated with mortality risk (0.71 [0.40–1.27], *p* = 0.250), after accounting for its interaction effects. Interactions terms with drug injection status were statistically significant for both age and alcohol use, but not for HCV cure. The adjusted hazard ratio of being ≥60 years was 1.94 [1.36–2.78] (*p* < 0.001) in people with no history of injection drug use. It was not statistically significant in PHID (0.80 [0.52–1.25], *p* = 0.334). In people with no history of injection drug use, moderate alcohol use was associated with a lower risk of mortality. Past or current unhealthy use was not associated with mortality (Table 2). In PHID, moderate
<figure><img src="image_4.png" /><figcaption>**FIGURE 1** Flow-chart of the study population (ANRS CO22 Hepather cohort). HCV, hepatitis C virus.</figcaption></figure>

procedure was used to build the final multivariable model, based on a *p*-value <0.05 for statistical significance. Proportional-hazard assumption was graphically verified using log-log survivor plots adjusted for the other variables in the final model, using the *stphplot* Stata command.

All analyses were performed with Stata version 17.0 for Windows (StataCorp LP, College Station, TX, USA).

## 3 | RESULTS

### 3.1 | Study population characteristics and mortality rates

The study population comprised 9735 cohort participants (Figure 1), of whom 53.9% were male (Table 1) and 29.0% were PHID (including 82 active injectors, or 0.8% of the whole study population). Median (interquartile range) age at enrolment was 56 (49–64) years. It was 51 (47–56) in PHID and 59 (51–68) in people with no history of injection drug use (*p* < 0.001). Median (interquartile range) follow-up time was 6.10 (4.16–7.31) years, corresponding to 54,672.83 person-years. During the study period, of the 1121 deaths which occurred, 279 (24.9%) were among PHID (including seven active injectors) (Table 2).

At the last available visit, 1375 (14.1%) participants were not HCV cured. Among them, 52.1% did not receive any treatment. Among the 659 participants already treated but not cured, 321 received second generation DAA, 44 received first generation DAA, and 294 received interferon-based treatments without DAA. There was no difference between PHID and people with no history of injection drug use in terms of having received first,

second generation DAA or other treatments (*p* = 0.063, data not shown).

The crude mortality rate (95% confidence interval) was significantly higher in people with no history of injection drug use than in PHID (2.16 [2.02–2.31] and 1.79 [1.59–2.01] per 100 person-years, respectively, *p* = 0.006). The SMR was lower in people with no history of injection drug use than in PHID (1.81 [1.69–1.94] and 3.30 [2.94–3.71], respectively). The same was true when considering only post-cure period (Table 2).

### 3.2 | Factors associated with all-cause mortality in people with and without a history of injection drug use

Table 3 provides the factors associated with all-cause mortality in the study population. After multivariable adjustment, HCV cure was associated with a 66% (adjusted hazard ratio [95% confidence interval] 0.34 [0.29–0.39], *p* < 0.001) lower risk of mortality. Drug injection status was not significantly associated with mortality risk (0.71 [0.40–1.27], *p* = 0.250), after accounting for its interaction effects. Interactions terms with drug injection status were statistically significant for both age and alcohol use, but not for HCV cure. The adjusted hazard ratio of being ≥60 years was 1.94 [1.36–2.78] (*p* < 0.001) in people with no history of injection drug use. It was not statistically significant in PHID (0.80 [0.52–1.25], *p* = 0.334). In people with no history of injection drug use, moderate alcohol use was associated with a lower risk of mortality. Past or current unhealthy use was not associated with mortality (Table 2). In PHID, moderate
<table><caption>TABLE 1 Study sample characteristics according to drug injection status (ANRS CO22 Hepather cohort, N = 9735).</caption><thead><tr><th>Characteristics<sup>a</sup> (% of missing values)</th><th>Study population (N = 9735) N (%) or median [IQR]</th><th>People with no history of injection drug use (N = 6913) N (%) or median [IQR]</th><th>PHID (N = 2822) N (%) or median [IQR]</th><th>p-value<sup>b</sup></th><th>Person-years</th></tr></thead><tbody><tr><td>Sex (0)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Male</td><td>5250 (53.9)</td><td>3150 (45.6)</td><td>2100 (74.4)</td><td>&lt;0.001</td><td>28,871.2</td></tr><tr><td>Female</td><td>4485 (46.1)</td><td>3763 (54.4)</td><td>722 (25.6)</td><td></td><td>25,801.6</td></tr><tr><td>Age (0), years</td><td>56 [49–64]</td><td>59 [51–68]</td><td>51 [47–56]</td><td>&lt;0.001</td><td></td></tr><tr><td>Age (0), years</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt;50</td><td>2450 (25.2)</td><td>1395 (20.2)</td><td>1055 (37.4)</td><td>&lt;0.001</td><td>8639.9</td></tr><tr><td>50–59</td><td>3645 (37.4)</td><td>2141 (31.0)</td><td>1504 (53.3)</td><td></td><td>18,882.0</td></tr><tr><td>≥60</td><td>3640 (37.4)</td><td>3377 (48.8)</td><td>263 (9.3)</td><td></td><td>27,150.9</td></tr><tr><td>Place of birth<sup>c</sup> (0.2)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>France</td><td>7158 (73.6)</td><td>4742 (68.7)</td><td>2416 (85.6)</td><td>&lt;0.001</td><td>40,197.1</td></tr><tr><td>Europe (outside France)/Latin and North America/Australia</td><td>744 (7.7)</td><td>570 (8.3)</td><td>174 (6.2)</td><td></td><td>3986.7</td></tr><tr><td>North Africa and Middle East</td><td>928 (9.5)</td><td>778 (11.3)</td><td>150 (5.3)</td><td></td><td>5062.2</td></tr><tr><td>Sub-Saharan Africa/Caribbean</td><td>622 (6.4)</td><td>590 (8.6)</td><td>32 (1.1)</td><td></td><td>3561.2</td></tr><tr><td>Asia</td><td>267 (2.7)</td><td>218 (3.2)</td><td>49 (1.7)</td><td></td><td>1388.2</td></tr><tr><td>Living in poverty<sup>d</sup> (3.4)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>6521 (69.3)</td><td>4794 (71.8)</td><td>1727 (63.2)</td><td>&lt;0.001</td><td>37,200.8</td></tr><tr><td>Yes</td><td>2884 (30.7)</td><td>1880 (28.2)</td><td>1004 (36.8)</td><td></td><td>15,682.0</td></tr><tr><td>Alcohol use<sup>e</sup> (0.5)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Abstinent without past unhealthy use</td><td>4148 (42.8)</td><td>3561 (51.7)</td><td>587 (21.0)</td><td>&lt;0.001</td><td>23,621.3</td></tr><tr><td>Moderate use</td><td>3792 (39.1)</td><td>2607 (37.8)</td><td>1185 (42.4)</td><td></td><td>21,546.1</td></tr><tr><td>Past or current unhealthy use</td><td>1746 (18.0)</td><td>724 (10.5)</td><td>1022 (36.6)</td><td></td><td>9237.9</td></tr><tr><td>Tobacco use<sup>f</sup> (pack-years) (5.3)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>0</td><td>3685 (40.0)</td><td>3539 (53.5)</td><td>146 (5.6)</td><td>&lt;0.001</td><td>21,246.8</td></tr><tr><td>1–10</td><td>1554 (16.9)</td><td>1074 (16.2)</td><td>480 (18.4)</td><td></td><td>8766.8</td></tr><tr><td>11–20</td><td>1534 (16.6)</td><td>794 (12.0)</td><td>740 (28.4)</td><td></td><td>8700.2</td></tr><tr><td>&gt;20</td><td>2448 (26.5)</td><td>1209 (18.3)</td><td>1239 (47.6)</td><td></td><td>13,179.7</td></tr><tr><td>Body mass index<sup>g</sup> (0.8)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Normal</td><td>4907 (50.8)</td><td>3315 (48.4)</td><td>1592 (56.8)</td><td>&lt;0.001</td><td>27,544.8</td></tr><tr><td>Underweight</td><td>319 (3.3)</td><td>180 (2.6)</td><td>139 (5.0)</td><td></td><td>1677.4</td></tr></tbody></table>
<table><caption>TABLE 1 Study sample characteristics according to drug injection status (ANRS CO22 Hepather cohort, N = 9735).</caption><thead><tr><th>Characteristics<sup>a</sup> (% of missing values)</th><th>Study population (N = 9735) N (%) or median [IQR]</th><th>People with no history of injection drug use (N = 6913) N (%) or median [IQR]</th><th>PHID (N = 2822) N (%) or median [IQR]</th><th>p-value<sup>b</sup></th><th>Person-years</th></tr></thead><tbody><tr><td>Sex (0)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Male</td><td>5250 (53.9)</td><td>3150 (45.6)</td><td>2100 (74.4)</td><td>&lt;0.001</td><td>28,871.2</td></tr><tr><td>Female</td><td>4485 (46.1)</td><td>3763 (54.4)</td><td>722 (25.6)</td><td></td><td>25,801.6</td></tr><tr><td>Age (0), years</td><td>56 [49–64]</td><td>59 [51–68]</td><td>51 [47–56]</td><td>&lt;0.001</td><td></td></tr><tr><td>Age (0), years</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt;50</td><td>2450 (25.2)</td><td>1395 (20.2)</td><td>1055 (37.4)</td><td>&lt;0.001</td><td>8639.9</td></tr><tr><td>50–59</td><td>3645 (37.4)</td><td>2141 (31.0)</td><td>1504 (53.3)</td><td></td><td>18,882.0</td></tr><tr><td>≥60</td><td>3640 (37.4)</td><td>3377 (48.8)</td><td>263 (9.3)</td><td></td><td>27,150.9</td></tr><tr><td>Place of birth<sup>c</sup> (0.2)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>France</td><td>7158 (73.6)</td><td>4742 (68.7)</td><td>2416 (85.6)</td><td>&lt;0.001</td><td>40,197.1</td></tr><tr><td>Europe (outside France)/Latin and North America/Australia</td><td>744 (7.7)</td><td>570 (8.3)</td><td>174 (6.2)</td><td></td><td>3986.7</td></tr><tr><td>North Africa and Middle East</td><td>928 (9.5)</td><td>778 (11.3)</td><td>150 (5.3)</td><td></td><td>5062.2</td></tr><tr><td>Sub-Saharan Africa/Caribbean</td><td>622 (6.4)</td><td>590 (8.6)</td><td>32 (1.1)</td><td></td><td>3561.2</td></tr><tr><td>Asia</td><td>267 (2.7)</td><td>218 (3.2)</td><td>49 (1.7)</td><td></td><td>1388.2</td></tr><tr><td>Living in poverty<sup>d</sup> (3.4)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>6521 (69.3)</td><td>4794 (71.8)</td><td>1727 (63.2)</td><td>&lt;0.001</td><td>37,200.8</td></tr><tr><td>Yes</td><td>2884 (30.7)</td><td>1880 (28.2)</td><td>1004 (36.8)</td><td></td><td>15,682.0</td></tr><tr><td>Alcohol use<sup>e</sup> (0.5)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Abstinent without past unhealthy use</td><td>4148 (42.8)</td><td>3561 (51.7)</td><td>587 (21.0)</td><td>&lt;0.001</td><td>23,621.3</td></tr><tr><td>Moderate use</td><td>3792 (39.1)</td><td>2607 (37.8)</td><td>1185 (42.4)</td><td></td><td>21,546.1</td></tr><tr><td>Past or current unhealthy use</td><td>1746 (18.0)</td><td>724 (10.5)</td><td>1022 (36.6)</td><td></td><td>9237.9</td></tr><tr><td>Tobacco use<sup>f</sup> (pack-years) (5.3)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>0</td><td>3685 (40.0)</td><td>3539 (53.5)</td><td>146 (5.6)</td><td>&lt;0.001</td><td>21,246.8</td></tr><tr><td>1–10</td><td>1554 (16.9)</td><td>1074 (16.2)</td><td>480 (18.4)</td><td></td><td>8766.8</td></tr><tr><td>11–20</td><td>1534 (16.6)</td><td>794 (12.0)</td><td>740 (28.4)</td><td></td><td>8700.2</td></tr><tr><td>&gt;20</td><td>2448 (26.5)</td><td>1209 (18.3)</td><td>1239 (47.6)</td><td></td><td>13,179.7</td></tr><tr><td>Body mass index<sup>g</sup> (0.8)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Normal</td><td>4907 (50.8)</td><td>3315 (48.4)</td><td>1592 (56.8)</td><td>&lt;0.001</td><td>27,544.8</td></tr><tr><td>Underweight</td><td>319 (3.3)</td><td>180 (2.6)</td><td>139 (5.0)</td><td></td><td>1677.4</td></tr></tbody></table>
<table><caption>TABLE 1 (Continued)</caption><thead><tr><th>Characteristics<sup>a</sup> (% of missing values)</th><th>Study population (N = 9735) N (%) or median [IQR]</th><th>People with no history of injection drug use (N = 6913) N (%) or median [IQR]</th><th>PHID (N = 2822) N (%) or median [IQR]</th><th>p-value<sup>b</sup></th><th>Person-years</th></tr></thead><tbody><tr><td>Overweight</td><td>3152 (32.6)</td><td>2340 (34.1)</td><td>812 (29.0)</td><td></td><td>17,897.9</td></tr><tr><td>Obesity</td><td>1276 (13.2)</td><td>1018 (14.9)</td><td>258 (9.2)</td><td></td><td>7141.7</td></tr><tr><td>Diabetes (0)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>8449 (86.8)</td><td>5859 (84.8)</td><td>2590 (91.8)</td><td>&lt;0.001</td><td>47,623.7</td></tr><tr><td>Yes</td><td>1285 (13.2)</td><td>1053 (15.2)</td><td>232 (8.2)</td><td></td><td>7047.3</td></tr><tr><td>Advanced liver fibrosis<sup>b</sup> (6.5)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>6732 (74.0)</td><td>4717 (72.9)</td><td>2015 (76.6)</td><td>&lt;0.001</td><td>38,349.9</td></tr><tr><td>Yes</td><td>2367 (26.0)</td><td>1750 (27.1)</td><td>617 (23.4)</td><td></td><td>12611.9</td></tr><tr><td>Hypertension (0.1)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>6874 (70.7)</td><td>4493 (65.0)</td><td>2381 (84.4)</td><td>&lt;0.001</td><td>38,840.2</td></tr><tr><td>Yes</td><td>2854 (29.3)</td><td>2414 (35.0)</td><td>440 (15.6)</td><td></td><td>15,807.3</td></tr><tr><td>HCV cure (0)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>1375 (14.1)</td><td>960 (13.9)</td><td>415 (14.7)</td><td>0.462</td><td>14,679.0</td></tr><tr><td>Yes by first generation DAA and/or interferon</td><td>81 (0.8)</td><td>55 (0.8)</td><td>26 (0.9)</td><td></td><td>1213.4</td></tr><tr><td>Yes by second generation DAA</td><td>8279 (85.1)</td><td>5898 (85.3)</td><td>2381 (84.4)</td><td></td><td>38,780.4</td></tr><tr><td>HCV cure (0)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>1375 (14.1)</td><td>960 (13.9)</td><td>415 (14.7)</td><td>0.292</td><td>14,679.0</td></tr><tr><td>Yes</td><td>8360 (85.9)</td><td>5953 (86.1)</td><td>2407 (85.3)</td><td></td><td>39,993.8</td></tr></tbody></table>

Abbreviations: DAA, direct-acting antivirals; HCV, hepatitis C virus; IQR, interquartile range; PHID, people with a history of injection drug use.

