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. Author manuscript; available in PMC: 2024 Dec 1.
Published in final edited form as: Drug Alcohol Depend. 2023 Oct 21;253:111007. doi: 10.1016/j.drugalcdep.2023.111007

Temporal trends in HCV treatment uptake and success among people who inject drugs in Baltimore, MD since the introduction of direct acting antivirals

Catelyn R Coyle a,b,c,*, Rachel E Gicquelais d,*, Becky L Genberg a, Jacquie Astemborski a, Oluwaseun Falade-Nwulia e, Gregory D Kirk a,e, David L Thomas e, Shruti H Mehta a
PMCID: PMC10917145  NIHMSID: NIHMS1943616  PMID: 38456165

Abstract

Background:

Although hepatitis C virus (HCV) can be cured by direct acting antivirals (DAA), uptake is not well characterized for people who inject drugs (PWID).

Methods:

Among 1,130 participants of a community-based cohort of PWID with chronic HCV, we longitudinally characterized HCV treatment uptake and cure early (2014-2016) and later (2017-2020).

Results:

Cumulative HCV treatment uptake increased from 4% in 2014 to 68% in 2020 and the percent with HCV viremia declined from nearly 100% to 33%. Predictors of treatment uptake varied across periods. Age (incidence rate ratio [IRR] per 5-year increase: 1.28; 95% confidence interval [CI]: 1.15, 1.42), educational attainment (IRR for ≥ high school diploma: 1.31; 95% CI: 1.04, 1.66), HIV coinfection with suppressed viral load (IRR vs. HIV negative: 2.08; 95% CI: 1.63, 2.66) and alcohol dependence (IRR vs. no alcohol use: 0.63; 95% CI: 0.43, 0.91) were associated with treatment uptake in the early period, but not later. HIV coinfection with a detectable viral load (IRR vs. HIV negative: 0.46; 95% CI: 0.23, 0.95) and daily injecting (IRR: 0.46 vs. no injection; 95% CI: 0.27, 0.79) were significantly associated with lower treatment uptake later. Homelessness was associated with significantly reduced likelihood of viral clearance in the late DAA era (IRR: 0.51; 95% CI: 0.30, 0.88).

Conclusion:

Treatment uptake improved substantially in this cohort of PWID in the first five years of DAA availability with commensurate declines in viremia. Additional efforts are needed to treat those actively injecting and unstably housed in order to realize elimination goals.

Keywords: HCV treatment, people who inject drugs (PWID), direct acting antivirals (DAA), injection drug use, barriers

1. INTRODUCTION

Hepatitis C virus (HCV) is the most prevalent bloodborne viral infection in the United States (Alter et al., 1999; Hofmeister et al., 2019). Injection drug use (IDU) remains the most common mode of transmission in the US and prevalence of HCV among people who inject drugs (PWID) has historically been upwards of 90% (Bell et al., 1990; Bolumar et al., 1996; van Ameijden et al., 1993). Moreover, in the US, HCV incidence has more than quadrupled since 2010 (Division of Viral Hepatitis at CDC, 2020, 2017, 2011), reflecting an expansion of the epidemic among PWID in urban settings to one that increasingly includes populations who live in suburban and rural areas of the US (Ly et al., 2017; Zibbell et al., 2014).

With the initial approval of direct acting antivirals (DAAs) in 2014, HCV treatment has minimal adverse events and result in cure rates of >98% (Bourliere et al., 2017; Everson et al., 2015; Jacobson et al., 2017; Kwo et al., 2017; Zeuzem et al., 2018). In response to these new therapeutics and the growing burden of HCV-associated liver disease and mortality, the World Health Organization and National Academies of Sciences, Engineering, and Medicine released/endorsed goals for global HCV elimination in 2015: specifically, 1) to decrease HCV incidence by 80% by 2030, and 2) to decrease HCV-related mortality by 65% by 2030 (Buckley and Strom, 2016; World Health Organization, 2016).

PWID may experience challenges accessing HCV treatment (Alavi et al., 2014; Iversen et al., 2017, 2014; Young et al., 2018) due to multifactorial barriers including poor knowledge and competing priorities, concerns about treatment-related side effects, stigma, and provider unwillingness to treat actively injecting PWID (Mehta et al., 2007, 2005). In addition, state Medicaid plans may restrict access to DAAs due to their high cost (NVHR and CHLPI, 2017). While implementation of these restrictions varied across states, they included requirements for advanced liver fibrosis and 6-months abstinence from substance use, and treatment was limited to providers at specialty practices (i.e., hepatology, gastroenterology, or infectious diseases).

