1. Hannah Fraser1, Natasha Martin2,1, Peter Vickerman1, Matthew Hickman1
18 November 2018
HCV treatment as prevention in Europe: model projections and impact of current and scaled-up treatment rates
Hannah Fraser1, Natasha Martin2,1, Peter Vickerman1, Matthew Hickman1
1Univeristy of Bristol, UK
2University of California San Diego, USA
Lisbon title slide
@hannahfraser243

2. Received honorarium from MSD
18 November 2018
Disclosures
Received honorarium from MSD

3. 18 November 2018
Acknowledgements
NIHR Health Protection Research Unit in Evaluation of Interventions.
European Commission Drug Prevention and Information Programme (DIPP) “Treatment as Prevention in Europe: Model Projections of Impact and Strengthening Evidence Base on Intervention Coverage and Effect and HCV Morbidity [JUST/2013/DPIP/AG/4812]”
NIHR (HS&DR) (12/3070/13) – Assessing the impact and cost-effectiveness of NSP on HCV
The views expressed are those of the author(s) and not necessarily those of NIHR or EU.
Co-authors:- Henrikki Brummer-Korvenkontio, Patrizia Carrieri, Olav Dalgard, John Dillon, David Goldberg, Sharon Hutchinson, Marie Jauffret-Roustide, Martin Kåberg, Amy A Matser, Mojca Matičič, Havard Midgard, Viktor Mravcik, Anne Ovrehus, Maria Prins, Jens Reimer, Geert Robaeys, Bernd Schulte, Daniela K van Santen, Ruth Zimmermann

4. Hepatitis C Virus (HCV) in Europe
18 November 2018
Hepatitis C Virus (HCV) in Europe
HCV infection is a leading cause of liver disease and morbidity, causing more deaths than HIV in many high-income countries1-3.
In Europe, people who inject drugs (PWID) are the main drivers of transmission of HCV4.
Existing interventions such as opioid substitution therapy (OST) and needle and syringe programmes (NSP) help reduce HCV transmission among PWID5,6
However, these are not sufficient to decrease prevalence to low levels so treatment is also needed.
1. Williams et al (2014) Lancet; 2. Nelson et al (2011) Lancet; 3. Cowie et al (2010) Journal of Hepatology ; 4. ECDC & EMCDDA (2011); 5. Turner et al. (2011) Addiction; 6. van den Berg (2007) Addiction

5. Why HCV treatment is needed for prevention
18 November 2018
Why HCV treatment is needed for prevention
Opioid substation therapy (OST) and needle and syringe programmes (NSP) can reduce HCV prevalence, but unclear whether can lead to substantial reductions
Therefore scaling-up treatment is also needed.
Vickerman et al. Addiction 2012.

6. Aims Estimate rates of HCV treatment in 11 European sites
18 November 2018
Aims
Estimate rates of HCV treatment in 11 European sites
Estimate impact of current and scaled-up treatment rates in each setting.
Project impact 2016 to 2026 if:
Current treatment rates continue with new DAAs,
Treatment rates are doubled,
Or 50/1000 PWID treated annually.
With and without scale-up of OST & NSP to 80% coverage.
Determine treatment needed to reduce incidence to 2% by 2026.

7. Methods Dynamic model of HCV transmission in PWID
18 November 2018
Methods
Dynamic model of HCV transmission in PWID
Model parameterised to site-specific data including
PWID population size
Antibody/chronic prevalence
OST/NSP coverage
Model calibration incorporated uncertainty in site specific data – multiple parameter sets.
Project the impact of interventions on prevalence and incidence.

8. Dynamic HCV transmission model among PWID
18 November 2018
Dynamic HCV transmission model among PWID
Recruitment
Susceptible: S
Previously infected, (Ab+ RNA-): E
Chronic infected, (Ab+ RNA+): I
Treatment: T
Failed treatment: F
Infection
Spontaneous clearance
Infection
Spontaneous clearance
Antiviral treatment
Sustained viral response (SVR)
Treatment failed
When switch to DAAs retreat those who have previously failed treatment.