<sup>a</sup>Characteristics are given for cohort enrolment, except for HCV cure (time-varying variable), which was provided at the last available visit.

<sup>b</sup>Pearson's chi-squared test or Student t test.

<sup>c</sup>The category 'Europe and America' included participants from Europe (excluding France), South America (N = 32), North America (N = 20), Central America (N = 2) and Russia (N = 45). The category 'Sub-Saharan Africa' included participants from the Caribbean (N = 10).

<sup>d</sup>Living in poverty was defined as a standard of living lower than the 2015 French poverty threshold (1015 euros per month) [16].

<sup>e</sup>Unhealthy alcohol use was defined as >2 and >3 standard drinks per day for women and men, respectively, in accordance with the French National Authority for Health [17].

<sup>f</sup>The number of pack-years was obtained by multiplying the number of years the person had smoked by the average number of packs of cigarettes smoked per day.

<sup>g</sup>Body mass index was categorised according to World Health Organization cut-offs: overweight: ≥25 and <30 kg/m², obesity: ≥30 kg/m² [14].

<sup>h</sup>Advanced liver fibrosis was defined as an FIB-4 score >3.25 [15].
<table><caption>TABLE 1 (Continued)</caption><thead><tr><th>Characteristics<sup>a</sup> (% of missing values)</th><th>Study population (N = 9735) N (%) or median [IQR]</th><th>People with no history of injection drug use (N = 6913) N (%) or median [IQR]</th><th>PHID (N = 2822) N (%) or median [IQR]</th><th>p-value<sup>b</sup></th><th>Person-years</th></tr></thead><tbody><tr><td>Overweight</td><td>3152 (32.6)</td><td>2340 (34.1)</td><td>812 (29.0)</td><td></td><td>17,897.9</td></tr><tr><td>Obesity</td><td>1276 (13.2)</td><td>1018 (14.9)</td><td>258 (9.2)</td><td></td><td>7141.7</td></tr><tr><td>Diabetes (0)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>8449 (86.8)</td><td>5859 (84.8)</td><td>2590 (91.8)</td><td>&lt;0.001</td><td>47,623.7</td></tr><tr><td>Yes</td><td>1285 (13.2)</td><td>1053 (15.2)</td><td>232 (8.2)</td><td></td><td>7047.3</td></tr><tr><td>Advanced liver fibrosis<sup>b</sup> (6.5)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>6732 (74.0)</td><td>4717 (72.9)</td><td>2015 (76.6)</td><td>&lt;0.001</td><td>38,349.9</td></tr><tr><td>Yes</td><td>2367 (26.0)</td><td>1750 (27.1)</td><td>617 (23.4)</td><td></td><td>12611.9</td></tr><tr><td>Hypertension (0.1)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>6874 (70.7)</td><td>4493 (65.0)</td><td>2381 (84.4)</td><td>&lt;0.001</td><td>38,840.2</td></tr><tr><td>Yes</td><td>2854 (29.3)</td><td>2414 (35.0)</td><td>440 (15.6)</td><td></td><td>15,807.3</td></tr><tr><td>HCV cure (0)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>1375 (14.1)</td><td>960 (13.9)</td><td>415 (14.7)</td><td>0.462</td><td>14,679.0</td></tr><tr><td>Yes by first generation DAA and/or interferon</td><td>81 (0.8)</td><td>55 (0.8)</td><td>26 (0.9)</td><td></td><td>1213.4</td></tr><tr><td>Yes by second generation DAA</td><td>8279 (85.1)</td><td>5898 (85.3)</td><td>2381 (84.4)</td><td></td><td>38,780.4</td></tr><tr><td>HCV cure (0)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>1375 (14.1)</td><td>960 (13.9)</td><td>415 (14.7)</td><td>0.292</td><td>14,679.0</td></tr><tr><td>Yes</td><td>8360 (85.9)</td><td>5953 (86.1)</td><td>2407 (85.3)</td><td></td><td>39,993.8</td></tr></tbody></table>

Abbreviations: DAA, direct-acting antivirals; HCV, hepatitis C virus; IQR, interquartile range; PHID, people with a history of injection drug use.

<sup>a</sup>Characteristics are given for cohort enrolment, except for HCV cure (time-varying variable), which was provided at the last available visit.

<sup>b</sup>Pearson's chi-squared test or Student t test.

<sup>c</sup>The category 'Europe and America' included participants from Europe (excluding France), South America (N = 32), North America (N = 20), Central America (N = 2) and Russia (N = 45). The category 'Sub-Saharan Africa' included participants from the Caribbean (N = 10).

<sup>d</sup>Living in poverty was defined as a standard of living lower than the 2015 French poverty threshold (1015 euros per month) [16].

<sup>e</sup>Unhealthy alcohol use was defined as >2 and >3 standard drinks per day for women and men, respectively, in accordance with the French National Authority for Health [17].

<sup>f</sup>The number of pack-years was obtained by multiplying the number of years the person had smoked by the average number of packs of cigarettes smoked per day.

<sup>g</sup>Body mass index was categorised according to World Health Organization cut-offs: overweight: ≥25 and <30 kg/m², obesity: ≥30 kg/m² [14].

