Leitch, E. Carol McWilliam

McLauchlan, John

Nickbakhsh, Sema

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     Nickbakhsh, S., McLauchlan, J.  and Leitch, E. C. M. (2018) Evaluating “treatment as prevention” on the road to hepatitis C virus elimination. Annals of Blood, 3, 44. (doi:10.21037/aob.2018.10.05)  This is the author’s final accepted version.  There may be differences between this version and the published version. You are advised to consult the publisher’s version if you wish to cite from it.  http://eprints.gla.ac.uk/179970/                             Deposited on: 18 February 2019         Enlighten – Research publications by members of the University of Glasgow http://eprints.gla.ac.uk   1   Evaluating ‘treatment as prevention’ on the road to hepatitis C virus elimination 1 Sema Nickbakhsh, John McLauchlan and E. Carol McWilliam Leitch 2 MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK 3  4 *Corresponding Author. E. Carol McWilliam Leitch, MRC-University of Glasgow Centre for 5 Virus Research, University of Glasgow, Glasgow, UK. Email: carol.leitch@glasgow.ac.uk 6  7 Running Title: HCV “treatment as prevention” evaluation  8 2   Fraser and colleagues (1) have recently published the results of a study modelling the direct 9 acting antiviral (DAA) scale-up requirements needed to reduce hepatitis C virus (HCV) 10 infection in people who inject drugs (PWID) within selected European sites. Such “treatment 11 as prevention” strategies have been previously proposed to address the ambitious WHO 12 HCV elimination target for 2030 (2), established in response to the world-wide exponential 13 growth in HCV-associated liver disease which has occurred in the past few decades and is a 14 leading cause of increased liver-related mortality (3). Although a challenging proposal even 15 for resource-rich regions such as Europe, the WHO target is now deemed feasible with the 16 advent of DAA treatments which achieve sustained viral response (SVR) rates above 90% for 17 the most prevalent genotypes (4). As illustrated through the modelling of comparative 18 interventions, Fraser et al. (1) conclude that “treatment as prevention” is a viable strategy 19 for curtailing the future burden of disease. Although transmission of HCV occurs primarily 20 among PWID in most resource-rich countries, treatment recommendation guidelines have 21 historically excluded PWID because of concerns surrounding reinfection rates and 22 compliance to treatment regimens involving pegylated interferon which can have significant 23 side effects. However current European, AASLD/IDSA and WHO treatment guidelines 24 indicate a reversal in this position owing to the relative ease of treatment with DAAs and 25 evidence that high rates of SVR are achievable among this group (5, 6). The prioritisation of 26 PWID for treatment is recognised as a potentially effective strategy to significantly decrease 27 HCV incidence by not only reducing the prevalence of existing chronic cases of HCV infection 28 but additionally preventing new transmission events (7). However, the likely effectiveness 29 and long-term epidemiological impact of wider access to treatment alongside existing harm 30 reduction prevention strategies is not well understood.  31 3   In order to gain a more comprehensive understanding of the scale-up of DAA 32 treatment required to reduce HCV infection in PWID to minimal levels for 11 European  33 sites, Fraser et al. (1) have developed a deterministic mathematical model parameterised 34 using published data from each of the geographical sites . In addition to treatment status, 35 the model was stratified according to opioid substitution therapy (OST) and needle and 36 syringe programmes (NSPs) allowing for different infection rates among these groups. 37 Results suggest that treatment scale-up will be needed to reduce HCV prevalence in all but 38 three of the sites. Only modest reductions in prevalence are estimated to be achieved in 39 Belgium, Denmark, Hamburg, Norway and Scotland by doubling the current DAA treatment 40 rates and at least a fivefold increase in the current HCV treatment rates will be needed to 41 reduce HCV incidence to <2% by 2026. Due to the high prevalence of chronic HCV in Finland 42 and Sweden, treatment rates of 50/1000 PWID will be required to halve prevalence by 2026. 43 Increasing OST and NSP coverage to 80% whilst maintaining current treatment rates is 44 projected to reduce prevalence by at least 30% in all sites except Finland and Hamburg. 