Insurance restrictions have since relaxed in many states. For example, by 2017, Maryland’s Medicaid plan relaxed its sobriety restriction (2016 for those living with HIV) and enabled primary care providers and non-infectious disease specialists to prescribe treatment in consultation with a specialist. By mid-2019, treatment became available to all those with mild fibrosis regardless of HIV status (NVHR and CHLPI, 2020, 2017). Treatment uptake among PWID has improved in areas where insurance restrictions were relaxed and among those who are engaged in specialty healthcare or PWID-related services (Bass et al., 2018; Brown et al., 2017; Dore et al., 2016; Falade-Nwulia et al., 2019). However, many PWID who are disconnected from specialty services may face persistent barriers to treatment. In the context of these dynamics, we evaluate temporal trends in HCV treatment uptake and impact on the proportion of persons with ongoing HCV infection (viremia) since the advent of DAAs from 2014 through 2020 considering both the expanded use of DAAs and relaxation of restrictions among a community-based cohort of PWID.

2. METHODS

2.1. Study population

The ALIVE (AIDS Linked to the Intravenous Experience) Study is a community-based cohort of current and former PWID in Baltimore, MD, ongoing since 1988 and previously described (Vlahov et al., 1991). Participants are recruited primarily through street outreach, flyer distribution and peer referrals. Recruitment has spanned more than three decades with open enrollment in 1988-1989 (N=2,939), 1994-1995 (N=434), 1997-1998 (N=295), 2005-2008 (N=1,009), and 2015-2018 (N=830). Eligible participants were ≥18 years of age with a history of injection drug use. In total, 5,506 individuals have been enrolled across all recruitment periods. This analysis includes 1,130 HCV-antibody positive participants with evidence of chronic HCV infection as of 2012 (for those recruited by 2008) or when they joined the study (for those recruited in 2015-2018). Evidence of chronic infection was defined as having either 1) viremia (detectable HCV RNA) or 2) self-reporting a history of DAA-based treatment (regardless of whether they tested positive for HCV RNA) at their first study visit included in this analysis. The latter criteria was necessary to capture DAA treatment prior to enrollment.

2.2. HCV treatment in Maryland

We evaluated outcomes in two periods: 1) early in the availability of DAAs (January 2014-December 2016 when most states had significant restrictions) and 2) the later DAA period (January 2017- February 2020) when restrictions were sequentially relaxed. In Maryland, Medicaid restrictions prior to 2017 included 6 months abstinence from drugs and alcohol, prescription of HCV treatment by a specialist, and documentation of advanced liver disease (F2 or greater) (NVHR and CHLPI, 2017). In the later DAA period included in our analysis (January 2017- February 2020), restrictions were sequentially relaxed (2017: abstinence restriction changed to screening and counseling and treatment could be prescribed by non-specialists in consultation with a specialist and 2019: liver disease requirement shifted to F1) (NVHR and CHLPI, 2020, 2017). We were unable to evaluate the impact of later removal of all fibrosis restrictions in February of 2020 because of COVID-19.

2.3. Data collection

At entry, ALIVE participants self-reported demographic characteristics, lifetime drug use, and medical history. Subsequently, participants were followed semi-annually, at which time they completed surveys about substance use (types and frequency), comorbidities, healthcare utilization within the previous 6-months and frequency of IDU within the past 30 days. A semi-annual FibroScan was performed on all participants to measure liver stiffness (fibrosis) (Ragazzo et al., 2017). FibroScan results were categorized as: no or mild fibrosis (<8 kPa), significant fibrosis (8 kPa-12.3 kPa), or cirrhosis (>12.3 kPa) (Kirk et al., 2009; Mehta et al., 2012).

Participants were screened for HIV at each study visit using an enzyme-linked immunosorbent assay (ELISA) and Geenius HIV 1/2 Confirmatory Assay (Bio-Rad, Hercules, California). An HIV RNA test (Roche, Basel, Switzerland) was performed on HIV-positive participants at each visit to determine HIV viral suppression (≤50 copies/mL). All participants were screened for HCV antibodies at baseline using an ELISA (Ortho Clinical Diagnostics, Raritan, NJ) followed by confirmatory HCV RNA testing (Abbott Molecular, Des Plaines, Ill). An HCV RNA test was performed for all antibody-positive participants during the year 2012, and then annually on all HCV-antibody positive participants during 2014-2020 after the approval of DAAs.

The study was approved by the Johns Hopkins School of Public Health IRB and all participants provided written informed consent.

2.4. Outcome and covariates

The primary outcome, self-reported HCV treatment uptake, was based on whether a participant self-reported being treated for HCV, at any study visit. As a secondary outcome, we characterized clearance of HCV viremia, a biological proxy for treatment uptake and success. This was defined as having an HCV RNA test result <125 IU/mL after a prior RNA test of ≥125 IU/mL.