<sup>h</sup>Advanced liver fibrosis was defined as an FIB-4 score >3.25 [15].
<table><caption>TABLE 2 Mortality rates and standardised mortality ratios according to drug injection status (ANRS CO22 Hepather cohort).</caption><thead><tr><th>Characteristics<sup>a</sup></th><th>Deaths (N = 1121)<br>N (%)</th><th>People with no history of injection<br>drug use (N = 703)<br>Mortality rates per 100 person-years<br>[95% CI]</th><th>PHID (N = 242)<br>Mortality rates per 100 person-years<br>[95% CI]</th><th>p-value<sup>b</sup></th><th>People with no history of injection<br>drug use (N = 842)<br>Standardised mortality ratios [95% CI]</th><th>PHID (N = 279)<br>Standardised mortality<br>ratios [95% CI]</th></tr></thead><tbody><tr><td>Overall</td><td>2.16 [2.02-2.31]</td><td></td><td>1.79 [1.59-2.01]</td><td>0.006</td><td>1.81 [1.69-1.94]</td><td>3.30 [2.94-3.71]</td></tr><tr><td>Sex</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Male</td><td>717 (64.0)</td><td>2.73 [2.50-2.99]</td><td>2.11 [1.86-2.39]</td><td>0.001</td><td>2.01 [1.84-2.20]</td><td>3.40 [3.00-3.86]</td></tr><tr><td>Female</td><td>404 (36.0)</td><td>1.69 [1.53-1.88]</td><td>0.89 [0.65-1.24]</td><td>&lt;0.001</td><td>1.60 [1.45-1.78]</td><td>2.77 [2.01-3.83]</td></tr><tr><td>Age, years</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt;50</td><td>91 (8.1)</td><td>0.72 [0.53-0.99]</td><td>1.64 [1.25-2.16]</td><td>&lt;0.001</td><td>8.10 [5.94-11.04]</td><td>15.28 [11.62-20.11]</td></tr><tr><td>50-59</td><td>314 (28.0)</td><td>1.50 [1.28-1.75]</td><td>1.86 [1.59-2.17]</td><td>0.062</td><td>4.98 [4.24-5.83]</td><td>5.06 [4.34-5.90]</td></tr><tr><td>≥60</td><td>716 (63.9)</td><td>2.78 [2.58-3.01]</td><td>1.74 [1.37-2.21]</td><td>&lt;0.001</td><td>1.51 [1.40-1.63]</td><td>1.34 [1.05-1.71]</td></tr><tr><td>Place of birth<sup>c</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>France</td><td>829 (74.1)</td><td>2.20 [2.03-2.38]</td><td>1.73 [1.52-1.97]</td><td>0.002</td><td>1.76 [1.63-1.91]</td><td>3.23 [2.85-3.68]</td></tr><tr><td>Europe (outside France)/Latin and North<br>America/Australia</td><td>87 (7.8)</td><td>2.29 [1.81-2.89]</td><td>1.84 [1.14-2.96]</td><td>0.502</td><td>1.92 [1.52-2.43]</td><td>3.54 [2.20-5.69]</td></tr><tr><td>North Africa and Middle East</td><td>140 (12.5)</td><td>2.79 [2.33-3.34]</td><td>2.66 [1.75-4.04]</td><td>0.948</td><td>2.14 [1.78-2.56]</td><td>3.80 [2.50-5.77]</td></tr><tr><td>Sub-Saharan Africa/Caribbean</td><td>44 (3.9)</td><td>1.19 [0.87-1.62]</td><td>2.14 [0.80-5.70]</td><td>0.398</td><td>1.55 [1.14-2.12]</td><td>3.96 [1.49-10.54]</td></tr><tr><td>Asia</td><td>19 (1.7)</td><td>1.36 [0.84-2.23]</td><td>1.39 [0.45-4.32]</td><td>1.000</td><td>1.71 [1.05-2.79]</td><td>3.50 [1.13-10.85]</td></tr><tr><td>Living in poverty<sup>d</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>699 (64.7)</td><td>2.04 [1.87-2.21]</td><td>1.44 [1.22-1.70]</td><td>&lt;0.001</td><td>1.60 [1.47-1.74]</td><td>2.51 [2.13-2.96]</td></tr><tr><td>Yes</td><td>381 (35.3)</td><td>2.43 [2.15-2.75]</td><td>2.43 [2.04-2.88]</td><td>1.000</td><td>2.46 [2.17-2.78]</td><td>5.00 [4.21-5.95]</td></tr><tr><td>Alcohol use<sup>e</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Absent without past unhealthy use</td><td>499 (44.6)</td><td>2.29 [2.09-2.51]</td><td>1.08 [0.78-1.49]</td><td>&lt;0.001</td><td>1.81 [1.65-1.99]</td><td>2.00 [1.45-2.76]</td></tr><tr><td>Moderate use</td><td>341 (30.5)</td><td>1.64 [1.45-1.86]</td><td>1.45 [1.19-1.77]</td><td>0.335</td><td>1.47 [1.30-1.66]</td><td>2.70 [2.21-3.30]</td></tr><tr><td>Past or current unhealthy use</td><td>278 (24.9)</td><td>3.52 [2.97-4.17]</td><td>2.65 [2.25-3.12]</td><td>0.022</td><td>3.15 [2.66-3.73]</td><td>4.84 [4.11-5.70]</td></tr><tr><td>Tobacco use<sup>f</sup>, pack-years</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>0</td><td>404 (38.6)</td><td>1.92 [1.74-2.12]</td><td>1.43 [0.81-2.52]</td><td>0.380</td><td>1.48 [1.34-1.63]</td><td>2.25 [1.28-3.96]</td></tr><tr><td>1-10</td><td>133 (12.7)</td><td>1.64 [1.35-1.99]</td><td>1.24 [0.88-1.74]</td><td>0.188</td><td>1.72 [1.41-2.09]</td><td>2.49 [1.76-3.49]</td></tr><tr><td>11-20</td><td>140 (13.4)</td><td>1.79 [1.44-2.23]</td><td>1.42 [1.11-1.83]</td><td>0.204</td><td>2.04 [1.64-2.35]</td><td>2.94 [2.29-3.78]</td></tr><tr><td>&gt;20</td><td>369 (35.3)</td><td>3.51 [3.08-3.99]</td><td>2.12 [1.80-2.50]</td><td>&lt;0.001</td><td>2.78 [2.44-3.16]</td><td>3.63 [3.08-4.28]</td></tr><tr><td>Body mass index<sup>g</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Normal</td><td>501 (45.2)</td><td>1.95 [1.76-2.16]</td><td>1.54 [1.30-1.82]</td><td>0.020</td><td>1.66 [1.49-1.84]</td><td>2.88 [2.44-3.41]</td></tr><tr><td>Underweight</td><td>44 (4.0)</td><td>2.72 [1.85-4.00]</td><td>2.49 [1.57-3.95]</td><td>0.896</td><td>2.82 [1.92-4.13]</td><td>5.43 [3.42-8.62]</td></tr><tr><td>Overweight</td><td>373 (33.6)</td><td>2.15 [1.92-2.42]</td><td>1.89 [1.53-2.33]</td><td>0.318</td><td>1.71 [1.52-1.92]</td><td>3.29 [2.66-4.06]</td></tr><tr><td>Obesity</td><td>191 (17.2)</td><td>2.68 [2.29-3.14]</td><td>2.64 [1.91-3.66]</td><td>1.000</td><td>2.36 [2.01-2.76]</td><td>5.15 [3.71-7.14]</td></tr></tbody></table>
<table><caption>TABLE 2 Mortality rates and standardised mortality ratios according to drug injection status (ANRS CO22 Hepather cohort).</caption><thead><tr><th>Characteristics<sup>a</sup></th><th>Deaths (N = 1121)<br>N (%)</th><th>People with no history of injection<br>drug use (N = 703)<br>Mortality rates per 100 person-years<br>[95% CI]</th><th>PHID (N = 242)<br>Mortality rates per 100 person-years<br>[95% CI]</th><th>People with no history of injection<br>drug use (N = 842)<br>Standardised mortality ratios [95% CI]</th><th>PHID (N = 279)<br>Standardised mortality<br>ratios [95% CI]</th></tr></thead><tbody><tr><td>Overall</td><td>2.16 [2.02-2.31]</td><td></td><td>1.79 [1.59-2.01]</td><td>0.006</td><td>3.30 [2.94-3.71]</td></tr><tr><td>Sex</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Male</td><td>717 (64.0)</td><td>2.73 [2.50-2.99]</td><td>2.11 [1.86-2.39]</td><td>0.001</td><td>3.40 [3.00-3.86]</td></tr><tr><td>Female</td><td>404 (36.0)</td><td>1.69 [1.53-1.88]</td><td>0.89 [0.65-1.24]</td><td>&lt;0.001</td><td>2.77 [2.01-3.83]</td></tr><tr><td>Age, years</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt;50</td><td>91 (8.1)</td><td>0.72 [0.53-0.99]</td><td>1.64 [1.25-2.16]</td><td>&lt;0.001</td><td>15.28 [11.62-20.11]</td></tr><tr><td>50-59</td><td>314 (28.0)</td><td>1.50 [1.28-1.75]</td><td>1.86 [1.59-2.17]</td><td>0.062</td><td>5.06 [4.34-5.90]</td></tr><tr><td>≥60</td><td>716 (63.9)</td><td>2.78 [2.58-3.01]</td><td>1.74 [1.37-2.21]</td><td>&lt;0.001</td><td>1.34 [1.05-1.71]</td></tr><tr><td>Place of birth<sup>c</sup></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>France</td><td>829 (74.1)</td><td>2.20 [2.03-2.38]</td><td>1.73 [1.52-1.97]</td><td>0.002</td><td>3.23 [2.85-3.68]</td></tr><tr><td>Europe (outside France)/Latin and North<br>America/Australia</td><td>87 (7.8)</td><td>2.29 [1.81-2.89]</td><td>1.84 [1.14-2.96]</td><td>0.502</td><td>3.54 [2.20-5.69]</td></tr><tr><td>North Africa and Middle East</td><td>140 (12.5)</td><td>2.79 [2.33-3.34]</td><td>2.66 [1.75-4.04]</td><td>0.948</td><td>3.80 [2.50-5.77]</td></tr><tr><td>Sub-Saharan Africa/Caribbean</td><td>44 (3.9)</td><td>1.19 [0.87-1.62]</td><td>2.14 [0.80-5.70]</td><td>0.398</td><td>3.96 [1.49-10.54]</td></tr><tr><td>Asia</td><td>19 (1.7)</td><td>1.36 [0.84-2.23]</td><td>1.39 [0.45-4.32]</td><td>1.000</td><td>3.50 [1.13-10.85]</td></tr><tr><td>Living in poverty<sup>d</sup></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>699 (64.7)</td><td>2.04 [1.87-2.21]</td><td>1.44 [1.22-1.70]</td><td>&lt;0.001</td><td>2.51 [2.13-2.96]</td></tr><tr><td>Yes</td><td>381 (35.3)</td><td>2.43 [2.15-2.75]</td><td>2.43 [2.04-2.88]</td><td>1.000</td><td>5.00 [4.21-5.95]</td></tr><tr><td>Alcohol use<sup>e</sup></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Absinent without past unhealthy use</td><td>499 (44.6)</td><td>2.29 [2.09-2.51]</td><td>1.08 [0.78-1.49]</td><td>&lt;0.001</td><td>2.00 [1.45-2.76]</td></tr><tr><td>Moderate use</td><td>341 (30.5)</td><td>1.64 [1.45-1.86]</td><td>1.45 [1.19-1.77]</td><td>0.335</td><td>2.70 [2.21-3.30]</td></tr><tr><td>Past or current unhealthy use</td><td>278 (24.9)</td><td>3.52 [2.97-4.17]</td><td>2.65 [2.25-3.12]</td><td>0.022</td><td>4.84 [4.11-5.70]</td></tr><tr><td>Tobacco use<sup>f</sup>, pack-years</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>0</td><td>404 (38.6)</td><td>1.92 [1.74-2.12]</td><td>1.43 [0.81-2.52]</td><td>0.380</td><td>2.25 [1.28-3.96]</td></tr><tr><td>1-10</td><td>133 (12.7)</td><td>1.64 [1.35-1.99]</td><td>1.24 [0.88-1.74]</td><td>0.188</td><td>2.49 [1.76-3.49]</td></tr><tr><td>11-20</td><td>140 (13.4)</td><td>1.79 [1.44-2.23]</td><td>1.42 [1.11-1.83]</td><td>0.204</td><td>2.94 [2.29-3.78]</td></tr><tr><td>&gt;20</td><td>369 (35.3)</td><td>3.51 [3.08-3.99]</td><td>2.12 [1.80-2.50]</td><td>&lt;0.001</td><td>3.63 [3.08-4.28]</td></tr><tr><td>Body mass index<sup>g</sup></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Normal</td><td>501 (45.2)</td><td>1.95 [1.76-2.16]</td><td>1.54 [1.30-1.82]</td><td>0.020</td><td>2.88 [2.44-3.41]</td></tr><tr><td>Underweight</td><td>44 (4.0)</td><td>2.72 [1.85-4.00]</td><td>2.49 [1.57-3.95]</td><td>0.896</td><td>5.43 [3.42-8.62]</td></tr><tr><td>Overweight</td><td>373 (33.6)</td><td>2.15 [1.92-2.42]</td><td>1.89 [1.53-2.33]</td><td>0.318</td><td>3.29 [2.66-4.06]</td></tr><tr><td>Obesity</td><td>191 (17.2)</td><td>2.68 [2.29-3.14]</td><td>2.64 [1.91-3.66]</td><td>1.000</td><td>5.15 [3.71-7.14]</td></tr></tbody></table>
<table><caption>TABLE 2 (Continued)</caption><thead><tr><th>Characteristics<sup>a</sup></th><th>Deaths (N = 1121)<br>N (%)</th><th>People with no history of injection drug use (N = 703)<br>Mortality rates per 100 person-years [95% CI]</th><th>PHID (N = 242)<br>Mortality rates per 100 person-years [95% CI]</th><th>p-value<sup>b</sup></th><th>People with no history of injection drug use (N = 842)<br>Standardised mortality ratios [95% CI]</th><th>PHID (N = 279)<br>Standardised mortality ratios [95% CI]</th></tr></thead><tbody><tr><td>Diabetes</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>840 (74.9)</td><td>1.81 [1.67-1.96]</td><td>1.67 [1.47-1.89]</td><td>0.316</td><td>1.59 [1.47-1.72]</td><td>3.14 [2.77-3.56]</td></tr><tr><td>Yes</td><td>281 (25.1)</td><td>4.19 [3.69-4.75]</td><td>3.10 [2.27-4.22]</td><td>0.084</td><td>2.78 [2.45-3.16]</td><td>4.76 [3.49-6.49]</td></tr><tr><td>Advanced liver fibrosis<sup>b</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>454 (43.2)</td><td>1.25 [1.12-1.39]</td><td>1.03 [0.86-1.23]</td><td>0.079</td><td>1.24 [1.12-1.38]</td><td>2.00 [1.66-2.39]</td></tr><tr><td>Yes</td><td>598 (56.8)</td><td>4.84 [4.41-5.31]</td><td>4.47 [3.80-5.25]</td><td>0.427</td><td>2.73 [2.49-3.00]</td><td>7.19 [6.11-8.46]</td></tr><tr><td>Hypertension</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>612 (54.6)</td><td>1.56 [1.42-1.72]</td><td>1.60 [1.40-1.83]</td><td>0.792</td><td>1.71 [1.55-1.88]</td><td>3.14 [2.75-3.60]</td></tr><tr><td>Yes</td><td>508 (45.4)</td><td>3.28 [2.99-3.61]</td><td>2.80 [2.21-3.56]</td><td>0.247</td><td>1.91 [1.74-2.10]</td><td>3.92 [3.09-4.98]</td></tr><tr><td>HCV cure</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>429 (38.3)</td><td>3.10 [2.78-3.46]</td><td>2.49 [2.06-3.01]</td><td>0.053</td><td>5.10 [4.57-5.69]</td><td>11.77 [9.73-14.24]</td></tr><tr><td>Yes by first generation DAA and/or interferon</td><td>7 (0.6)</td><td>0.70 [0.32-1.57]</td><td>0.28 [0.04-1.97]</td><td>0.669</td><td>2.27 [1.02-5.04]</td><td>1.59 [0.22-11.31]</td></tr><tr><td>Yes by second generation DAA</td><td>685 (61.1)</td><td>1.85 [1.69-2.01]</td><td>1.56 [1.35-1.81]</td><td>0.061</td><td>1.29 [1.18-1.40]</td><td>2.30 [1.98-2.67]</td></tr><tr><td>HCV cure</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>429 (38.3)</td><td>3.10 [2.78-3.46]</td><td>2.49 [2.06-3.01]</td><td>0.053</td><td>5.10 [4.57-5.69]</td><td>11.77 [9.73-14.24]</td></tr><tr><td>Yes</td><td>692 (61.7)</td><td>1.81 [1.66-1.98]</td><td>1.52 [1.31-1.77]</td><td>0.049</td><td>1.29 [1.19-1.41]</td><td>2.29 [1.97-2.66]</td></tr></tbody></table>

Abbreviations: CI, confidence interval; DAA, direct-acting antivirals; HCV, hepatitis C virus; PHID, people with a history of injection drug use.

<sup>a</sup>Characteristics are given at cohort enrollment, except for HCV cure (time-varying variable), which was provided at the last available visit.

<sup>b</sup>Fisher's exact test for incidence rates difference.

<sup>c</sup>The category 'Europe and America' included participants from Europe (excluding France), South America (N = 32), North America (N = 20), Central America (N = 2) and Russia (N = 45). The category 'Sub-Saharan Africa' included participants from the Caribbean (N = 10).

<sup>d</sup>Living in poverty was defined as a standard of living lower than the 2015 French poverty threshold (1015 euros per month) [16].

<sup>e</sup>Unhealthy alcohol use was defined as >2 and >3 standard drinks per day for women and men, respectively, in accordance with the French National Authority for Health [17].

<sup>f</sup>The number of pack-years was obtained by multiplying the number of years the person had smoked by the average number of packs of cigarettes smoked per day.

<sup>g</sup>Body mass index was categorised according to World Health Organization cut-offs: overweight: ≥25 and <30 kg/m²; obesity: ≥30 kg/m² [14].

<sup>h</sup>Advanced liver fibrosis was defined as an FIB-4 score >3.25 [15].
<table><caption>TABLE 2 (Continued)</caption><thead><tr><th>Characteristics<sup>a</sup></th><th>Deaths (N = 1121)<br>N (%)</th><th>People with no history of injection drug use (N = 703)<br>Mortality rates per 100 person-years [95% CI]</th><th>PHID (N = 242)<br>Mortality rates per 100 person-years [95% CI]</th><th>p-value<sup>b</sup></th><th>People with no history of injection drug use (N = 842)<br>Standardised mortality ratios [95% CI]</th><th>PHID (N = 279)<br>Standardised mortality ratios [95% CI]</th></tr></thead><tbody><tr><td>Diabetes</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>840 (74.9)</td><td>1.81 [1.67-1.96]</td><td>1.67 [1.47-1.89]</td><td>0.316</td><td>1.59 [1.47-1.72]</td><td>3.14 [2.77-3.56]</td></tr><tr><td>Yes</td><td>281 (25.1)</td><td>4.19 [3.69-4.75]</td><td>3.10 [2.27-4.22]</td><td>0.084</td><td>2.78 [2.45-3.16]</td><td>4.76 [3.49-6.49]</td></tr><tr><td>Advanced liver fibrosis<sup>b</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>454 (43.2)</td><td>1.25 [1.12-1.39]</td><td>1.03 [0.86-1.23]</td><td>0.079</td><td>1.24 [1.12-1.38]</td><td>2.00 [1.66-2.39]</td></tr><tr><td>Yes</td><td>598 (56.8)</td><td>4.84 [4.41-5.31]</td><td>4.47 [3.80-5.25]</td><td>0.427</td><td>2.73 [2.49-3.00]</td><td>7.19 [6.11-8.46]</td></tr><tr><td>Hypertension</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>612 (54.6)</td><td>1.56 [1.42-1.72]</td><td>1.60 [1.40-1.83]</td><td>0.792</td><td>1.71 [1.55-1.88]</td><td>3.14 [2.75-3.60]</td></tr><tr><td>Yes</td><td>508 (45.4)</td><td>3.28 [2.99-3.61]</td><td>2.80 [2.21-3.56]</td><td>0.247</td><td>1.91 [1.74-2.10]</td><td>3.92 [3.09-4.98]</td></tr><tr><td>HCV cure</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>429 (38.3)</td><td>3.10 [2.78-3.46]</td><td>2.49 [2.06-3.01]</td><td>0.053</td><td>5.10 [4.57-5.69]</td><td>11.77 [9.73-14.24]</td></tr><tr><td>Yes by first generation DAA and/or interferon</td><td>7 (0.6)</td><td>0.70 [0.32-1.57]</td><td>0.28 [0.04-1.97]</td><td>0.669</td><td>2.27 [1.02-5.04]</td><td>1.59 [0.22-11.31]</td></tr><tr><td>Yes by second generation DAA</td><td>685 (61.1)</td><td>1.85 [1.69-2.01]</td><td>1.56 [1.35-1.81]</td><td>0.061</td><td>1.29 [1.18-1.40]</td><td>2.30 [1.98-2.67]</td></tr><tr><td>HCV cure</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No</td><td>429 (38.3)</td><td>3.10 [2.78-3.46]</td><td>2.49 [2.06-3.01]</td><td>0.053</td><td>5.10 [4.57-5.69]</td><td>11.77 [9.73-14.24]</td></tr><tr><td>Yes</td><td>692 (61.7)</td><td>1.81 [1.66-1.98]</td><td>1.52 [1.31-1.77]</td><td>0.049</td><td>1.29 [1.19-1.41]</td><td>2.29 [1.97-2.66]</td></tr></tbody></table>

Abbreviations: CI, confidence interval; DAA, direct-acting antivirals; HCV, hepatitis C virus; PHID, people with a history of injection drug use.

