Forecasting Hepatitis C liver disease burden on real-life data. Does the hidden iceberg matter to reach the elimination goals?

1 INTRODUCTION

Hepatitis C virus (HCV) is a leading cause of liver-related morbidity and mortality worldwide. An estimated 71 million people are affected by chronic hepatitis C (CHC) infection1 and a significant number of those chronically infected progress to cirrhosis or liver cancer if left untreated.2, 3 However, the development of direct-acting antiviral (DAA) therapy has revolutionized the approach to treatment and reinvigorated public health initiatives aimed at identifying patients with CHC. Galvanized by these results, the World Health Organization (WHO) foresees the elimination of HCV infection by 2030 through achieving the Global Health Sector Strategy Goals (GHSS) for Hepatitis.4 While targeted screening programmes for high-risk populations such as injection drug users are necessary for elimination of Hepatitis C,5, 6 little has been done to understand what increases in diagnosis and treatment are necessary in the general population of high endemic countries for achieving these goals. Given that the use of DAAs regardless of fibrosis stage is cost-effective,7 it is crucial that health policies expand treatment access for all HCV-infected individuals. The goal of this study was to use a new modelling approach, grounded in real-life cohort data of diagnosed and treated patients, to compare different linkage to care scenarios to the overall HCV-infected population in Italy. We aimed to evaluate the possible impact of only linked-to-care individuals on overall HCV burden and to identify a possible strategy to achieve the WHO targets by 2030.

2 METHODS

3 RESULTS

3.1 Base 2016 (Italy Polaris Model)

There were an estimated 849 000 (95% UI: 371 000-1 240 000) infected individuals in 2015. The forecasted impact of each scenario on total number of viraemic infections, HCV liver-related morbidity and mortality were compared through 2030 (Figures 1 and 2). Given the relatively large number of patients treated in Italy, total infections are expected to decline to 288 000 (95% UI: 71 880-424 640), or 65%, by 2030. DC cases are forecasted to decrease 75% from 22 900 (95% UI: 4300-46 700) in 2015 to 6100 (95% UI: 100-15 300) in 2030 (Figure 2). HCC cases are also expected to decline from 14 000 (95% UI: 3300-35 100) to 3800 (95% UI: 60-12 500) by the same year. HCV liver-related mortality is expected to decline by 75% from 11 300 (95% UI: 2600-19 600) to 3100 (95% UI: 50-7000) deaths by 2030.

3.4 Sensitivity analysis

The model inputs that had the largest contribution to the uncertainty in the Italy Polaris and PITER adjusted models are shown in Figure 3A,B. For the Italy Polaris model, the anti-HCV prevalence in 2015 had the largest effect on the 2030 forecast of infections (Figure 3A). There would be approximately 535 000 remaining viraemic cases in 2030, as compared to 288 000, if there were 1.24 million infections in 2015. More than 89% of the variability in the 2030 forecasted viraemic infections could be explained by the estimated number of treated patients. If the eligible linked to care patients were to diminish and only 10 000 patients would be eligible for treatment moving forward (rather than the base case of 33, 700), there would be an estimated 260 000 viraemic cases in 2030, almost 100 000 more than under the base assumption. The top five factors explained more than 98% of the variability in both models (Figure 3A,B).

In addition, we assessed how prevalence may impact the different linkage-to-care scenarios and the related case finding strategies. Given the “low” prevalence rate, the eligible patients to treat would be depleted sooner than under the base case (4). If prevalence was 370 000 infections rather than the 849 000, we would expect the eligible patients to treat to be depleted by 2022 under the 40% scenario; and in 2025 under both the 60% and 80% linkage to care scenarios. However, if prevalence was more than a million patients, the eligible patient pool would be reduced by 2027 under the 40% linked-to-care scenario. Under the 60% and 80% scenarios, the number of treated patients (approximately 35 000) could be maintained annually through 2030. The prevalence did not have a significant impact on the identified targeted screening strategies. Assuming a prevalence of approximately 370 000 cases, we estimate a less than 5% change in the distribution of F0-F3 cases by birth cohort.

Table 4. Year the eligible pool of patients to treat is estimated to be depleteda, by linkage to care scenario and prevalence range

Linkage to care scenario	Prevalence
	Low (n) 371 000	Base (n) 849 000	High (n) 1 240 000
40%	2022	2025	2027
60%	2025	2028	—
80%	2025	2031	—

• ^a To assess how the uncertainty in the prevalence estimate impacts the estimated number of eligible patients to treat, the linkage to care scenarios were run on the range of prevalence values (low: 371 000, base: 849 000, high: 1 240 000) to assess when the treated patients may exceed eligible patients (“be depleted”). —Signifies that given the “high” prevalence estimate, the treated patients will not exceed eligible patients and treatment levels can be maintained through 2030.