9. Antibody prevalence and PWID population size
Norway*:
Prev=45%
Pop=15500
Antibody prevalence and PWID population size
Finland:
Prev=76.0%
Pop=15611
18 November 2018
Scotland:
Prev=58.0%
Pop=16000
Sweden:
Prev=81.7%
Pop=8–27000
Denmark*:
Prev= %
Pop=16500
Hamburg:
Prev=67.7%
Pop=8492
Amsterdam:
Prev=59.4%
Pop=1874
Belgium:
Prev=43.3%
Pop=9080
Czech Republic:
Prev=35.0%
Pop=42–47000
2. Antibody prevalence
We had antibody prevalence data which the model was fit to (unless chronic prevalence data was available – Denmark and Norway).
The year that antibody prevalence data for fit to depended on where the data was from, ranging from 2005 (Czech Republic) and 2007 (Amsterdam and Norway) up to 2014 (Finland, Hamburg, Sweden and Denmark).
Slovenia:
Prev=27.3%
Pop=6000
France:
Prev=66.4%
Pop=80000
* Chronic prevalence rather than antibody
Image from:

10. Results 1: % of estimated PWID with chronic infections treated at baseline (2015/16)
Only two sites are treating over 5% of those that are chronically infected at baseline.
Fraser et al, (2017) Journal of Hepatology, In press

11. Results 2: Baseline chronic prevalence
At baseline prevalence varies widely. As shown before, much higher in Finland and Sweden where there is little treatment among PWID than in Czech Republic and Slovenia.
Fraser et al, (2017) Journal of Hepatology, In press

12. Results 2: 10 year impact on chronic prevalence if switch to DAAs
Click 1: In sites with high prevalence and minimal treatment switching to DAAs has little inmpact.
Click 2: In sites with low or decreasing prevalence switching to DAAs has a much greater impact, with projections suggesting it likely to be able to observe a difference in prevalence in 10 years.
$ z-score < 0.5 (unlikely to observe a difference )
+ z-score (may be able to observe a difference )
* z-score (increasingly likely to be able to observe a difference )
# z-score >3 (highly likely to be able to observe a difference )
Fraser et al, (2017) Journal of Hepatology, In press

13. Results 2: 10 year impact on chronic prevalence if also double treatment rate
Click 1: Switching to DAAs and doubling treatment still has little effect in Finland, and slightly more in Sweden.
Click 2: In sites with moderate prevalence we see that projections suggest that the decrease in chronic prevalence will be observable, however (click 3) in Belgium it is still only increasingly likely.
$ z-score < 0.5 (unlikely to observe a difference )
+ z-score (may be able to observe a difference )
* z-score (increasingly likely to be able to observe a difference )
# z-score >3 (highly likely to be able to observe a difference )
Fraser et al, (2017) Journal of Hepatology, In press

14. Results 2: 10 year impact on chronic prevalence if treat 50/1000 per year
Finally, treating 50 per 1000 PWID has an impact at all sites (highly likely to observe at all), and this can really be seen at the sites with high prevalence and low initial treatment rates among PWID.
$ z-score < 0.5 (unlikely to observe a difference )
+ z-score (may be able to observe a difference )
* z-score (increasingly likely to be able to observe a difference )
# z-score >3 (highly likely to be able to observe a difference )
Fraser et al, (2017) Journal of Hepatology, In press

15. Results 3: Baseline and projected 10 year chronic prevalence – with OST/NSP scale-up
We now look at the results if we also scale-up OST and NSP to 80% coverage. Here we again have the prevalence at baseline.
$ z-score < 0.5 (unlikely to observe a difference )
+ z-score (may be able to observe a difference )
* z-score (increasingly likely to be able to observe a difference )
# z-score >3 (highly likely to be able to observe a difference )
Fraser et al, Journal of Hepatology, In press

16. Results 3: Baseline and projected 10 year chronic prevalence – with OST/NSP scale-up
What we see is that if we switch to DAAs and scale-up OST and NSP there is an immediate impact at all sites, with all sites projecting that this decrease is likely to be observable.
$ z-score < 0.5 (unlikely to observe a difference )
+ z-score (may be able to observe a difference )
* z-score (increasingly likely to be able to observe a difference )
# z-score >3 (highly likely to be able to observe a difference )
Fraser et al, Journal of Hepatology, In press

17. Results 3: Baseline and projected 10 year chronic prevalence – with OST/NSP scale-up
If we double treatments as well we can see that in many sites this then adds to the impact, however in Finland and Sweden there is still little additional impact on top of switching to DAAs. This is because of the minimal treatment.
$ z-score < 0.5 (unlikely to observe a difference )
+ z-score (may be able to observe a difference )
* z-score (increasingly likely to be able to observe a difference )
# z-score >3 (highly likely to be able to observe a difference )
Fraser et al, Journal of Hepatology, In press