<sup>a</sup>Characteristics are given at cohort enrollment, except for HCV cure (time-varying variable), which was provided at the last available visit.

<sup>b</sup>Fisher's exact test for incidence rates difference.

<sup>c</sup>The category 'Europe and America' included participants from Europe (excluding France), South America (N = 32), North America (N = 20), Central America (N = 2) and Russia (N = 45). The category 'Sub-Saharan Africa' included participants from the Caribbean (N = 10).

<sup>d</sup>Living in poverty was defined as a standard of living lower than the 2015 French poverty threshold (1015 euros per month) [16].

<sup>e</sup>Unhealthy alcohol use was defined as >2 and >3 standard drinks per day for women and men, respectively, in accordance with the French National Authority for Health [17].

<sup>f</sup>The number of pack-years was obtained by multiplying the number of years the person had smoked by the average number of packs of cigarettes smoked per day.

<sup>g</sup>Body mass index was categorised according to World Health Organization cut-offs: overweight: ≥25 and <30 kg/m²; obesity: ≥30 kg/m² [14].

<sup>h</sup>Advanced liver fibrosis was defined as an FIB-4 score >3.25 [15].
<table><caption>TABLE 3 Factors associated with all-cause mortality, univariable and multivariable analyses (Cox proportional hazards models, ANRS CO22 Hepather cohort, N = 9735).</caption><thead><tr><th rowspan="2">Explanatory variables</th><th colspan="2">Univariable analyses (N = 9735)</th><th colspan="2">Interactions adjusted for principal effects</th><th colspan="2">Multivariable analysis (N = 8287)</th></tr><tr><th>HR [95% CI]</th><th>p-value</th><th>aHR [95% CI]</th><th>p-value</th><th>aHR [95% CI]</th><th>p-value</th></tr></thead><tbody><tr><td>Drug injection status</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>People with no history of injection drug use (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>PHID</td><td>0.83 [0.72-0.95]</td><td>0.008</td><td></td><td></td><td>0.71 [0.40-1.27]</td><td>0.250</td></tr><tr><td>Sex</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Male (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>Female</td><td>0.63 [0.56-0.71]</td><td>&lt;0.001</td><td></td><td></td><td>0.58 [0.50-0.67]</td><td>&lt;0.001</td></tr><tr><td>Sex*PHID interaction</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Male (ref.)</td><td></td><td></td><td>1</td><td></td><td></td><td></td></tr><tr><td>Female</td><td></td><td></td><td>0.69 [0.47-1.00]</td><td>0.047</td><td></td><td></td></tr><tr><td>Age, years<sup>a</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt;50 (ref.)</td><td>1</td><td>&lt;0.001</td><td></td><td></td><td>1</td><td>&lt;0.001</td></tr><tr><td>50-59</td><td>1.53 [1.22-1.94]</td><td>&lt;0.001</td><td></td><td></td><td>1.42 [0.97-2.07]</td><td>0.0.71</td></tr><tr><td>≥60</td><td>2.33 [1.87-2.90]</td><td>&lt;0.001</td><td></td><td></td><td>1.94 [1.36-2.78]</td><td>&lt;0.001</td></tr><tr><td>Age*PHID interaction</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt;50 (ref.)</td><td></td><td></td><td>1</td><td></td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>50-59</td><td></td><td></td><td>0.52 [0.33-0.84]</td><td>0.007</td><td>1</td><td>0.428</td></tr><tr><td>≥60</td><td></td><td></td><td>0.25 [0.15-0.41]</td><td>&lt;0.001</td><td>0.41 [0.24-0.72]</td><td>0.002</td></tr><tr><td>Place of birth<sup>b</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>France (ref.)</td><td>1</td><td>&lt;0.001</td><td></td><td></td><td>1</td><td>0.002</td></tr><tr><td>Europe (outside France)/Latin and North America/Australia</td><td>1.07 [0.86-1.34]</td><td>0.514</td><td></td><td></td><td>0.87 [0.67-1.11]</td><td>0.261</td></tr><tr><td>North Africa and Middle East</td><td>1.36 [1.13-1.62]</td><td>0.001</td><td></td><td></td><td>0.87 [0.70-1.09]</td><td>0.221</td></tr><tr><td>Sub-Saharan Africa/Caribbean</td><td>0.60 [0.44-0.81]</td><td>0.001</td><td></td><td></td><td>0.54 [0.38-0.76]</td><td>&lt;0.001</td></tr><tr><td>Asia</td><td>0.68 [0.43-1.07]</td><td>0.094</td><td></td><td></td><td>0.54 [0.31-0.95]</td><td>0.034</td></tr><tr><td>Living in poverty<sup>c</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>Yes</td><td>1.30 [1.15-1.48]</td><td>&lt;0.001</td><td></td><td></td><td>1.29 [1.11-1.50]</td><td>0.001</td></tr><tr><td>Alcohol use<sup>d</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Absent without past unhealthy use (ref.)</td><td>1</td><td>&lt;0.001</td><td></td><td></td><td>1</td><td>&lt;0.001</td></tr><tr><td>Moderate use</td><td>0.76 [0.66-0.87]</td><td>&lt;0.001</td><td></td><td></td><td>0.69 [0.58-0.83]</td><td>&lt;0.001</td></tr><tr><td>Past or current unhealthy use</td><td>1.44 [1.25-1.67]</td><td>&lt;0.001</td><td></td><td></td><td>0.94 [0.74-1.19]</td><td>0.581</td></tr><tr><td>Alcohol use*PHID interaction</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Absent without past unhealthy use (ref.)</td><td></td><td></td><td>1</td><td>0.011</td><td>1</td><td>0.010</td></tr><tr><td>Moderate use</td><td></td><td></td><td>1.87 [1.24-2.82]</td><td>0.003</td><td>1.99 [1.27-3.11]</td><td>0.003</td></tr></tbody></table>
<table><caption>TABLE 3 Factors associated with all-cause mortality, univariable and multivariable analyses (Cox proportional hazards models, ANRS CO22 Hepather cohort, N = 9735).</caption><thead><tr><th rowspan="2">Explanatory variables</th><th colspan="2">Univariable analyses (N = 9735)</th><th colspan="2">Interactions adjusted for principal effects</th><th colspan="2">Multivariable analysis (N = 8287)</th></tr><tr><th>HR [95% CI]</th><th>p-value</th><th>aHR [95% CI]</th><th>p-value</th><th>aHR [95% CI]</th><th>p-value</th></tr></thead><tbody><tr><td>Drug injection status</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>People with no history of injection drug use (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>PHID</td><td>0.83 [0.72-0.95]</td><td>0.008</td><td></td><td></td><td>0.71 [0.40-1.27]</td><td>0.250</td></tr><tr><td>Sex</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Male (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>Female</td><td>0.63 [0.56-0.71]</td><td>&lt;0.001</td><td></td><td></td><td>0.58 [0.50-0.67]</td><td>&lt;0.001</td></tr><tr><td>Sex*PHID interaction</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Male (ref.)</td><td></td><td></td><td>1</td><td></td><td></td><td></td></tr><tr><td>Female</td><td></td><td></td><td>0.69 [0.47-1.00]</td><td>0.047</td><td></td><td></td></tr><tr><td>Age, years<sup>a</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt;50 (ref.)</td><td>1</td><td>&lt;0.001</td><td></td><td></td><td>1</td><td>&lt;0.001</td></tr><tr><td>50-59</td><td>1.53 [1.22-1.94]</td><td>&lt;0.001</td><td></td><td></td><td>1.42 [0.97-2.07]</td><td>0.0.71</td></tr><tr><td>≥60</td><td>2.33 [1.87-2.90]</td><td>&lt;0.001</td><td></td><td></td><td>1.94 [1.36-2.78]</td><td>&lt;0.001</td></tr><tr><td>Age*PHID interaction</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt;50 (ref.)</td><td></td><td></td><td>1</td><td></td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>50-59</td><td></td><td></td><td>0.52 [0.33-0.84]</td><td>0.007</td><td>1</td><td>0.428</td></tr><tr><td>≥60</td><td></td><td></td><td>0.25 [0.15-0.41]</td><td>&lt;0.001</td><td>0.41 [0.24-0.72]</td><td>0.002</td></tr><tr><td>Place of birth<sup>b</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>France (ref.)</td><td>1</td><td>&lt;0.001</td><td></td><td></td><td>1</td><td>0.002</td></tr><tr><td>Europe (outside France)/Latin and North America/Australia</td><td>1.07 [0.86-1.34]</td><td>0.514</td><td></td><td></td><td>0.87 [0.67-1.11]</td><td>0.261</td></tr><tr><td>North Africa and Middle East</td><td>1.36 [1.13-1.62]</td><td>0.001</td><td></td><td></td><td>0.87 [0.70-1.09]</td><td>0.221</td></tr><tr><td>Sub-Saharan Africa/Caribbean</td><td>0.60 [0.44-0.81]</td><td>0.001</td><td></td><td></td><td>0.54 [0.38-0.76]</td><td>&lt;0.001</td></tr><tr><td>Asia</td><td>0.68 [0.43-1.07]</td><td>0.094</td><td></td><td></td><td>0.54 [0.31-0.95]</td><td>0.034</td></tr><tr><td>Living in poverty<sup>c</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>Yes</td><td>1.30 [1.15-1.48]</td><td>&lt;0.001</td><td></td><td></td><td>1.29 [1.11-1.50]</td><td>0.001</td></tr><tr><td>Alcohol use<sup>d</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Absent without past unhealthy use (ref.)</td><td>1</td><td>&lt;0.001</td><td></td><td></td><td>1</td><td>&lt;0.001</td></tr><tr><td>Moderate use</td><td>0.76 [0.66-0.87]</td><td>&lt;0.001</td><td></td><td></td><td>0.69 [0.58-0.83]</td><td>&lt;0.001</td></tr><tr><td>Past or current unhealthy use</td><td>1.44 [1.25-1.67]</td><td>&lt;0.001</td><td></td><td></td><td>0.94 [0.74-1.19]</td><td>0.581</td></tr><tr><td>Alcohol use*PHID interaction</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Absent without past unhealthy use (ref.)</td><td></td><td></td><td>1</td><td>0.011</td><td>1</td><td>0.010</td></tr><tr><td>Moderate use</td><td></td><td></td><td>1.87 [1.24-2.82]</td><td>0.003</td><td>1.99 [1.27-3.11]</td><td>0.003</td></tr></tbody></table>
<table><caption>TABLE 3 (Continued)</caption><thead><tr><th rowspan="2">Explanatory variables</th><th colspan="2">Univariable analyses (N = 9735)</th><th colspan="2">Interactions adjusted for principal effects</th><th colspan="2">Multivariable analysis (N = 8287)</th></tr><tr><th>HR [95% CI]</th><th>p-value</th><th>aHR [95% CI]</th><th>p-value</th><th>aHR [95% CI]</th><th>p-value</th></tr></thead><tbody><tr><td>Past or current unhealthy use</td><td></td><td></td><td>1.59 [1.06-2.40]</td><td>0.026</td><td>1.69 [1.06-2.69]</td><td>0.026</td></tr><tr><td>Tobacco use<sup>a</sup>, pack-years</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>0 (ref.)</td><td>1</td><td>&lt;0.001</td><td></td><td></td><td>1</td><td>&lt;0.001</td></tr><tr><td>1-10</td><td>0.80 [0.66-0.98]</td><td>0.029</td><td></td><td></td><td>1.00 [0.80-1.25]</td><td>0.991</td></tr><tr><td>11-20</td><td>0.85 [0.70-1.03]</td><td>0.101</td><td></td><td></td><td>1.03 [0.82-1.29]</td><td>0.804</td></tr><tr><td>&gt;20</td><td>1.49 [1.30-1.72]</td><td>&lt;0.001</td><td></td><td></td><td>1.53 [1.27-1.84]</td><td>&lt;0.001</td></tr><tr><td>Body mass index<sup>d</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Normal (ref.)</td><td>1</td><td>&lt;0.001</td><td></td><td></td><td>1</td><td>0.016</td></tr><tr><td>Underweight</td><td>1.46 [1.06-1.99]</td><td>0.019</td><td></td><td></td><td>1.57 [1.09-2.26]</td><td>0.015</td></tr><tr><td>Overweight</td><td>1.14 [1.00-1.30]</td><td>0.054</td><td></td><td></td><td>0.92 [0.79-1.07]</td><td>0.297</td></tr><tr><td>Obesity</td><td>1.47 [1.24-1.73]</td><td>&lt;0.001</td><td></td><td></td><td>1.12 [0.93-1.36]</td><td>0.233</td></tr><tr><td>Diabetes</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>Yes</td><td>2.26 [1.98-2.59]</td><td>&lt;0.001</td><td></td><td></td><td>1.37 [1.15-1.62]</td><td>&lt;0.001</td></tr><tr><td>Advanced liver fibrosis<sup>b</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>Yes</td><td>4.03 [3.57-4.55]</td><td>&lt;0.001</td><td></td><td></td><td>3.71 [3.21-4.29]</td><td>&lt;0.001</td></tr><tr><td>Hypertension</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>Yes</td><td>2.04 [1.81-2.29]</td><td>&lt;0.001</td><td></td><td></td><td>1.65 [1.42-1.92]</td><td>&lt;0.001</td></tr><tr><td>HCV cure<sup>a</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>Yes</td><td>0.44 [0.39-0.50]</td><td>&lt;0.001</td><td></td><td></td><td>0.34 [0.29-0.39]</td><td>&lt;0.001</td></tr><tr><td>HCV cure<sup>a</sup>PHID interaction</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No (ref.)</td><td></td><td></td><td>1</td><td></td><td></td><td></td></tr><tr><td>Yes</td><td></td><td></td><td>1.08 [0.82-1.43]</td><td>0.567</td><td></td><td></td></tr></tbody></table>

Note: P-values in bold are global p-values.