4 DISCUSSION

Italy has been considered the country with the highest HCV prevalence in Western Europe, with the peak prevalence in older ages (>70 years).14-16 However, many studies estimating HCV prevalence in the Italian general population were conducted more than 20 years ago and have shown regional variances.17 The highest prevalence rates have been reported in Southern Italy, though many of these earlier studies were conducted in smaller, more rural areas. Recent studies have also reported decreasing rates of HCV prevalence in the country.11, 18, 19

The limitation of HCV therapy is no longer treatment efficacy or adherence, but the identification of available patients to treat.20 As with prevalence, the availability of treatment and linkage to care varies across the country. Though in Italy a National Hepatitis Plan exists, decentralized models of HCV care persist and there are no uniform strategies across regional networks. Only 2 (Sicily and Veneto) of 20 regions throughout Italy have developed adequate organizational and operational politics regarding HCV elimination.21-23 Linkage to care is limited in that no enhanced HCV screening and diagnosis is implemented in the country. The number of prescribers is restricted only to gastrointestinal and infectious disease specialists whom are limited per region. It was recently estimated that there are 1500 residents per general practitioner in Italy, often curbing the availability of referral and linkage to care to a specialist.13 In addition, no specific strategies for marginalized patients and at-risk groups are implemented at the national level.

A true cascade of care for HCV infection is lacking in Italy as the number of patients under care remains uncertain. Recent studies reported between 20% and 80% of HCV+ individuals are aware of their status.11, 23 This uncertainty has clear implications for treatment, as the population first needs to be identified in order to be placed in care. While the real number of linked-to-care patients in Italy remains unknown, the PITER cohort is considered a representative sample of linked-to-care patients in Italy.8 The PITER linkage-to-care scenarios are based on the characteristics of patients enrolled in PITER and estimates different possible proportions of the “tip of the iceberg.” Extrapolating the age and fibrosis stage distribution of current linked-to-care patients (PITER model) to the general population in Italy (Polaris model) is useful for understanding what may occur in the overall infected population if current HCV trends are to remain at current levels. As seen in the Base 2016 Scenario, the WHO goal of reducing HCV liver-related deaths by 65% by 2030 is achievable in Italy if the treatment rate is maintained at current levels. However, in the 40% and 60% linkage-to-care scenarios, given the same number of treated patients through 2030, the eligible pool of patients to be treated would run out between 2025 and 2028, leaving a significant proportion of infected individuals undiagnosed and without access to care, as is shown in Figure 1.

Considering the cohort effect of HCV infection in Italy and low rates of injection drug use, the younger cohorts (1988+) are those with the lowest prevalence of HCV infection in Italy. We did not consider possible screening strategies for individuals born in 1935-1948 as the natural depletion of the virus in those individuals was assumed. This modelling estimates that more than 70% of the infected (F0-F3) individuals, those that are most often asymptomatic and undiagnosed (the underwater portion), were within the 1948 to 1978 birth cohorts in 2020 (Table 3). This signifies a potential need to increase case finding in these individuals if the treatment rate starts to decrease prior to the year 2025 (40% linked to care scenario). Similarly, though approximately 75% of individuals with chronic HCV in the United States are within the 1945-1965 birth cohort, screening in this population is not systematically done and a large portion of infected individuals fall outside of this cohort.24

The PITER adjusted model refers to a population with a mean age of 59 years, which in part reflects that of populations in other parts of the world that have similar epidemiological characteristics (ie individuals infected previously through blood transfusion or nosocomial transmission with historical trends of high incidence of infection).25 As seen in this modelling study, the rate of treatment uptake will decline unless screening and linking diagnosed patients to care is improved. In the country of Georgia, one of the nine countries on track to achieve the WHO Targets by 2030, the number of newly diagnosed patients entering the national treatment programme has fallen in the past year, suggesting that identification and linkage-to-care of HCV-infected patients in the country might be slowing.26, 27 The potential targeted screening strategies that were produced in this analysis are useful tools that can be used in countries with comparable HCV epidemiology. A similar approach can also be used for countries with different HCV epidemiology, in that it addresses the improvement of diagnosis and the linkage to care—key factors for achieving the elimination goals.28, 29

Several limitations of the analysis exist. This analysis was not focused on treatment as prevention. While neither disease burden model dynamically considers new infections nor reinfections in the population, the high treatment rate in Italy coupled with the reduced treatment restrictions exceeds the proportion required for treatment when compared to other dynamic models.30-32 In addition, although the PITER cohort is considered reasonably representative of those receiving care across the country, the PITER model uses a disease stage distribution based on a small proportion (9145 vs 357 000) of diagnosed and linked-to-care patients. The true proportion of the linked-to-care population in Italy is unknown. While rates of up to 80% have been reported,11 experts involved in the analysis have suggested that 40% of the total infected population is linked-to-care. To address this uncertainty, we presented the PITER analysis under three scenarios of 40%, 60% and 80% linkage-to-care. In addition, we evaluated the impact of this uncertainty and found the percent change in the linked-to-care population had a smaller influence on viraemic prevalence in 2030 than other factors (Figure 2A,B). Lastly, the variance in prevalence had limited influence on the proportion of F0-F3 patients identified and would not impact the screening strategies discussed.

This analysis highlights that Italy is on track to meeting the WHO target of 65% reduction in liver-related mortality by 2030. However, given the same number of annually treated patients through 2030, the eligible pool of patients to be treated would run out between 2025 and 2028, leaving a significant proportion of infected individuals undiagnosed and without access to care. Increased case finding through potential targeted screening strategies are necessary to achieve the WHO goals. This modelling analysis is a useful tool that can be used by different countries to develop screening strategies for HCV elimination.

CONFLICT OF INTEREST

The authors do not have any disclosures to report.