Additional covariates were considered based on known associations with HCV treatment uptake and were primarily assessed in semi-annual surveys. Sociodemographic characteristics included sex, race, age, education level, and homelessness status. A participant was considered homeless if they self-reported being displaced for at least one night. Additional variables captured insurance restrictions (e.g., fibrosis score, type of insurance, and recent drug use), services associated with improved treatment uptake (e.g., general outpatient medical visits, HIV specialty care [represented by undetectable HIV RNA], prescription of medication for opioid use disorder) and medical comorbidities, all of which had been previously associated with treatment uptake (Barua et al., 2015; Canary et al., 2015; Crespo et al., 2015; Falade-Nwulia et al., 2019; Harris and Rhodes, 2013; Lin et al., 2017; Marcus et al., 2018; Mehta et al., 2007, 2005; Norton et al., 2017; Schaeffer and Khalili, 2015; Spradling et al., 2018; Sylvestre et al., 2005; Wong et al., 2018).

2.5. Statistical analysis

We compared participants who had been treated at any time during follow-up or treated prior to enrollment to those who had not been treated using Chi-square or Fisher’s exact test for categorical variables and Kruskal-Wallis test for continuous variables. To evaluate temporal changes in treatment uptake and viremia, among the 1,130 with chronic infection, we calculated the cumulative proportion of participants treated per year based on self-report through February 2020. Once a participant was treated, they were considered as treated in all subsequent years. In this analysis, we included the 91 individuals who reported treatment prior to entering the study; they were considered treated beginning with their initial visit. We characterized the prevalence of viremia in each year among those who had viral load testing available in that calendar year. This also included persons who had been treated by their first visit and could have already achieved sustained virologic response.

Annual treatment rates were calculated per 1000 person-years of follow-up assuming participants were treated at the midpoint between the first visit where treatment was reported and the prior visit where treatment was not reported. If a participant had a visit in January or February, they were considered treated in the previous calendar year. Because the exact month/year of treatment could not be determined in the 91 individuals who reported treatment at their first visit, they were excluded from annual treatment rate calculations.

Subsequent analyses were restricted to the years where data was complete (January 2014 – December 2019). To evaluate how characteristics of those treated for HCV changed over time, we compared sociodemographic, behavioral and clinical characteristics of individuals treated early in the availability of DAAs (January 2014 – December 2016) when insurance companies were most restrictive to the later DAA era when insurance restrictions were sequentially relaxed (January 2017 – December 2019).

To identify factors associated with treatment uptake in each of the two time periods, we used Poisson regression (again excluding the 91 in whom date of treatment could not be determined). Variables considered for adjustment included sociodemographic characteristics, health-related variables, and drug use practices. Because health care utilization could be a marker for hepatitis C treatment engagement (rather than a predictor), we constructed models with (Model 2) and without (Model 1) this variable. These variables were considered based on a priori knowledge of factors associated with HCV treatment uptake or which had p-values <0.1 in the univariable analysis. All analyses were repeated for clearance of HCV viremia. For this analysis we excluded 9 persons who reported DAA-based treatment at their first visit but already had an undetectable HCV RNA leaving 1,121 for analysis. For this analysis, because HCV RNA was measured only annually in ALIVE, each measurement was carried forward until the next one was obtained. Sensitivity analyses examined temporal trends and correlates of treatment uptake in the most recently recruited ALIVE cohort (2015-2018) since they had significantly less follow-up time.

3. RESULTS

3.1. Characteristics of study population

Characteristics of the 1,130 participants included in the study are presented in Table 1. Overall, the median age was 55 years (IQR: 51-60), 71% (n=799) were male, and 76% (n=863) were Black. Over follow-up, 44% (n=502) reported receiving any treatment for HCV, with 8% (n=91) treated prior to entry into the study and 36% (n=411) reporting treatment at some time during follow-up. Of the 91 persons treated prior to entry, 82 (90.1%) had evidence of cure and of the 411 treated during follow up, 348 (84.7%) had evidence of cure.

Table 1.