Abbreviations: aHR, adjusted hazard ratio; CI, confidence interval; HR, hazard ratio; HCV, hepatitis C virus; PHID, people with a history of injection drug use.

<sup>a</sup>All explanatory variables are fixed, except for age and HCV cure, which were time-varying variables.

<sup>b</sup>The category 'Europe and America' included participants from Europe (outside France), South America (N = 20), Central America (N = 2), and Russia (N = 47). The category 'Sub-Saharan Africa' included participants from the Caribbean (N = 11).

<sup>c</sup>Living in poverty was defined as a standard of living lower than the 2015 French poverty threshold (1015 euros per month) [16].

<sup>d</sup>Unhealthy alcohol use was defined as >2 and >3 standard drinks per day for women and men, respectively, in accordance with the French National Authority for Health [17].

<sup>e</sup>The number of pack-years was obtained by multiplying the number of years the person had smoked by the average number of packs of cigarettes smoked per day.

<sup>f</sup>Body mass index was categorised according to World Health Organization cut-offs: overweight: ≥25 and <30 kg/m², obesity: ≥30 kg/m² [14].

<sup>g</sup>Advanced liver fibrosis was defined as a FIB-4 score >3.25 [15].
<table><caption>TABLE 3 (Continued)</caption><thead><tr><th rowspan="2">Explanatory variables</th><th colspan="2">Univariable analyses (N = 9735)</th><th colspan="2">Interactions adjusted for principal effects</th><th colspan="2">Multivariable analysis (N = 8287)</th></tr><tr><th>HR [95% CI]</th><th>p-value</th><th>aHR [95% CI]</th><th>p-value</th><th>aHR [95% CI]</th><th>p-value</th></tr></thead><tbody><tr><td>Past or current unhealthy use</td><td></td><td></td><td>1.59 [1.06-2.40]</td><td>0.026</td><td>1.69 [1.06-2.69]</td><td>0.026</td></tr><tr><td>Tobacco use<sup>a</sup>, pack-years</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>0 (ref.)</td><td>1</td><td>&lt;0.001</td><td></td><td></td><td>1</td><td>&lt;0.001</td></tr><tr><td>1-10</td><td>0.80 [0.66-0.98]</td><td>0.029</td><td></td><td></td><td>1.00 [0.80-1.25]</td><td>0.991</td></tr><tr><td>11-20</td><td>0.85 [0.70-1.03]</td><td>0.101</td><td></td><td></td><td>1.03 [0.82-1.29]</td><td>0.804</td></tr><tr><td>&gt;20</td><td>1.49 [1.30-1.72]</td><td>&lt;0.001</td><td></td><td></td><td>1.53 [1.27-1.84]</td><td>&lt;0.001</td></tr><tr><td>Body mass index<sup>d</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Normal (ref.)</td><td>1</td><td>&lt;0.001</td><td></td><td></td><td>1</td><td>0.016</td></tr><tr><td>Underweight</td><td>1.46 [1.06-1.99]</td><td>0.019</td><td></td><td></td><td>1.57 [1.09-2.26]</td><td>0.015</td></tr><tr><td>Overweight</td><td>1.14 [1.00-1.30]</td><td>0.054</td><td></td><td></td><td>0.92 [0.79-1.07]</td><td>0.297</td></tr><tr><td>Obesity</td><td>1.47 [1.24-1.73]</td><td>&lt;0.001</td><td></td><td></td><td>1.12 [0.93-1.36]</td><td>0.233</td></tr><tr><td>Diabetes</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>Yes</td><td>2.26 [1.98-2.59]</td><td>&lt;0.001</td><td></td><td></td><td>1.37 [1.15-1.62]</td><td>&lt;0.001</td></tr><tr><td>Advanced liver fibrosis<sup>b</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>Yes</td><td>4.03 [3.57-4.55]</td><td>&lt;0.001</td><td></td><td></td><td>3.71 [3.21-4.29]</td><td>&lt;0.001</td></tr><tr><td>Hypertension</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>Yes</td><td>2.04 [1.81-2.29]</td><td>&lt;0.001</td><td></td><td></td><td>1.65 [1.42-1.92]</td><td>&lt;0.001</td></tr><tr><td>HCV cure<sup>a</sup></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No (ref.)</td><td>1</td><td></td><td></td><td></td><td>1</td><td></td></tr><tr><td>Yes</td><td>0.44 [0.39-0.50]</td><td>&lt;0.001</td><td></td><td></td><td>0.34 [0.29-0.39]</td><td>&lt;0.001</td></tr><tr><td>HCV cure<sup>a</sup>PHID interaction</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No (ref.)</td><td></td><td></td><td>1</td><td></td><td></td><td></td></tr><tr><td>Yes</td><td></td><td></td><td>1.08 [0.82-1.43]</td><td>0.567</td><td></td><td></td></tr></tbody></table>

Note: P-values in bold are global p-values.

Abbreviations: aHR, adjusted hazard ratio; CI, confidence interval; HR, hazard ratio; HCV, hepatitis C virus; PHID, people with a history of injection drug use.

<sup>a</sup>All explanatory variables are fixed, except for age and HCV cure, which were time-varying variables.

<sup>b</sup>The category 'Europe and America' included participants from Europe (outside France), South America (N = 20), Central America (N = 2), and Russia (N = 47). The category 'Sub-Saharan Africa' included participants from the Caribbean (N = 11).

<sup>c</sup>Living in poverty was defined as a standard of living lower than the 2015 French poverty threshold (1015 euros per month) [16].

<sup>d</sup>Unhealthy alcohol use was defined as >2 and >3 standard drinks per day for women and men, respectively, in accordance with the French National Authority for Health [17].

<sup>e</sup>The number of pack-years was obtained by multiplying the number of years the person had smoked by the average number of packs of cigarettes smoked per day.

<sup>f</sup>Body mass index was categorised according to World Health Organization cut-offs: overweight: ≥25 and <30 kg/m², obesity: ≥30 kg/m² [14].

<sup>g</sup>Advanced liver fibrosis was defined as a FIB-4 score >3.25 [15].
alcohol use was not associated with the study outcome, while unhealthy use was (1.58 [1.06–2.37], *p* = 0.026).

4 | DISCUSSION

In this study, DAA-related HCV cure was associated with a 66% lower risk in all-cause mortality, irrespective of drug injection status. This result shows that expanded access to DAA resulted in an equitable reduction in mortality for PHID, who nevertheless still had a higher SMR than people with no history of injection drug use.

Furthermore, this result suggests that the decrease in HCV-related mortality—and therefore in infectious disease-related mortality overall—among PHID could be strengthened by adequately scaling up DAA [11, 22, 23]. Currently, too many barriers exist [24–26] to this scale-up, yet hope lies in innovative multilevel interventions and outreach strategies that have proven efficient in reaching and engaging PHID in HCV testing and prevention [27–31]. It has been shown that multidisciplinary, people-centred strategies improves HCV linkage to care and adherence to treatment in a variety of settings [32]. For instance, providing HCV treatment in primary care rather than in hospital facilities may increase treatment uptake and cure rates [33], and receiving treatment at a peer-led needle and syringe program was estimated as acceptable by people who inject drugs [34].

While PHID equally benefited from DAA-related HCV cure in terms of reduced mortality, past or current alcohol use prevalence was three times higher among PHID than people with no history of injection drug use; moreover, its effect was only significant among the former. Unhealthy alcohol use is a risk factor for liver fibrosis and cirrhosis, which may lead to liver-related death. As advanced liver fibrosis is a major risk factor for mortality among HCV-infected people [11, 35] (adjusted hazard ratio = 3.71 in our study sample), we may expect unhealthy alcohol use to increase all-cause and liver-related mortality in this population [36, 37]. The protective effect of moderate alcohol use on mortality we found in people with no history of injection drug use has previously been found in some general population studies [38–40]. This effect, which is more present in the context of cardiovascular mortality [41], may be the result of confounding effects of health behaviours [42, 43] not present in PHID. As treatment of potential alcohol use disorder may benefit patients, substance use services should include comprehensive care for HCV-infected people [44, 45].

The mortality rates higher in our study population than what would have been expected in the general

population is in line with a recent population-based cohort study. Hamill et al. found SMRs between 2.96 and 13.61 (according to the setting and liver disease severity) among their sample of DAA-cured participants [35]. They also found a protective effect of being a woman in some sub-populations and, while differently assessed, detrimental effects of recent unhealthy alcohol use and past or recent substance use (in most of their sub-populations).

Our study has several strengths. First, it had a large sample size. Second, we collected data on demographic, clinical and socio-behavioural variables. Third, we were able to compare PHID with people with no history of injection drug use in the same context. One limitation is that only a small number of participants were active injectors; accordingly, replication of our results is needed in samples with more active injectors, as drug-related mortality may be important in this sub-population. We did not make the distinction between first and second generation DAA in our survival analyses because of the low number of cases of first generation DAA-related cure. Future analyses exclusively including second generation DAA treatment era should be performed to inform on the generalisability of our findings. Another limitation is that deaths that were not reported in the cohort context (i.e., for participants lost to follow-up) were missed. As we may expect PHID to be lost to follow-up more frequently than people with no history of injection drug use, this may have led to underestimation of mortality among PHID. Moreover, causes of deaths were not available. Therefore, we were not able to separately estimate for instance COVID-, liver- or drug-related mortality, and highlight specific patterns of mortality in each sub-population.

To conclude, DAA-related HCV cure led to comparable benefits in terms of mortality reduction in PHID and people with no history of injection drug use. Policies and strategies to enhance DAA uptake among PHID are needed to lower mortality in this population.

AUTHOR CONTRIBUTIONS

Conceptualisation: Tangui Barré, Marc Bourlière, Camelia Protopopescu, Fabrice Carrat and Patrizia Carrieri. Methodology: Clémence Ramier and Camelia Protopopescu. Formal analysis: Clémence Ramier. Investigation: Marc Bourlière, Lucia Parlati, Carole Cagnot, Celine Doral, Jérôme Nicol, Fabien Zoulim and Fabrice Carrat. Writing—original draft: Tangui Barré. Writing—review and editing: all authors.

ACKNOWLEDGMENTS

The Hepather cohort is funded by ANRS | Emerging Infectious Diseases, the French Agence Nationale de la
alcohol use was not associated with the study outcome, while unhealthy use was (1.58 [1.06–2.37], *p* = 0.026).

4 | DISCUSSION

In this study, DAA-related HCV cure was associated with a 66% lower risk in all-cause mortality, irrespective of drug injection status. This result shows that expanded access to DAA resulted in an equitable reduction in mortality for PHID, who nevertheless still had a higher SMR than people with no history of injection drug use.

Furthermore, this result suggests that the decrease in HCV-related mortality—and therefore in infectious disease-related mortality overall—among PHID could be strengthened by adequately scaling up DAA [11, 22, 23]. Currently, too many barriers exist [24–26] to this scale-up, yet hope lies in innovative multilevel interventions and outreach strategies that have proven efficient in reaching and engaging PHID in HCV testing and prevention [27–31]. It has been shown that multidisciplinary, people-centred strategies improves HCV linkage to care and adherence to treatment in a variety of settings [32]. For instance, providing HCV treatment in primary care rather than in hospital facilities may increase treatment uptake and cure rates [33], and receiving treatment at a peer-led needle and syringe program was estimated as acceptable by people who inject drugs [34].

While PHID equally benefited from DAA-related HCV cure in terms of reduced mortality, past or current alcohol use prevalence was three times higher among PHID than people with no history of injection drug use; moreover, its effect was only significant among the former. Unhealthy alcohol use is a risk factor for liver fibrosis and cirrhosis, which may lead to liver-related death. As advanced liver fibrosis is a major risk factor for mortality among HCV-infected people [11, 35] (adjusted hazard ratio = 3.71 in our study sample), we may expect unhealthy alcohol use to increase all-cause and liver-related mortality in this population [36, 37]. The protective effect of moderate alcohol use on mortality we found in people with no history of injection drug use has previously been found in some general population studies [38–40]. This effect, which is more present in the context of cardiovascular mortality [41], may be the result of confounding effects of health behaviours [42, 43] not present in PHID. As treatment of potential alcohol use disorder may benefit patients, substance use services should include comprehensive care for HCV-infected people [44, 45].