45 However, the relative benefit of PWID-targeted treatment allocation and traditional harm 46 reduction preventative measures was difficult to ascertain owing to uncertainty in highly 47 influential model parameters such as injection duration. Nevertheless, this study identifies 48 important knowledge gaps that must be confronted if optimal and realistic public health 49 policy decisions are to be determined and implemented. 50 Quantitative models play an increasingly important role in guiding public health 51 policy decisions, through improved understanding of infection transmission dynamics and 52 forecasting the impact of interventions on infection incidence and disease burden. Several 53 studies, employing methods such as deterministic mathematical modelling and stochastic 54 4   simulations, have evaluated the impact of varying treatment rates and PWID-targeted 55 allocation strategies on HCV infection prevalence and/or the burden of severe liver 56 morbidity (8-10). These studies have focused on generalised or single country settings. 57 However, the spread of HCV among PWID is known to occur across broad geographical 58 scales, with inter-country spread (11) and the potential for multiple independent virus 59 introduction events (12). Given variation in critical features of HCV epidemiology and 60 treatment delivery between geographically disperse regions, the impact of PWID-targeted 61 treatment is not expected to be uniform globally.  A concerted transboundary effort, with 62 treatment interventions appraised at both local and international scales, will be essential on 63 the road to global HCV elimination.   64 Broad-scale deterministic models, such as those used by Fraser et al (1), provide a 65 flexible framework for comparing general scenarios for multiple regions in the face of sparse 66 data. However, these models are not designed for accurate predictions which require a high 67 degree of confidence in empirically-driven model assumptions. Additional sources of 68 epidemiological variation compounds accurate predictions of treatment impact by country.  69 Firstly, the geographical distribution of HCV genotypes and subtypes is known to 70 vary within and between continents, with large-scale movement of HCV among PWID 71 recognised within Europe (11,13). Consequently, the relative rollout of different DAA 72 therapy combinations and treatment durations could vary geographically. Furthermore, 73 despite the advent of second-generation DAAs with pan-genotypic action, clinical trials have 74 shown drug efficacy can vary between HCV genotypes and subtypes (4). However, extensive 75 observational data accrued through long-term routine clinical usage is needed to fully 76 elucidate the genotype-specific effectiveness of DAAs in the real-world setting. The 77 5   temporal and spatial dynamics of HCV transmission and associated treatment practices 78 must therefore be borne in mind to ensure predictive models of treatment impacts are 79 timely, relevant, and of public health utility.  80 Secondly, deterministic mathematical models in this context make the unrealistic 81 assumption of random contact patterns among PWID. The sharing of needles and syringes 82 are the major empirically supported source of exposure for this group (14). The network of 83 contacts among PWID via this route is characterised by a non-homogeneous pattern, with 84 transmission events being more likely among affiliates of certain subpopulations. For 85 example, several studies utilising virus sequences have found a high degree of phylogenetic 86 clustering of HCV infections, and these clusters have discernible shared biological 87 characteristics such as recent seroconversion or HIV co-infection (15). The genetic clustering 88 of HCV among HIV co-infected PWID is particularly significant considering the higher HCV 89 RNA levels associated with HIV co-infection (16), suggesting a greater chance of 90 transmission from these individuals. Indeed, a modelling study investigating the targeting of 91 treatment at HIV/HCV co-infected individuals has shown this to be an effective strategy in 92 reducing transmission (17).  93 Social components of HCV transmission among PWID have also been studied and 94 highlight the potential for particularly prominent individuals that may act as infection ‘super 95 spreaders’ (18). Another important component of PWID networks is incarceration, which 96 presents an independent and high risk environment for the generation of new HCV 97 infections as well as the increased chance of re-infection (19). Phylogeographic studies have 98 also revealed a highly localised spatial clustering component to HCV transmission providing 99 further insights into potential demographic, social, or economically-driven transmission 100 6   hotspots which could be exploited for targeting treatment interventions (12). As well as 101 social network features suggestive of heightened transmission risk, other behavioural 102 factors may provide protective outcomes. For example, community-based surveillance has 103 identified acts of “serosorting”, whereby HCV positive persons preferentially share injection 104 equipment with others of known HCV positive status (20). Such behaviours may limit the 105 occurrence of transmission among PWID networks. Further studies incorporating non-106 random contact structures [see (21) for an example of an individual-based stochastic 107 modelling of HCV transmission among PWID] may improve the utility of models evaluating 108 “treatment as prevention”.  