Characteristics of 1,130 HCV-antibody positive participants by self-reported HCV treatment status anytime from 2014-2020

Never treated for
HCV		 Treated during
follow-up		 Treated prior to
analysis		 Total cohort p-
value
N 628 411 91 1130
Demographic Characteristics
Age (year), median (IQR) 54.2 (48.5, 58.9) 55.8 (51.9, 60.0) 59.3 (55.5, 62.7) 51.8 (47.0, 58.5)
Female sex 203 (32.3%) 104 (25.3%) 24 (26.4%) 331 (29.3%) 0.04
Black race 435 (69.3%) 357 (86.9%) 71 (78.0%) 863 (76.4%) <0.01
Education level ≥high school diploma 271 (43.4%) 197 (47.9%) 41 (45.1%) 509 (45.2%) 0.35
Substance Use
Frequency of injection drug use†δ
 None 249 (72.6%) 252 (75.7%) 18 (75.0%) 519 (74.1%) 0.81
 Less than daily 47 (13.7%) 42 (12.6%) 2 (8.3%) 91 (13.0%)
 Daily 47 (13.7%) 39 (11.7%) 4 (16.7%) 90 (12.9%)
Any non-injection drug use†§ 113 (32.8%) 91 (27.1%) 8 (33.3%) 212 (30.1%) 0.26
Marijuana use†§ 47 (13.6%) 42 (12.5%) 1 (4.2%) 90 (12.8%) 0.40
Alcohol use#
 None 167 (48.3%) 159 (47.3%) 16 (66.7%) 342 (48.4%) 0.09
 Harmful/hazardous use 85 (24.6%) 103 (30.7%) 3 (12.5%) 191 (27.1%)
 Dependence 94 (27.2%) 74 (22.0%) 5 (20.8%) 173 (24.5%)
Co-Morbidities and Healthcare Utilization
Type of health insurance† §
 Medicaid 221 (64.4%) 214 (63.5%) 15 (62.5%) 450 (63.9%) 0.59
 Other insurance 106 (30.9%) 113 (33.5%) 9 (37.5%) 228 (32.4%)
 Uninsured 16 (4.7%) 10 (3.0%) 0 (0.0%) 26 (3.7%)
At least one outpatient visit† # 247 (71.6%) 280 (83.1%) 23 (95.8%) 550 (77.9%) <0.01
HIV status/HIV viral suppression## §
 HCV mono-infected 240 (69.4%) 196 (58.3%) 8 (36.4%) 444 (63.1%) <0.01
 Coinfected & undetectable HIV 41 (11.9%) 24 (7.1%) 2 (9.1%) 67 (9.5%)
 Coinfected & detectable HIV 65 (18.8%) 116 (34.5%) 12 (54.6%) 193 (27.4%)
Fibrosis score†† #
 None or mild fibrosis 129 (37.3%) 138 (41.1%) 8 (33.3%) 275 (39.0%) 0.69
 Significant fibrosis 49 (14.2%) 48 (14.3%) 2 (8.3%) 99 (14.0%)
 Cirrhosis 37 (10.7%) 41 (12.2%) 3 (12.5%) 81 (11.5%)
Year of Recruitment into the Study
1988-89 113 (18.0%) 149 (36.3%) 11 (12.1%) 273 (24.2%) <0.01
1994-2000 71 (11.3%) 64 (15.6%) 3 (3.3%) 138 (12.2%)
2005-2008 158 (25.2%) 123 (29.9%) 10 (11.0%) 291 (25.8%)
2015-2018 286 (45.5% 75 (18.3%) 67 (73.6%) 428 (37.9%)
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†

Reflective of 6 months prior to study visit

δ

430 people were missing data

§

426 people were missing data

#

424 people were missing data

##

Viral suppression is defined as ≤400 copies per mL

††

None or mild fibrosis defined as <8 kPa, significant fibrosis defined as 8-12.3 kPa, cirrhosis defined as ≥12.3 kPa

Compared to those who were not treated, those who were treated (whether during follow-up or prior to) were younger, and more likely to be female, co-infected with HIV, and have had an outpatient visit in the prior 6 months. Those treated were also significantly less likely to use drugs and inject daily and less likely to be on Medicaid.

Characteristics of the 399 participants who were treated from January 2014 – December 2019 are presented in Table 2, stratified by treatment era. Of those treated, 50.6% were treated in the early DAA-era, and 49.4% in the late DAA-era. Those treated in the late DAA-era were more likely to be white and use and inject drugs. They were also significantly less likely to be co-infected with HIV and have severe fibrosis/cirrhosis.

Table 2.