The mortality rates higher in our study population than what would have been expected in the general

population is in line with a recent population-based cohort study. Hamill et al. found SMRs between 2.96 and 13.61 (according to the setting and liver disease severity) among their sample of DAA-cured participants [35]. They also found a protective effect of being a woman in some sub-populations and, while differently assessed, detrimental effects of recent unhealthy alcohol use and past or recent substance use (in most of their sub-populations).

Our study has several strengths. First, it had a large sample size. Second, we collected data on demographic, clinical and socio-behavioural variables. Third, we were able to compare PHID with people with no history of injection drug use in the same context. One limitation is that only a small number of participants were active injectors; accordingly, replication of our results is needed in samples with more active injectors, as drug-related mortality may be important in this sub-population. We did not make the distinction between first and second generation DAA in our survival analyses because of the low number of cases of first generation DAA-related cure. Future analyses exclusively including second generation DAA treatment era should be performed to inform on the generalisability of our findings. Another limitation is that deaths that were not reported in the cohort context (i.e., for participants lost to follow-up) were missed. As we may expect PHID to be lost to follow-up more frequently than people with no history of injection drug use, this may have led to underestimation of mortality among PHID. Moreover, causes of deaths were not available. Therefore, we were not able to separately estimate for instance COVID-, liver- or drug-related mortality, and highlight specific patterns of mortality in each sub-population.

To conclude, DAA-related HCV cure led to comparable benefits in terms of mortality reduction in PHID and people with no history of injection drug use. Policies and strategies to enhance DAA uptake among PHID are needed to lower mortality in this population.

AUTHOR CONTRIBUTIONS

Conceptualisation: Tangui Barré, Marc Bourlière, Camelia Protopopescu, Fabrice Carrat and Patrizia Carrieri. Methodology: Clémence Ramier and Camelia Protopopescu. Formal analysis: Clémence Ramier. Investigation: Marc Bourlière, Lucia Parlati, Carole Cagnot, Celine Dorival, Jérôme Nicol, Fabien Zoulim and Fabrice Carrat. Writing—original draft: Tangui Barré. Writing—review and editing: all authors.

ACKNOWLEDGMENTS

The Hepather cohort is funded by ANRS | Emerging Infectious Diseases, the French Agence Nationale de la
<figure><img src="image_4.png" /></figure>

Recherche for the France 2030 #ANR-19-COHO-0002 program, the French Direction Générale de la Santé, Merck Sharp and Dohme, Janssen-Cilag, Gilead, Abbvie, Bristol-Myers Squibb, Roche. These funding sources had no role in the writing of the manuscript or in the decision to submit it for publication. The authors would like to thank the study participants and participating clinicians at each site. The authors also thank the INSERM-ANRS MIE for sponsoring, funding and conducting the ANRS CO22 Hepather cohort in collaboration with the French Association for the Study of the Liver (Association Française pour l'Etude du Foie). Finally, our thanks to Jude Sweeney (Milan, Italy) for the English revision and copy-editing of our manuscript.

## CONFLICT OF INTEREST STATEMENT

No conflict declared.

## ORCID

Tangui Barré https://orcid.org/0000-0002-3439-8868

Camelia Protopopescu https://orcid.org/0000-0003-0164-7917

## REFERENCES

1. Mathers BM, Degenhardt L, Bucello C, Lemon J, Wiessing L, Hickman M. Mortality among people who inject drugs: a systematic review and meta-analysis. Bull World Health Organ. 2013;91:102-23.

2. Larney S, Tran LT, Leung J, Santo T, Santomauro D, Hickman M, et al. All-cause and cause-specific mortality among people using extramedical opioids: a systematic review and meta-analysis. JAMA Psychiatry. 2020;77:493-502.

3. Valerio H, Alavi M, Conway A, Silk D, Treloar C, Martinello M, et al. Declining prevalence of current HCV infection and increased treatment uptake among people who inject drugs: the ETHOS engage study. Int J Drug Policy. 2022; 105:103706.

4. Rashti R, Sharafi H, Alavian SM, Moradi Y, Mohamadi Bolbanabad A, Moradi G. Systematic review and meta-analysis of global prevalence of HBsAg and HIV and HCV antibodies among people who inject drugs and female sex workers. Pathogens. 2020;9:432.

5. Hill PL, Stoové M, Agius PA, Maher L, Hickman M, Crawford S, et al. Mortality in the SuperMIX cohort of people who inject drugs in Melbourne, Australia: a prospective observational study. Addiction. 2022;117:3091-8.

6. Degenhardt L, Bucello C, Mathers B, Briegleb C, Ali H, Hickman M, et al. Mortality among regular or dependent users of heroin and other opioids: a systematic review and meta-analysis of cohort studies. Addiction. 2011;106:32-51.

7. Kimber J, Stoové M, Maher L. Mortality among people who inject drugs: ten-year follow-up of the hepatitis C virus cohort. Drug Alcohol Rev. 2019;38:270-3.

8. Mathers BM, Degenhardt L. Examining non-AIDS mortality among people who inject drugs. AIDS. 2014;28(Suppl 4): S435-44.

9. Schulte B, Schmidt CS, Strada L, Rosenkranz M, Schäfer I, Verthein U, et al. Hepatitis C virus prevalence and incidence in a large nationwide sample of patients in opioid substitution treatment in Germany: a prospective cohort study. Clin Infect Dis. 2020;70:2199-205.

10. Cepeda JA, Thomas DL, Astemborski J, Rudolph JE, Gicquelais R, Kirk GD, et al. Impact of hepatitis C treatment uptake on cirrhosis and mortality in persons who inject drugs. Ann Intern Med. 2022;175:1083-91.

11. Janjua NZ, Wong S, Abdia Y, Jeong D, Buller-Taylor T, Adu PA, et al. Impact of direct-acting antivirals for HCV on mortality in a large population-based cohort study. J Hepatol. 2021;75:1049-57.

12. Pol S, Bourliere M, Lucier S, Hezode C, Dorival C, Larrey D, et al. Safety and efficacy of daclatasvir-sofosbuvir in HCV genotype 1-mono-infected patients. J Hepatol. 2017;66:39-47.

13. Brouard C, Boussac-Zarebska M, Silvain C, Durand J, de Lédinghen V, Pillonel J, et al. Rapid and large-scale implementation of HCV treatment advances in France, 2007-2015. BMC Infect Dis. 2017;17:784.

14. World Health Organization. Body mass index—BMI [Internet]. 2019 [cited 9 July 2019]. Available from: http://www.euro.who.int/en/health-topics/disease-prevention/nutrition/healthy-lifestyle/body-mass-index-bmi

15. Sterling RK, Eduardo L, Nathan C, Ricard S, Cassia CM, Julio M, et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology. 2006;43:1317-25.

16. Institut National de la Statistique et des Etudes Economiques. Définition—Pauvreté monétaire/Seuil de pauvreté/Seuil de pauvreté [Insee [Internet]. 2021 [cited 10 December 2021]. Available from: https://www.insee.fr/fr/metadonnees/definition/c1653

17. Haute Autorité de Santé (French National Authority for Health). Screening tool for early detection and brief intervention (Outil d'aide au repérage précoce et à l'intervention brève) [Internet]. 2014 [cited 24 October 2019]. Available from: https://www.has-sante.fr/jcms/c_1795221/fr/outil-d-aide-au-reperage-precoce-et-intervention-breve-alcool-cannabis-tabac-chez-l-adulte

18. Institut National de la Statistique et des Etudes Economiques. Statistiques nationales sur les décès en 2019 – Les décès en 2019 | Insee (National death statistics, 2019) [Internet]. 2020 [cited 14 June 2023]. Available from: https://www.insee.fr/fr/statistiques/4770424?sommaire=4772633&q=Statistiques+nationales+sur+les+d%C3%A9c%C3%A8s+en+2019

19. Iversen J, Page K, Madden A, Maher L. HIV, HCV and health-related harms among women who inject drugs: implications for prevention and treatment. J Acquir Immune Defic Syndr. 2015;69:S176-81.

20. Horyniak D, Dietze P, Degenhardt L, Higgs P, McIlwraith F, Alati R, et al. The relationship between age and risky injecting behaviours among a sample of Australian people who inject drugs. Drug Alcohol Depend. 2013;132:541-6.

21. Irvin R, Chander G, Falade-Nwulia O, Astemborski J, Starbird L, Kirk GD, et al. Overlapping epidemics of alcohol and illicit drug use among HCV-infected persons who inject drugs. Addict Behav. 2019;96:56-61.
<figure><img src="image_5.png" /></figure>

Recherche for the France 2030 #ANR-19-COHO-0002 program, the French Direction Générale de la Santé, Merck Sharp and Dohme, Janssen-Cilag, Gilead, Abbvie, Bristol-Myers Squibb, Roche. These funding sources had no role in the writing of the manuscript or in the decision to submit it for publication. The authors would like to thank the study participants and participating clinicians at each site. The authors also thank the INSERM-ANRS MIE for sponsoring, funding and conducting the ANRS CO22 Hepather cohort in collaboration with the French Association for the Study of the Liver (Association Française pour l'Etude du Foie). Finally, our thanks to Jude Sweeney (Milan, Italy) for the English revision and copy-editing of our manuscript.

## CONFLICT OF INTEREST STATEMENT

No conflict declared.

## ORCID

Tangui Barré https://orcid.org/0000-0002-3439-8868

Camelia Protopopescu https://orcid.org/0000-0003-0164-7917

## REFERENCES

1. Mathers BM, Degenhardt L, Bucello C, Lemon J, Wiessing L, Hickman M. Mortality among people who inject drugs: a systematic review and meta-analysis. Bull World Health Organ. 2013;91:102-23.

2. Larney S, Tran LT, Leung J, Santo T, Santomauro D, Hickman M, et al. All-cause and cause-specific mortality among people using extramedical opioids: a systematic review and meta-analysis. JAMA Psychiatry. 2020;77:493-502.

3. Valerio H, Alavi M, Conway A, Silk D, Treloar C, Martinello M, et al. Declining prevalence of current HCV infection and increased treatment uptake among people who inject drugs: the ETHOS engage study. Int J Drug Policy. 2022; 105:103706.

4. Rashti R, Sharafi H, Alavian SM, Moradi Y, Mohamadi Bolbanabad A, Moradi G. Systematic review and meta-analysis of global prevalence of HBsAg and HIV and HCV antibodies among people who inject drugs and female sex workers. Pathogens. 2020;9:432.

5. Hill PL, Stoové M, Agius PA, Maher L, Hickman M, Crawford S, et al. Mortality in the SuperMIX cohort of people who inject drugs in Melbourne, Australia: a prospective observational study. Addiction. 2022;117:3091-8.

6. Degenhardt L, Bucello C, Mathers B, Briegleb C, Ali H, Hickman M, et al. Mortality among regular or dependent users of heroin and other opioids: a systematic review and meta-analysis of cohort studies. Addiction. 2011;106:32-51.

7. Kimber J, Stoové M, Maher L. Mortality among people who inject drugs: ten-year follow-up of the hepatitis C virus cohort. Drug Alcohol Rev. 2019;38:270-3.

8. Mathers BM, Degenhardt L. Examining non-AIDS mortality among people who inject drugs. AIDS. 2014;28(Suppl 4): S435-44.

9. Schulte B, Schmidt CS, Strada L, Rosenkranz M, Schäfer I, Verthein U, et al. Hepatitis C virus prevalence and incidence in a large nationwide sample of patients in opioid substitution treatment in Germany: a prospective cohort study. Clin Infect Dis. 2020;70:2199-205.

10. Cepeda JA, Thomas DL, Astemborski J, Rudolph JE, Gicquelais R, Kirk GD, et al. Impact of hepatitis C treatment uptake on cirrhosis and mortality in persons who inject drugs. Ann Intern Med. 2022;175:1083-91.

11. Janjua NZ, Wong S, Abdia Y, Jeong D, Buller-Taylor T, Adu PA, et al. Impact of direct-acting antivirals for HCV on mortality in a large population-based cohort study. J Hepatol. 2021;75:1049-57.

12. Pol S, Bourliere M, Lucier S, Hezode C, Dorival C, Larrey D, et al. Safety and efficacy of daclatasvir-sofosbuvir in HCV genotype 1-mono-infected patients. J Hepatol. 2017;66:39-47.

13. Brouard C, Boussac-Zarebska M, Silvain C, Durand J, de Lédinghen V, Pillonel J, et al. Rapid and large-scale implementation of HCV treatment advances in France, 2007-2015. BMC Infect Dis. 2017;17:784.

14. World Health Organization. Body mass index—BMI [Internet]. 2019 [cited 9 July 2019]. Available from: http://www.euro.who.int/en/health-topics/disease-prevention/nutrition/healthy-lifestyle/body-mass-index-bmi

15. Sterling RK, Eduardo L, Nathan C, Ricard S, Cassia CM, Julio M, et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology. 2006;43:1317-25.

