This prospective real-world study adds nuance to the literature around the challenges of (a) maintaining people on HCV treatment and (b) confirming cure after treatment completion in an SSP setting.
We observed significantly higher intention-to-treat SVR12 rates in those receiving treatment in the MOUD (96%) versus SSP setting (60%). These differences were driven mostly by nonadherence to SVR12 lab visits, as the per protocol SVR12 rate was more similar at 100% vs 88%, respectively, though this remained statistically significant (P = 0.01). Adherence was generally good in both arms, though higher treatment discontinuation rates were seen in the SSP arm. Treatment was generally well tolerated with mild side effects, none of which led to treatment discontinuation. The community standard academic hepatology group was comparatively older, with more socioeconomic stability, achieving a similar SVR12 rate to the MOUD group.
The MOUD group performed similarly to average cure rates in real world studies among people who use drugs, (
16-
18) while the ITT cure rates were slightly lower in the SSP group than average rates reported in the meta-analysis by Hajarizadeh et al. (
9). The lower ITT SVR12 rate in the SSP group likely reflects multiple factors. We financially incentivized study enrollment but intentionally did not incentivize engagement with study visits, medication pickups, or SVR12 lab results. The SSP group also had a higher rate of homelessness and other factors previously associated with lower SVR12 rates, especially in ITT analysis, driven by completion of lab results (
18-
20). Our data did not show homelessness to be negatively associated with SVR12, though it was inadequately powered for this association and other data our group has published has found lower SVR12 completion among homeless individuals (
21). For many PWID, especially those who experience homelessness, personal cost-benefit analysis of completing lab work after finishing a medication with high chances of cure are seen by some participants to be less favorable than more immediate concerns (
22). People who use opioids must often prioritize procuring opioids to avoid withdrawal. This need may be less pronounced for those on MOUD, which prevents opioid withdrawal. The disproportionate number of people actively using opioids in the SSP group may have affected these participants’ willingness to complete study labs, and the lack of telephone access may have contributed to less SVR12 lab completion in the SSP group. In addition, real-world, non-incentivized studies have been shown to have lower SVR12 lab completion rates than financially incentivized prospective clinical trials among PWID (
9). Implementing financial incentives to routine HCV treatment in this population may improve engagement and lab completion.
It should be noted that while low adherence was associated with low ITT SVR12 rates, treatment discontinuation was most strongly associated with lower ITT SVR12. The actual cure rate is difficult to assess in the SSP group given the substantial portion who did not return for SVR12 lab results. While interesting that our study showed lack of MOUD and low adherence to be negatively associated with SVR12, the degree to which the SSP participants did not complete SVR12 labs demonstrates mostly the willingness to complete labs as opposed to rate of cure. This may in part explain why our results differ from those of other larger, better funded studies, such as PREVAIL and SIMPLIFY, which did not show significant impacts of substance use or adherence (
15,
23). These studies also employed electronic blister packs and were better suited to describe the relationship between adherence and cure.
Perhaps the most important finding from our study is found in a review of screening data (
Figure 1). Out of a total of 300 participants with chronic HCV screened, 250 were unable to make it to enrollment. A total of 82 were excluded by investigator driven constraints, such as inclusion criteria requiring low fibrosis status, or MOUD or active drug use. However, several factors related to the study drug E/G also contributed. Fifty three patients were excluded were due to inability to complete the high volume of lab work necessitated by this agent (notably genotype and NS5A resistance testing), 47 due to wrong genotype (exclusively genotype 3), and 8 due to RAVs inconsistent with the study drug. This reflects a total of 36% of the overall screened population. In a clinical environment the participants with genotype 3 HCV would often be offered other treatment options, but the high burden of lab testing would remain. Pan genotypic regimens, streamlining lab orders to limit volume, and non-phlebotomy confirmation tests such as dried blood spot may all lower barriers to treatment uptake in this population.
Our study had several important limitations. First, the two study groups were separated primarily by site of clinical engagement (MOUD and SSP settings), though there was crossover exposure to both MOUD and SSP engagement at both sites. While our data allow some comparisons of HCV treatment outcomes from these different clinical settings, our ability to assess the role of MOUD or SSP engagement on HCV treatment outcomes is limited. Additionally, the small sample size was powered sufficiently to detect a difference in the primary outcome between recruitment sites but not to detect meaningful differences in individual predictors of participants completing treatment or achieving SVR12.