Characteristics of 399 participants with chronic HCV infection who self-reported HCV treatment in the early and late DAA eras

DAA Era with Strict Restrictions
(2014-2016)		 Later Availability of DAAs
(2017-2019)		 p-value
N 202 197
Demographic Characteristics
Age (year), median (IQR) 58.7 (54.5, 62.7) 57.1 (51.6, 62.1)
Female sex 49 (24.3%) 53 (26.9%) 0.54
Black race 193 (95.5%) 154 (78.2%) <0.01
Education level ≥high school diploma 95 (47.0%) 96 (48.7%) 0.73
Substance Use
Frequency of injection drug use 0.02
 None 167 (82.7%) 139 (70.6%)
 Less than daily 20 (9.9%) 36 (18.3%)
 Daily 15 (7.4%) 22 (11.2%)
Any non-injection drug use† 40 (19.8%) 82 (41.6%) <0.01
Marijuana use† 23 (11.4%) 34 (17.3%) 0.09
Alcohol use
 None 124 (61.4%) 101 (51.3%) 0.12
 Harmful/hazardous use 44 (21.8%) 56 (28.4%)
 Dependence 34 (16.8%) 40 (20.3%)
Co-Morbidities and Healthcare Utilization
Type of health insurance†
 Medicaid 152 (75.3%) 162 (82.2%) 0.16
 Other insurance 48 (23.8%) 32 (16.2%)
 Uninsured 2 (1.0%) 3 (1.5%)
At least one outpatient visit† 183 (90.6%) 176 (89.3%) 0.68
HIV status/HIV viral Suppression# <0.01
 HCV mono-infected 102 (50.5%) 139 (70.6%)
 Coinfected & undetectable HIV 14 (6.9%) 8 (4.1%)
 Coinfected & detectable HIV 86 (42.6%) 50 (25.4%)
Fibrosis score†† §
 None or mild fibrosis 41 (20.3%) 97 (49.2%) <0.01
 Significant fibrosis 21 (10.4%) 21 (10.7%)
 Cirrhosis 22 (10.9%) 18 (9.1%)
Year of recruitment into the study <0.01
 1988-89 91 (45.1%) 53 (26.9%)
 1994-2000 36 (17.8%) 26 (13.2%)
 2005-2008 64 (31.7%) 58 (29.4%)
 2015-2018 11 (5.5%) 60 (30.5%)
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†

Reflective of 6 months prior to study visit

#

Viral suppression is defined as ≤400 copies per mL

††

None or mild fibrosis defined as <8 kPa, significant fibrosis defined as 8-12.3 kPa, cirrhosis defined as ≥12.3 kPa

§

Percentages to not add up to 100% because 179 people were missing data

Among the 1130, 898 (79.5%) had more than 1 HCV RNA test and 232 (20.5%) had only 1. Those with only 1 assessment were younger, more often White, more recently recruited to the cohort, and endorsed injecting drugs more frequently than those who had 2 or more HCV RNA tests. No significant differences were detected in sex, HIV status, or source of medical insurance (data not shown).

3.2. Temporal trends in HCV treatment uptake and viral clearance

HCV treatment uptake increased substantially from 4% in 2014 to 59% in 2019 and 68% in 2020. (Figure 1). Over this same period, the proportion with HCV viremia declined from 99% in 2014 to 44% in 2019 and 33% in 2020 (p<0.001). Among those who were treatment-naïve at study entry, treatment uptake increased substantially from 1.4 per 100 person years in 2014 to a peak of 16.4 per 100 person-years in 2016 and then was maintained at 5 – 9 per 100 person-years through February 2020 (Figure 2).

Figure 1.

Figure 1.

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Cumulative HCV treatment uptake and HCV viremia among people who inject drugs in Baltimore, MD, 2014 – 2020. Note that viremia at any one point reflects spontaneous clearance (without treatment) as well as reinfection, treatment uptake and success. Thus, absolute sums are not as informative as trends.

Figure 2.

Figure 2.

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Annual rate of HCV treatment uptake among people who inject drugs in Baltimore, MD, 2014 – 2020

3.3. Correlates of HCV treatment uptake and viral clearance

Correlates of HCV treatment uptake by time-period are presented in Table 3. In the early DAA period, older age (IRR: 1.37, 95% CI: 1.25, 1.50), Black race (IRR: 3.45, 95% CI: 1.62, 7.32), having a recent outpatient visit (IRR: 2.51, 95% CI: 1.56, 4.04), HIV coinfection with undetectable viral load (IRR: 2.28, 95% CI: 1.78, 2.93), and cirrhosis (IRR: 1.69, 95% CI: 1.01, 2.82) were associated with significantly increased treatment uptake. Female sex, recent homelessness, active injection drug use, non-injection drug use, and alcohol use were significantly associated with lower treatment uptake. In multivariable analysis (Model 1), age (IRR: 1.28, 95% CI: 1.15, 1.42), educational attainment (IRR: 1.31, 95% CI: 1.04, 1.66), and HIV/HCV coinfection with an undetectable HIV viral load (IRR: 2.08, 95% CI: 1.63, 2.66) remained significantly associated with higher treatment uptake. Alcohol dependence was significantly associated with lower treatment uptake (IRR: 0.63, 95% CI: 0.43, 0.91).