16. Institut National de la Statistique et des Etudes Economiques. Définition—Pauvreté monétaire/Seuil de pauvreté/Seuil de pauvreté [Insee [Internet]. 2021 [cited 10 December 2021]. Available from: https://www.insee.fr/fr/metadonnees/definition/c1653

17. Haute Autorité de Santé (French National Authority for Health). Screening tool for early detection and brief intervention (Outil d'aide au repérage précoce et à l'intervention brève) [Internet]. 2014 [cited 24 October 2019]. Available from: https://www.has-sante.fr/jcms/c_1795221/fr/outil-d-aide-au-reperage-precoce-et-intervention-breve-alcool-cannabis-tabac-chez-l-adulte

18. Institut National de la Statistique et des Etudes Economiques. Statistiques nationales sur les décès en 2019 – Les décès en 2019 | Insee (National death statistics, 2019) [Internet]. 2020 [cited 14 June 2023]. Available from: https://www.insee.fr/fr/statistiques/4770424?sommaire=4772633&q=Statistiques+nationales+sur+les+d%C3%A9c%C3%A8s+en+2019

19. Iversen J, Page K, Madden A, Maher L. HIV, HCV and health-related harms among women who inject drugs: implications for prevention and treatment. J Acquir Immune Defic Syndr. 2015;69:S176-81.

20. Horyniak D, Dietze P, Degenhardt L, Higgs P, McIlwraith F, Alati R, et al. The relationship between age and risky injecting behaviours among a sample of Australian people who inject drugs. Drug Alcohol Depend. 2013;132:541-6.

21. Irvin R, Chander G, Falade-Nwulia O, Astemborski J, Starbird L, Kirk GD, et al. Overlapping epidemics of alcohol and illicit drug use among HCV-infected persons who inject drugs. Addict Behav. 2019;96:56-61.
<figure><img src="image_5.png" /></figure>

22. Politi J, Guerras JM, Donat M, Belza MJ, Ronda E, Barrio G, et al. Favorable impact in hepatitis C-related mortality following free access to direct-acting antivirals in Spain. Hepatology. 2022;75:1247-56.

23. Ogawa E, Chien N, Kam L, Yeo YH, Ji F, Huang DQ, et al. Association of direct-acting antiviral therapy with liver and nonliver complications and long-term mortality in patients with chronic hepatitis C. JAMA Intern Med. 2023;183:97-105.

24. Barré T, Marcellin F, Beo VD, Delorme J, Rojas TR, Mathurin P, et al. Untreated alcohol use disorder in people who inject drugs (PWID) in France: a major barrier to HCV treatment uptake (the ANRS-FANTASIO study). Addiction. 2020;115:573-82.

25. Rojas Rojas T, Di Beo V, Delorme J, Barre T, Mathurin P, Protopopescu C, et al. Lower HCV treatment uptake in women who have received opioid agonist therapy before and during the DAA era: the ANRS FANTASIO project. Int J Drug Policy. 2019;72:61-8.

26. Rolland B, Lions C, Di Beo V, Carrieri P, Authier N, Barré T, et al. Adherence to opioid agonist therapy predicts uptake of direct-acting antivirals in people who use drugs: results from the French national healthcare database (the ANRS FANTASIO study). Harm Reduct J. 2022;19:119.

27. Bajis S, Dore GJ, Hajarizadeh B, Cunningham EB, Maher L, Grebely J. Interventions to enhance testing, linkage to care and treatment uptake for hepatitis C virus infection among people who inject drugs: a systematic review. Int J Drug Policy. 2017;47:34-46.

28. Blackburn NA, Patel RC, Zibbell JE. Improving screening methods for hepatitis C among people who inject drugs: findings from the HepTLC initiative, 2012-2014. Public Health Rep. 2016;131(Suppl 2):91-7.

29. Broad J, Mason K, Guyton M, Lettner B, Matelski J, Powis J. Peer outreach point-of-care testing as a bridge to hepatitis C care for people who inject drugs in Toronto, Canada. Int J Drug Policy. 2020;80:102755.

30. Coupland H, White B, Bates A, Park JN, Iversen J, Maher L. Engaging people who inject drugs in hepatitis C virus testing and prevention through community-based outreach, in Sydney, Australia. Drug Alcohol Rev. 2019;38:177-84.

31. Latham NH, Pedrana A, Doyle JS, Howell J, Williams B, Higgs P, et al. Community-based, point-of-care hepatitis C testing: perspectives and preferences of people who inject drugs. J Viral Hepat. 2019;26:919-22.

32. Schwarz T, Horváth I, Fenz L, Schmutterer I, Rosian-Schikuta I, Mårdh O. Interventions to increase linkage to care and adherence to treatment for hepatitis C among people who inject drugs: a systematic review and practical considerations from an expert panel consultation. Int J Drug Policy. 2022;102:103588.

33. Wade AJ, Doyle JS, Gane E, Stedman C, Draper B, Iser D, et al. Outcomes of treatment for hepatitis C in primary care, compared to hospital-based care: a randomized, controlled trial in people who inject drugs. Clin Infect Dis. 2020;70:1900-6.

34. Conway A, Read P, Gilliver R, McNaughton T, Valerio H, Cunningham EB, et al. Awareness of HCV status and preferences for testing and treatment among people with recent

injecting drug use at a peer-led needle and syringe program: the TEMPO pilot study. Viruses. 2022;14:2463.

35. Hamill V, Wong S, Benselin J, Krajden M, Hayes PC, Mutimer D, et al. Mortality rates among patients successfully treated for hepatitis C in the era of interferon-free antivirals: population based cohort study. BMJ. 2023;382:e074001.

36. Sinn DH, Kang D, Guallar E, Chang Y, Ryu S, Zhao D, et al. Alcohol intake and mortality in patients with chronic viral hepatitis: a nationwide cohort study. Am J Gastroenterol. 2021;116:329-35.

37. Younossi ZM, Zheng L, Stepanova M, Venkatesan C, Mir HM. Moderate, excessive or heavy alcohol consumption: each is significantly associated with increased mortality in patients with chronic hepatitis C. Aliment Pharmacol Ther. 2013;37:703-9.

38. Stockwell T, Zhao J, Panwar S, Roemer A, Naimi T, Chikritzhs T. Do 'moderate' drinkers have reduced mortality risk? A systematic review and meta-analysis of alcohol consumption and all-cause mortality. J Stud Alcohol Drugs. 2016;77:185-98.

39. Tian Y, Liu J, Zhao Y, Jiang N, Liu X, Zhao G, et al. Alcohol consumption and all-cause and cause-specific mortality among US adults: prospective cohort study. BMC Med. 2023;21:208.

40. Zhao J, Stockwell T, Naimi T, Churchill S, Clay J, Sherk A. Association between daily alcohol intake and risk of all-cause mortality. JAMA Netw Open. 2023;6:e236185.

41. Ding C, O'Neill D, Bell S, Stamatakis E, Britton A. Association of alcohol consumption with morbidity and mortality in patients with cardiovascular disease: original data and meta-analysis of 48,423 men and women. BMC Med. 2021;19:167.

42. Powell L, Feng Y, Duncan MJ, Hamer M, Stamatakis E. Does a physically active lifestyle attenuate the association between alcohol consumption and mortality risk? Findings from the UK biobank. Prev Med. 2020;130:105901.

43. Smothers B, Bertolucci D. Alcohol consumption and health-promoting behavior in a U.S. household sample: leisure-time physical activity. J Stud Alcohol. 2001;62:467-76.

44. Harney BL, Brereton R, Whitton B, Pietrzak D, Paige E, Roberts SK, et al. Hepatitis C treatment in a co-located mental health and alcohol and drug service using a nurse-led model of care. J Viral Hepat. 2021;28:771-8.

45. Ngo BV, James JR, Blalock KL, Jackson SL, Chew LD, Tsui JI. Hepatitis C treatment outcomes among patients treated in co-located primary care and addiction treatment settings. J Subst Abus Treat. 2021;131:108438.

**How to cite this article:** Barré T, Bourlière M, Parlati L, Ramier C, Marcellin F, Protopopescu C, et al. Hepatitis C virus cure from direct-acting antivirals and mortality: Are people with and without a history of injection drug use in the same boat? (ANRS CO22 Hepather cohort). Drug Alcohol Rev. 2024;43(3):718-31. https://doi.org/10.1111/dar.13802
<figure><img src="image_6.png" /></figure>

22. Politi J, Guerras JM, Donat M, Belza MJ, Ronda E, Barrio G, et al. Favorable impact in hepatitis C-related mortality following free access to direct-acting antivirals in Spain. Hepatology. 2022;75:1247-56.

23. Ogawa E, Chien N, Kam L, Yeo YH, Ji F, Huang DQ, et al. Association of direct-acting antiviral therapy with liver and nonliver complications and long-term mortality in patients with chronic hepatitis C. JAMA Intern Med. 2023;183:97-105.

24. Barré T, Marcellin F, Beo VD, Delorme J, Rojas TR, Mathurin P, et al. Untreated alcohol use disorder in people who inject drugs (PWID) in France: a major barrier to HCV treatment uptake (the ANRS-FANTASIO study). Addiction. 2020;115:573-82.

25. Rojas Rojas T, Di Beo V, Delorme J, Barre T, Mathurin P, Protopopescu C, et al. Lower HCV treatment uptake in women who have received opioid agonist therapy before and during the DAA era: the ANRS FANTASIO project. Int J Drug Policy. 2019;72:61-8.

26. Rolland B, Lions C, Di Beo V, Carrieri P, Authier N, Barré T, et al. Adherence to opioid agonist therapy predicts uptake of direct-acting antivirals in people who use drugs: results from the French national healthcare database (the ANRS FANTASIO study). Harm Reduct J. 2022;19:119.

27. Bajis S, Dore GJ, Hajarizadeh B, Cunningham EB, Maher L, Grebely J. Interventions to enhance testing, linkage to care and treatment uptake for hepatitis C virus infection among people who inject drugs: a systematic review. Int J Drug Policy. 2017;47:34-46.

28. Blackburn NA, Patel RC, Zibbell JE. Improving screening methods for hepatitis C among people who inject drugs: findings from the HepTLC initiative, 2012-2014. Public Health Rep. 2016;131(Suppl 2):91-7.

29. Broad J, Mason K, Guyton M, Lettner B, Matelski J, Powis J. Peer outreach point-of-care testing as a bridge to hepatitis C care for people who inject drugs in Toronto, Canada. Int J Drug Policy. 2020;80:102755.

30. Coupland H, White B, Bates A, Park JN, Iversen J, Maher L. Engaging people who inject drugs in hepatitis C virus testing and prevention through community-based outreach, in Sydney, Australia. Drug Alcohol Rev. 2019;38:177-84.

31. Latham NH, Pedrana A, Doyle JS, Howell J, Williams B, Higgs P, et al. Community-based, point-of-care hepatitis C testing: perspectives and preferences of people who inject drugs. J Viral Hepat. 2019;26:919-22.

32. Schwarz T, Horváth I, Fenz L, Schmutterer I, Rosian-Schikuta I, Mårdh O. Interventions to increase linkage to care and adherence to treatment for hepatitis C among people who inject drugs: a systematic review and practical considerations from an expert panel consultation. Int J Drug Policy. 2022;102:103588.

33. Wade AJ, Doyle JS, Gane E, Stedman C, Draper B, Iser D, et al. Outcomes of treatment for hepatitis C in primary care, compared to hospital-based care: a randomized, controlled trial in people who inject drugs. Clin Infect Dis. 2020;70:1900-6.

34. Conway A, Read P, Gilliver R, McNaughton T, Valerio H, Cunningham EB, et al. Awareness of HCV status and preferences for testing and treatment among people with recent

injecting drug use at a peer-led needle and syringe program: the TEMPO pilot study. Viruses. 2022;14:2463.

35. Hamill V, Wong S, Benselin J, Krajden M, Hayes PC, Mutimer D, et al. Mortality rates among patients successfully treated for hepatitis C in the era of interferon-free antivirals: population based cohort study. BMJ. 2023;382:e074001.

36. Sinn DH, Kang D, Guallar E, Chang Y, Ryu S, Zhao D, et al. Alcohol intake and mortality in patients with chronic viral hepatitis: a nationwide cohort study. Am J Gastroenterol. 2021;116:329-35.

37. Younossi ZM, Zheng L, Stepanova M, Venkatesan C, Mir HM. Moderate, excessive or heavy alcohol consumption: each is significantly associated with increased mortality in patients with chronic hepatitis C. Aliment Pharmacol Ther. 2013;37:703-9.

38. Stockwell T, Zhao J, Panwar S, Roemer A, Naimi T, Chikritzhs T. Do 'moderate' drinkers have reduced mortality risk? A systematic review and meta-analysis of alcohol consumption and all-cause mortality. J Stud Alcohol Drugs. 2016;77:185-98.

39. Tian Y, Liu J, Zhao Y, Jiang N, Liu X, Zhao G, et al. Alcohol consumption and all-cause and cause-specific mortality among US adults: prospective cohort study. BMC Med. 2023;21:208.

40. Zhao J, Stockwell T, Naimi T, Churchill S, Clay J, Sherk A. Association between daily alcohol intake and risk of all-cause mortality. JAMA Netw Open. 2023;6:e236185.

41. Ding C, O'Neill D, Bell S, Stamatakis E, Britton A. Association of alcohol consumption with morbidity and mortality in patients with cardiovascular disease: original data and meta-analysis of 48,423 men and women. BMC Med. 2021;19:167.

42. Powell L, Feng Y, Duncan MJ, Hamer M, Stamatakis E. Does a physically active lifestyle attenuate the association between alcohol consumption and mortality risk? Findings from the UK biobank. Prev Med. 2020;130:105901.

43. Smothers B, Bertolucci D. Alcohol consumption and health-promoting behavior in a U.S. household sample: leisure-time physical activity. J Stud Alcohol. 2001;62:467-76.

44. Harney BL, Brereton R, Whitton B, Pietrzak D, Paige E, Roberts SK, et al. Hepatitis C treatment in a co-located mental health and alcohol and drug service using a nurse-led model of care. J Viral Hepat. 2021;28:771-8.