109 Whilst DAA treatment is likely to greatly reduce the prevalence of HCV in the PWID 110 population, resistance-associated substitutions (RAS) can emerge in individuals who do not 111 attain an SVR. A single mutation is frequently sufficient to induce antiviral resistance in 112 some DAAs that have a low barrier to resistance and, although HCV strains containing RAS 113 tend to be less robust than their wild type counterparts, the evolution of compensatory 114 mutations can improve fitness to wild type levels. To prevent the emergence of resistance, 115 DAAs are generally given as a combination therapy consisting of two or more drugs. Despite 116 this however resistant strains do occur in a small number of individuals. If treatment for 117 actively injecting PWID is implemented, it is possible that HCV strains with established RAS 118 from the small number of individuals failing treatment will be transmitted to others, setting 119 the stage for infection and re-infection of the PWID population with drug-resistant strains 120 through the sharing of injecting equipment. Infection with HCV strains that carry RAS need 121 not be dependent on the emergence and transmission of HCV strains with compensatory 122 mutations; it is recognised that transmitted antiretroviral resistance associated with low 123 7   fitness HIV variants occurs, albeit at a reduced transmission frequency compared to wild 124 type HIV (22). In addition to RAS emergence, there are genotypes and sub-genotypes that 125 display an inherent resistance to certain DAAs, such as HCV subtypes gt1l, gt4r and subtypes 126 of gt3 (23,24). These subtypes are not widely distributed across PWID populations in Europe 127 but a marked reduction in the frequency of the predominant sub-genotypes could create a 128 niche suitable for the expansion of alternative strains which are unable to out-compete 129 current dominant strains either due to replication and transmission fitness or through 130 geographical restrictions. In the advent of universal DAA treatment for actively injecting 131 individuals it will be of the utmost importance to ensure strategies to monitor and limit the 132 emergence of antiviral resistant HCV strains are firmly in place.  133 Although many important challenges remain, such as the delivery of treatment to 134 marginalised groups including PWID and the potential for the emergence and spread of RAS, 135 the targeting of treatment to people at high risk of transmitting HCV will likely be key to the 136 successful global elimination of HCV as a public health concern. Given geographical 137 variability in genotype distribution and the role of social and spatial networks in the spread 138 of HCV, consideration of PWID networks and transmission hotspots may prove imperative in 139 the design of optimal treatment allocation strategies and the monitoring of emergent 140 strains carrying RAS. The incorporation of contact structure is a prudent aim for future 141 modelling exercises, for accurate, context-specific, predictions of the impact of different 142 treatment rates and allocation strategies (see Figure). Ultimately, model effectiveness will 143 remain difficult in the absence of good quality data and improved health monitoring 144 infrastructure in some settings; ongoing surveillance of PWID populations will be critical in 145 this endeavour (25). 146 8   References 147 1. Fraser H, Martin NK, Brummer-Korvenkontio H, et al. 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Curr Opin Infect Dis 2015;28:576-82. 212  213  214   215 11   Figure legend 216 Integrating social network and epidemiological data in future modelling exercises evaluating 217 “treatment as prevention” will be a prudent aim to ensure model predictions are accurate, 218 timely and of public health utility. 219  220 

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Evaluating “treatment as prevention” on the road to hepatitis C virus elimination

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Evaluating “treatment as prevention” on the road to hepatitis C virus elimination

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