Table 3.

Correlates of HCV treatment uptake by HCV treatment time-period among ALIVE participants, Baltimore MD, 2014-2019

DAA Era with Strict Restrictions (2014-
2016)		 Later Availability of DAAs (2017-2019)
Characteristic Unadjusted
IRR (95%
CI)		 Adjusted
IRR (95%
CI) Model 1		 Adjusted
IRR (95%
CI) Model 2		 Unadjusted
IRR (95%
CI)		 Adjusted
IRR (95%
CI) Model 1		 Adjusted
IRR (95%
CI) Model 2
Age (per 5 years) 1.37 (1.25, 1.50) 1.28 (1.15, 1.42) 1.26 (1.13, 1.40) 1.08 (0.98, 1.17) 1.02 (0.92, 1.14) 1.00 (0.90, 1.11)
Sex
 Male REF REF REF REF REF REF
 Female 0.73 (0.54, 0.98) 0.82 (0.61, 1.10) 0.78 (0.58, 1.06) 0.90 (0.64, 1.25) 0.94 (0.68, 1.31) 0.93 (0.67, 1.29)
Race
 Non-Black REF REF REF REF REF REF
 Black 3.45 (1.62, 7.32) 1.62 (0.76, 3.45) 1.63 (0.76, 3.50) 1.07 (0.75, 1.54) 0.83 (0.52, 1.33) 0.83 (0.52, 1.32)
Educational attainment
 < high school diploma REF REF REF REF REF REF
 ≥ high school diploma 1.21 (0.93, 1.56) 1.31 (1.04, 1.66) 1.29 (1.02, 1.64) 1.07 (0.77, 1.47) 1.11 (0.82, 1.51) 1.06 (0.78, 1.45)
Homeless
 No REF REF REF REF REF REF
 Yes 0.34 (0.15, 0.75) 0.53 (0.25, 1.12) 0.52 (0.24, 1.11) 0.52 (0.31, 0.88) 0.67 (0.41, 1.11) 0.75 (0.45, 1.24)
Outpatient visit in past 6 months
 No REF REF REF REF
 Yes 2.51 (1.56, 4.04) 1.88 (1.15, 3.09) 3.04 (1.86, 4.96) 2.69 (1.64, 4.39)
HIV status
 HCV mono-infected REF REF REF REF REF REF
 Coinfected & undetectable 2.28 (1.78, 2.93) 2.08 (1.63, 2.66) 1.93 (1.50, 2.48) 1.33 (0.89, 1.99) 1.29 (0.88, 1.88) 1.15 (0.78, 1.69)
 Coinfected & detectable 0.87 (0.48, 1.58) 1.32 (0.76, 2.29) 1.24 (0.71, 2.19) 0.36 (0.17, 0.78) 0.46 (0.23, 0.95) 0.47 (0.23, 0.94)
Frequency of injection drug use
 None REF REF REF REF REF REF
 Less than daily 0.59 (0.37, 0.95) 0.79 (0.50, 1.25) 0.81 (0.52, 1.28) 0.65 (0.41, 1.03) 0.74 (0.45, 1.20) 0.75 (0.45, 1.24)
 Daily 0.43 (0.24, 0.75) 0.71 (0.41, 1.20) 0.73 (0.43, 1.25) 0.39 (0.23, 0.65) 0.46 (0.27, 0.79) 0.48 (0.28, 0.83)
Any non-injection drug use†
 No REF REF
 Yes 0.51 (0.36, 0.72) 0.61 (0.44, 0.84)
Marijuana use
 No REF REF
 Yes 0.78 (0.51, 1.21) 0.92 (0.60, 1.42)
Liver fibrosis
 None or Mild Fibrosis REF REF REF REF REF REF
 Significant Fibrosis 1.05 (0.60, 1.82) 0.92 (0.52, 1.61) 0.90 (0.51, 1.58) 0.68 (0.40, 1.16) 0.72 (0.44, 1.18) 0.69 (0.42, 1.14)
 Cirrhosis 1.69 (1.01, 2.82) 1.56 (0.95, 2.55) 1.56 (0.96, 2.54) 0.73 (0.40, 1.35) 0.73 (0.40, 1.34) 0.65 (0.35,1.21)
Audit for alcohol use
 None REF REF REF REF REF REF
 Harmful/hazardous use 0.71 (0.51, 0.98) 0.72 (0.52, 1.00) 0.72 (0.52, 1.00) 0.89 (0.61, 1.31) 1.01 (0.69, 1.48) 1.03 (0.70, 1.51)
 Dependence 0.50 (0.34, 0.74) 0.63 (0.43, 0.91) 0.64 (0.44, 0.93) 0.63 (0.41, 0.96) 0.75 (0.50, 1.13) 0.77 (0.50, 1.17)
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†