18. Results 3: 10 year impact on chronic prevalence if also scale-up OST/NSP
If also scale up Ost and NSP to 80% then even just swopping to DAA with no scale up can have an observable impact, with the impact of scaling up to 50/1000 having much greater impact
Finally we can see that in all sites if we increase OST/NSP coverage we see a decrease, which is greater than the decrease over 10 years seen by simply increasing the treatment rate.
$ z-score < 0.5 (unlikely to observe a difference )
+ z-score (may be able to observe a difference )
* z-score (increasingly likely to be able to observe a difference )
# z-score >3 (highly likely to be able to observe a difference )
Fraser et al, (2017) Journal of Hepatology, In press

19. Results 4: Treatment needed (/1000 PWID) to reduce HCV to 2 per 100pyrs by 2026
Purple: Number of treatments per 1000 PWID at baseline (2015/16)
Green: Number of treatments needed per 1000 PWID in 2016/17 with current OST and NSP.
Yellow: Number of treatments needed per 1000 PWID in 2016/17 with 80% coverage OST and NSP.
Finally, we considered how much treatment is needed annually to reduce incidence to 2 per 100 person years by 2026.
The purple figures here show the baseline treatment number per 1000 PWID in There is much higher treatment in France per 1000 PWID than in other sites, and low treatment in Finland.
Fraser et al, (2017) Journal of Hepatology, In press

20. Results 4: Treatment needed per 1000 PWID to reduce HCV to 2 per 100pyrs by 2026
Purple: Number of treatments per 1000 PWID at baseline (2015/16)
Green: Number of treatments needed per 1000 PWID in 2016/17 with current OST and NSP.
Yellow: Number of treatments needed per 1000 PWID in 2016/17 with 80% coverage OST and NSP.
The green shows the number of treatments per 1000 PWID in each site if switching to DAAs only.
In Amsterdam and Slovenia, this is likely to be achieved simply by switching to DAAs and so minimal scale-up is needed.
In Czech Republic scaling-up treatment by 50% is likely to see 2% incidence by 2026.
In all other sites greater scale-up is needed, ranging from 3-17 times current treatment rates in all other sites other than Finland where 200 times current rates are needed.
However, we can see that per 1000 PWID this is actually a similar number of treatments to other sites.
Fraser et al, (2017) Journal of Hepatology, In press

21. Results 4: Treatment needed per 1000 PWID to reduce HCV to 2 per 100pyrs by 2026
Purple: Number of treatments per 1000 PWID at baseline (2015/16)
Green: Number of treatments needed per 1000 PWID in 2016/17 with current OST and NSP.
Yellow: Number of treatments needed per 1000 PWID in 2016/17 with 80% coverage OST and NSP.
Yellow shows treatment needed if OST and NSP also scaled-up to 80% coverage.
Can see that a decrease in the number of treatments is needed.
If we compare to baseline, in Amsterdam and Slovenia no scale-up is needed. In Czech Republic and Belgium minimal scale-up is needed as in over 50% of the runs 2% incidence is already achieved.
In other sites the scale-up needed compared to baseline is less than 5 times for all sites other than Finland, which is 150 times.
What is interesting to note is that the % decrease in the number of treatments needed is 20-80% across all sites if OST and NSP are scaled-up alongside switching to DAAs compared to if not.
Amsterdam 40%, Beglium 80%, CR 30%, Denmark 60%, Finland 20%, France 30%, Hamburg 23%, Norway 60%, Scotland 30%, Slovenia 20% Sweden 40%
Fraser et al, (2017) Journal of Hepatology, In press

22. 18 November 2018
Discussion
In most settings, treatment scale-up is necessary to substantially reduce HCV transmission among PWID in Europe.
Parallel scale-up of OST and NSP has greater impact.
Uncertainty in HCV treatment rates and HCV prevalence needs to be reduced in order to aid planning of interventions
Now need:
empirical evidence to test model projections & set affordable targets for HCV prevalence reductions.
Scale up case-finding to operationalise increase in treatment
Need to improve surveillance of HCV treatment uptake and prevention in PWID – important for evaluating ongoing progress
For point 2:
Generated from a diverse range of sources.
Only in Scotland was obtained from an ongoing community based surveillance system.