45. Ngo BV, James JR, Blalock KL, Jackson SL, Chew LD, Tsui JI. Hepatitis C treatment outcomes among patients treated in co-located primary care and addiction treatment settings. J Subst Abus Treat. 2021;131:108438.

**How to cite this article:** Barré T, Bourlière M, Parlati L, Ramier C, Marcellin F, Protopopescu C, et al. Hepatitis C virus cure from direct-acting antivirals and mortality: Are people with and without a history of injection drug use in the same boat? (ANRS CO22 Hepather cohort). Drug Alcohol Rev. 2024;43(3):718-31. https://doi.org/10.1111/dar.13802
# APPENDIX

Members of the ANRS/AFEF Hepather Study Group:

Laurent Alric, Delphine Bonnet, Océane Camou (CHU Rangueil, Toulouse, France), Fabien Zoulim, Marianne Maynard, François Bailly, Bénédicte Poumaroux, Miroslava Subic (Hospices Civils de Lyon, Lyon, France), François Raffi, Eric Billaud, David Boutoille, Maeva Lefebvre, Elisabeth André-Garnier (Hôpital Hôtel-Dieu, Nantes, France), Paul Cales, Isabelle Hubert, Clémence Canivet, Françoise Lunel, Jérôme Boursier (CHU Angers, Angers, France), Tarik Asselah, Nathalie Boyer, Nathalie Giuily, Corinne Castelnau, Giovanna Scoazec (Hôpital Beaujon, Clichy, France), Stanislas Pol, Hélène Fontaine, Lucia Parlati, Emilie Rousseaud, Anaïs Vallet-Pichard, Philippe Sogni (Hôpital Cochin, Paris, France), Victor de Ledinghen, Juliette Foucher, Jean-Baptiste Hiriart, Paul Hermabessière, Marie Irlès-Depé (Hôpital Haut-Lévêque, Pessac, Bordeaux, France), Marc Bourlière, Si Nafa Si Ahmed, Valérie Oules, Rania Kibeche (Hôpital Saint Joseph, Marseille, France), Albert Tran, Rodolphe Anty, Eve Gelsi, Régine Truchi (CHU de Nice, Nice, France), Dominique Thabut, Saloua Hammeche, Joseph Moussali (Hôpital de la Pitié Salpétrière, Paris, France), Xavier Causse, Barbara De Dieuleveult, Brahim Ouarani, Damien Labarrière, Magali Jeulin (CHR La Source, Orléans, France), Nathalie Ganne, Véronique Grandolemaire, Pierre Nahon, Séverine Brulé, Lucie Del Pozo (Avicenne, Bobigny, France), Dominique Guyader, Caroline Jezequel, Audrey Brener, Aline Rabot (CHU Rennes, Rennes, France), François Habersetzer, Thomas F. Baumert, Lawrence Serfaty, Pauline Simonoumbissie, Alexandre BOLLE (Hôpitaux Universitaires de Strasbourg, Strasbourg, France), Jean-Pierre Bronowicki, Mouni Bensenane-Oussalah, Vincent Haghnejad, Sébastien Daude, Sarah Hadj-Rhouma (CHU de Nancy, Nancy, France), Georges-Philippe Pageaux, Dominique Larrey, Magda Meszaros (Hôpital Saint Eloi, Montpellier, France), Sophie Metivier, Christophe Bureau, Thibault Morales, Jean Marie Peron, Hélène Larrue (CHU Rangueil, Toulouse, France), Thomas Decaens, Marie-Noelle Hilleret, Charlotte Costentin, Bleuenn Brusset, Agnès Bonadona (CHU de Grenoble, Grenoble, France), Ghassan Riachi, Odile Goria, Fatima Paris, Hélène Montialoux (CHU Charles Nicolle, Rouen, France), Vincent Leroy, Giuliana Amaddeo, Anne Varaut, Mélanie Simoes, Rachida Amzal, Slim Fourati (Hôpital Henri Mondor, Créteil, France), Olivier Chazouillières, Tony

Andreani, Bénédicte Angoulevant, Azeline Chevance (Hôpital Saint-Antoine, Paris, France), Jean-Charles Duclos Vallée, Audrey Coilly, Rodolphe Sobesky, Alina Pascale (Hôpital Paul Brousse, Villejuif, France), Benjamin Buchard, Armand Abergel, Maud Reymond, Chanteranne Brigitte, Léon Muti (Hôpital Estaing, Clermont-Ferrand, France), Vincent Di Martino (Hôpital Jean-Minjoz, Besançon, France), Claire Geist, Guillaume Conroy, Raphaëlle Riffault (Centre Hospitalier Régional, Metz, France), Isabelle Rosa, Camille Barrault, Laurent Costes, Anne Wampach (Centre Hospitalier Intercommunal, Créteil, France), Véronique Loustaud-Ratti, Paul Carrier, Maryline Debette-Gratien, (CHU Limoges, Limoges, France), Christine Silvain, Valentin Rolle, Valérie Roumy, Astrid Guyot d'Asnières de Salins (Hôpital de la Milétrie, Poitiers, France), Philippe Mathurin, Guillaume Lassailly, Elise Lemaitre, Valérie Canva, Sébastien Dharancy, Alexandre Louvet (CHRU Claude Huriez, Lille, France), Anne Minello, Marianne Latournerie, Thomas Mouillot Léa Lerosey, Théophile Gerster (Dijon University Hospital, Dijon, France), Dominique Roulot, Zahia Ben Abdesselam, (Hôpital Avicenne, Bobigny, France), Louis D'Alteroche, Coralie Fleurent, Charlotte Nicolas, Laure Elkrief, Anaïs Jaillais (CHU Trousseau, 37044 Tours, France), Denis Ouzan (Institut Arnault Tzank, Saint-Laurent-duVar, France), Jérôme Gournay, Caroline Chevalier, Isabelle Archambeaud (CHU de Nantes, Nantes, France), Isabelle Portal (CHU Timone, Marseille, France), Thông Dao (Hôpital de la Côte de Nacre, Caen, France), Moana Gelu-Simeon, Marie-Josée Lafrance, Lucie Catherine (CHU de Pointe-à-Pitre, Pointe-à-Pitre, Guadeloupe). Cécile Brouard (Agence Nationale de Santé Publique, Saint Maurice, France), Patrizia Carrieri (INSERM U912, Marseille, France), Elisabeth Delarocque-Astagneau (Inserm UMR1181, Paris), Chantal Housset (Inserm UMR-S938 1 IFR65, Paris), Linda Wittkop (ISPED-INSERM U897, Bordeaux, France), Jessica Zucman-Rossi (Inserm U674/1162, Paris), Marianne L'hennaff (ARCAT-TRT-5-CHV, France), Michèle Sizorn (SOS hépatites, France), Ventzislava Petrov-Sanchez, Carole Cagnot, Cécile Moins, Anais Boston, Elise Landry, Guillaume Le Meut, Alpha Diallo, (ANRS-MIE, Paris, France), Fabrice Carrat, Frederic Chau, Céline Dorival, Isabelle Goderel, Clovis Lusivika-Nzinga, Jonathan Bellet, Jessica Chane-Teng, Grégory Pannetier, Jérôme Nicol (Sorbonne University & INSERM U1136—IPLESP, Paris, France).
# APPENDIX

Members of the ANRS/AFEF Hepather Study Group:

Laurent Alric, Delphine Bonnet, Océane Camou (CHU Rangueil, Toulouse, France), Fabien Zoulim, Marianne Maynard, François Bailly, Bénédicte Poumaroux, Miroslava Subic (Hospices Civils de Lyon, Lyon, France), François Raffi, Eric Billaud, David Boutoille, Maeva Lefebvre, Elisabeth André-Garnier (Hôpital Hôtel-Dieu, Nantes, France), Paul Cales, Isabelle Hubert, Clémence Canivet, Françoise Lunel, Jérôme Boursier (CHU Angers, Angers, France), Tarik Asselah, Nathalie Boyer, Nathalie Giuily, Corinne Castelnau, Giovanna Scoazec (Hôpital Beaujon, Clichy, France), Stanislas Pol, Hélène Fontaine, Lucia Parlati, Emilie Rousseaud, Anaïs Vallet-Pichard, Philippe Sogni (Hôpital Cochin, Paris, France), Victor de Ledinghen, Juliette Foucher, Jean-Baptiste Hiriart, Paul Hermabessière, Marie Irlès-Depé (Hôpital Haut-Lévêque, Pessac, Bordeaux, France), Marc Bourlière, Si Nafa Si Ahmed, Valérie Oules, Rania Kibeche (Hôpital Saint Joseph, Marseille, France), Albert Tran, Rodolphe Anty, Eve Gelsi, Régine Truchi (CHU de Nice, Nice, France), Dominique Thabut, Saloua Hammeche, Joseph Moussali (Hôpital de la Pitié Salpétrière, Paris, France), Xavier Causse, Barbara De Dieuleveult, Brahim Ouarani, Damien Labarrière, Magali Jeulin (CHR La Source, Orléans, France), Nathalie Ganne, Véronique Grandolemaire, Pierre Nahon, Séverine Brulé, Lucie Del Pozo (Avicenne, Bobigny, France), Dominique Guyader, Caroline Jezequel, Audrey Brener, Aline Rabot (CHU Rennes, Rennes, France), François Habersetzer, Thomas F. Baumert, Lawrence Serfaty, Pauline Simo-Noumbissie, Alexandre BOLLE (Hôpitaux Universitaires de Strasbourg, Strasbourg, France), Jean-Pierre Bronowicki, Mouni Bensenane-Oussalah, Vincent Haghnejad, Sébastien Daude, Sarah Hadj-Rhouma (CHU de Nancy, Nancy, France), Georges-Philippe Pageaux, Dominique Larrey, Magda Meszaros (Hôpital Saint Eloi, Montpellier, France), Sophie Metivier, Christophe Bureau, Thibault Morales, Jean Marie Peron, Hélène Larrue (CHU Rangueil, Toulouse, France), Thomas Decaens, Marie-Noelle Hilleret, Charlotte Costentin, Bleuenn Brusset, Agnès Bonadona (CHU de Grenoble, Grenoble, France), Ghassan Riachi, Odile Goria, Fatima Paris, Hélène Montialoux (CHU Charles Nicolle, Rouen, France), Vincent Leroy, Giuliana Amaddeo, Anne Varaut, Mélanie Simoes, Rachida Amzal, Slim Fourati (Hôpital Henri Mondor, Créteil, France), Olivier Chazouillières, Tony

Andreani, Bénédicte Angoulevant, Azeline Chevance (Hôpital Saint-Antoine, Paris, France), Jean-Charles Duclos Vallée, Audrey Coilly, Rodolphe Sobesky, Alina Pascale (Hôpital Paul Brousse, Villejuif, France), Benjamin Buchard, Armand Abergel, Maud Reymond, Chantzeranne Brigitte, Léon Muti (Hôpital Estaing, Clermont-Ferrand, France), Vincent Di Martino (Hôpital Jean-Minjoz, Besançon, France), Claire Geist, Guillaume Conroy, Raphaëlle Riffault (Centre Hospitalier Régional, Metz, France), Isabelle Rosa, Camille Barrault, Laurent Costes, Anne Wampach (Centre Hospitalier Intercommunal, Créteil, France), Véronique Loustaud-Ratti, Paul Carrier, Maryline Debette-Gratien, (CHU Limoges, Limoges, France), Christine Silvain, Valentin Rolle, Valérie Roumy, Astrid Guyot d'Asnières de Salins (Hôpital de la Milétrie, Poitiers, France), Philippe Mathurin, Guillaume Lassailly, Elise Lemaitre, Valérie Canva, Sébastien Dharancy, Alexandre Louvet (CHRU Claude Huriez, Lille, France), Anne Minello, Marianne Latournerie, Thomas Mouillot Léa Lerosey, Théophile Gerster (Dijon University Hospital, Dijon, France), Dominique Roulot, Zahia Ben Abdesselam, (Hôpital Avicenne, Bobigny, France), Louis D'Alteroche, Coralie Fleurent, Charlotte Nicolas, Laure Elkrief, Anaïs Jaillais (CHU Trousseau, 37044 Tours, France), Denis Ouzan (Institut Arnault Tzank, Saint-Laurent-duVar, France), Jérôme Gournay, Caroline Chevalier, Isabelle Archambeaud (CHU de Nantes, Nantes, France), Isabelle Portal (CHU Timone, Marseille, France), Thông Dao (Hôpital de la Côte de Nacre, Caen, France), Moana Gelu-Simeon, Marie-Josée Lafrance, Lucie Catherine (CHU de Pointe-à-Pitre, Pointe-à-Pitre, Guadeloupe). Cécile Brouard (Agence Nationale de Santé Publique, Saint Maurice, France), Patrizia Carrieri (INSERM U912, Marseille, France), Elisabeth Delarocque-Astagneau (Inserm UMR1181, Paris), Chantal Housset (Inserm UMR-S938 1 IFR65, Paris), Linda Wittkop (ISPED-INSERM U897, Bordeaux, France), Jessica Zucman-Rossi (Inserm U674/1162, Paris), Marianne L'hennaff (ARCAT-TRT-5-CHV, France), Michèle Sizorn (SOS hépatites, France), Ventzislava Petrov-Sanchez, Carole Cagnot, Cécile Moins, Anais Boston, Elise Landry, Guillaume Le Meut, Alpha Diallo, (ANRS-MIE, Paris, France), Fabrice Carrat, Frederic Chau, Céline Dorival, Isabelle Goderel, Clovis Lusivika-Nzinga, Jonathan Bellet, Jessica Chane-Teng, Grégory Pannetier, Jérôme Nicol (Sorbonne University & INSERM U1136—IPLESP, Paris, France).