Excludes marijuana use

In the later DAA period, in univariable analysis, having an outpatient visit 6-12 months before reporting HCV treatment (IRR: 3.04, 95% CI: 1.86, 4.96) was associated with greater treatment uptake while recent homelessness (IRR: 0.52, 95% CI: 0.31, 0.88), HIV coinfection with a detectable HIV viral load (IRR: 0.36, 95% CI: 0.17, 0.78), injecting drugs daily (IRR vs. no injection: 0.39, 95% CI: 0.23, 0.65), non-injection drug use (IRR: 0.61, 95% CI: 0.44, 0.84), and alcohol dependence (IRR vs. no alcohol use: 0.63, 95% CI: 0.41, 0.96) were all significantly associated with lower HCV treatment uptake. In multivariable analysis (Model 1), the association between treatment uptake and HIV coinfection with a detectable viral load (IRR: 0.46, 95% CI: 0.23, 0.95) and daily injection drug use (IRR: 0.46, 95% CI: 0.27, 0.79) remained statistically significant, but the associations with recent homelessness and alcohol dependence were no longer statistically significant. For both time periods, results were qualitatively similar when adjusting for recent engagement in outpatient care (Model 2).

Results were also similar in models evaluating correlates of HCV RNA clearance (Supplemental Table 1), with a few differences. Female sex, Black race, cirrhosis, and educational attainment were not significantly associated with clearance. In the early DAA era, marijuana use was associated with lower likelihood of clearance (IRR: 0.44, 95% CI: 0.23, 0.84). After adjustment for demographics, less-than-daily active injection drug use was also associated with lower clearance (IRR vs. no use: 0.36, 95% CI: 0.16, 0.78). In the late DAA era, age was associated with higher likelihood of clearance (IRR: 1.13, 1.02, 1.24). Less-than-daily active injection drug use (IRR: 0.57, 95% CI: 0.35, 0.92) and harmful/hazardous alcohol use (IRR: 0.65, 95% CI: 0.43, 0.96) were associated with lower clearance. After adjustment for demographics, recent homelessness (IRR: 0.51, 95% CI: 0.30, 0.88) and alcohol dependence (IRR: 0.62, 95% CI: 0.43, 0.89) were associated with lower likelihood of clearance. In sensitivity analyses, associations with treatment uptake and clearance were qualitatively consistent in the ALIVE cohort recruited in 2015-2018 (Supplemental Table 2).

4. DISCUSSION

In this cohort of PWID, HCV treatment uptake improved dramatically from 4% at the beginning of the DAA era to more than 60% nearly 5 years after the availability of DAAs. Increased treatment uptake resulted in a marked decline in the prevalence of HCV viremia, from 99% in 2014 to 44% in 2019. This is remarkable as for nearly two decades, treatment uptake never exceeded 5% in this community-based cohort despite a growing burden of cirrhosis (Mehta et al., 2007). These increases were consistent across multiple cohorts representing PWID recruited as far back as 1988 to as recently as 2018, suggesting that these increases may represent the broader Baltimore community of PWID. Those who were treated soon after DAAs became available were more likely to be older, more educated, and living with HIV and suppressed on antiretroviral therapy, but these factors became less important over time. While persons with ongoing substance use and IDU were more likely to be treated in the later years of DAA availability, active substance use and associated factors (e.g., homelessness) remained barriers to treatment uptake in recent years.

The trends we observed are similar to those observed in other settings, reflecting the incredible effectiveness of DAA-based therapies, as well as the impact of removal of treatment restrictions, such as fibrosis severity and abstinence requirements from insurance restrictions (Bartlett et al., 2019; Barua et al., 2015; Chhatwal et al., 2019; Mirzazadeh et al., 2021; NVHR and CHLPI, 2020, 2017). HCV is a slowly progressing, largely asymptomatic, disease that takes 25-30 years to cause cirrhosis, the most severe stage of fibrosis, in approximately 30% of infected individuals (Lingala and Ghany, 2015). This cohort of current and former PWID had a median age of 58 years at the time when DAAs first became available, the decade of life where complications are increasingly likely to occur. It is not surprising that in the early years of DAA availability, those with the highest risk of progression (e.g., older age, HIV co-infection) were more likely to be treated. It is further encouraging that in the later DAA period, significantly more individuals with mild fibrosis were treated. Indeed, the percentage of those treated who had mild or no fibrosis more than doubled, from 20% to 49% between the early and late DAA eras, respectively. This finding suggests that disease stage is less of a barrier to treatment today, compared to during the early availability of DAAs.

There are several potential implications of expanded treatment. The most immediate is a reduction in HCV morbidity and mortality, and there are already data from this cohort suggesting that benefit (Cepeda et al., 2022). In addition, expansion of treatment among PWID may reduce incidence, as was shown men who have sex with men living with HIV (Braun et al., 2021) and modeled for PWID with HCV (Fraser et al., 2018).

To achieve HCV elimination among PWID, it is critical that strategies to increase treatment uptake focus on those who have not yet accessed treatment. While over time, people with ongoing substance use represented a larger percentage of those receiving treatment, it was also the case that daily IDU was associated with significantly lower treatment uptake in the late DAA era. While this signals overall improvements in treatment accessibility and acceptability for people who use substances, it also highlights that additional strategies may be needed to support PWID. Poor treatment uptake among actively injecting PWID could be due to a combination of patient and provider barriers. For example, stigmatizing attitudes towards active drug use could remain a persistent barrier to provider willingness to treat HCV among active PWID who are motivated to be treated (Asher et al., 2016; Morrill et al., 2005; Rogal et al., 2017; Zhang et al., 2020). HCV treatment may also remain a lower priority when a person is actively injecting drugs with high frequency or who experience other challenges such as housing instability (Mehta et al., 2005). While homelessness was not significantly associated with reduced treatment uptake in adjusted analyses, it was associated with a lower likelihood of viral clearance in both eras highlighting potential impacts of housing instability on treatment uptake optimal adherence and prevention of reinfection.

While we were unable to tease out the specific reasons that people remain untreated in this study, our findings highlight a need for targeted strategies including continued efforts to address stigma, providing treatment in flexible venues such as through mobile health vans, syringe services programs, or opioid treatment programs, and co-location of treatment with other services like housing assistance or other harm reduction services for PWID (Assoumou et al., 2021; Guerra-Veloz et al., 2023; Kapadia et al., 2023; Talal et al., 2023; Winetsky et al., 2020). The potential value of integration of harm reduction and infectious diseases testing and treatment has been recently underscored by the National Academies (National Academies of Sciences, 2020). In addition, novel strategies like provision of long-acting formulations of DAA HCV treatments should be considered particularly for those with inconsistent health care access.

Several limitations should be noted. Selection bias is always a concern in longitudinal studies. Those retained in the study may generally be healthier and more stable than those lost to follow-up, which could overestimate HCV treatment uptake. However, sensitivity analyses support that covariate associations were comparable across recruitment cohorts, including those recently recruited from the community and among cohorts with different follow-up rates and demographic characteristics. Second, other than HCV clearance, HIV status, and liver fibrosis, other variables, including the primary outcome, HCV treatment, are based on self-report. Though self-reported HCV treatment might not capture data on reinfection or even unsuccessful treatment initiation without completion, examining HCV clearance as a secondary outcome produced similar results that validated the findings from self-reported treatment. The factors associated with treatment uptake are also imprecise and intercorrelated. For example, homelessness can fail to capture a wide spectrum of housing instability and may differ by setting. Finally, Maryland relaxed its Medicaid’s fibrosis restriction in 2019, so we anticipated treatment to have improved even more. However, due to the well-recognized impact of COVID-19 on service access for PWID including HCV screening and treatment (Hoenigl et al., 2022; Levengood et al., 2022), we restricted our analysis to early 2020 and so were unable to evaluate the impact of this modification.

In conclusion, half of this population of current and former PWID had been treated for HCV by early 2020, resulting in a greater than 50% reduction of HCV viremia prevalence. Despite these improvements in treatment uptake, several characteristics remained associated with not being treated, including daily drug injection. HCV elimination goals are unachievable without addressing the needs of PWID. Our work highlights the need for future studies that test flexible and creative treatment delivery interventions in non-stigmatizing environments.

Supplementary Material

1

Highlights.

  • HCV treatment uptake in a cohort of PWID in Baltimore increased from 2014-2020

  • As a result of increased HCV treatment uptake, population HCV viremia declined

  • Additional support needed for the most marginalized PWID to achieve elimination

Funding:

This work was supported by the National Institutes of Health grant numbers T32-DA-007292, F31-DA-049613, U01-DA-036297, R01-DA-048063, K23-DA-041294 and K24-AI-118591, T32-AI-102623, P30-AI-094189.

Footnotes

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Conflict of Interest

DT: medical editing for UpToDate; scientific advisor to Excision Bio, Evrys Bio, and Merck. OFN research grants from Abbvie paid to institution; scientific consulting for Gilead. SM: materials support from Abbott. Other authors: no conflict declared.

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