Department of SOCIAL MEDICINE University of BRISTOL HEPATITIS C AND LIVER DISEASE PREVENTION Dr. Natasha Martin, DPhil Matthew Hickman, Daniela De Angelis,

Department ofSOCIAL MEDICINE

University ofBRISTOL

HEPATITIS C AND LIVER DISEASE PREVENTION

Dr. Natasha Martin, DPhil

Matthew Hickman, Daniela De Angelis, Peter Vickerman, Katy Turner, Vivian Hope, Norah Palmateer,

Michael Sweeting, Sharon Hutchinson, Noel Craine, Graham Foster, David Goldberg, Alec Miners



PUBLIC HEALTH IMPORTANCE

In UK Liver disease is 5th commonest cause of death HCV/HBV 2nd most important cause liver

disease

Worldwide HCV infection causes ~1/4 liver disease (over

350,000 deaths per year)



ESTIMATED NUMBER OF PEOPLE INFECTED WITH ANTI-HCV ANTIBODIES

Sweeting et al. Biostatistics 2008; De Angelis et al, Statistics in Meical Research 2009; Ross et al EJPH in press



INTERVENTION EFFECTIVENESS

NSP is effective in reducing self-reported injecting risk behaviour

BUT on HCV transmission Insufficient review level evidence that NSP is effective Weak evidence that OST is effective No review level evidence for other interventions

Palmateer et al Addiction 2010 105: 844-59 (http://www.hepcscotland.co.uk/action-plan.html



POOLING UK EVIDENCE ON INTERVENTION IMPACT

Judd et al. BMJ 2005. Craine et al. J Epi & Inf 2009; Hope JVH 2010; Turner Addiction in press

Site Year Design N HCV+ve Incidence Sero-conversions

Bristol 2006 RDS 299 59% 40 per 100py 14

Leeds 2008 RDS 302 60% 7.6 per 100py 2

Birmingham 2009 RDS 310 42% 5.2 per 100py 2

Glasgow 2008-09 C'sectional NSP 947 70% 10.0 per

100py 6

Wales 2004-06 Follow-up 406/700 26% 5.6 per 100 py 17

London 2001-02 Follow-up 282/428 43% 42 per 100py 49



INTERVENTION EFFECT

Intervention coverage New HCV infection

Unadjusted OR 95% CI Adjusted

OR 95% CI

(a) OST On OST* 2.6% 0.36 0.19 – 0.70 0.41 0.21 – 0.82Not on OST 6.9%(b) NSP ** ≥ 100% coverage 3.8% 0.52 0.28 -0.99 0.48 0.25 – 0.93<100% coverage 7.0% (c) COMBINEDFull HR: OST and no injecting or ≥100% NSP 2.0% 0.19 0.08 – 0.47 0.21 0.08 – 0.52

≥100% NSP, No OST 5.3% 0.52 0.23 – 1.15 0.5 0.22 – 1.12<100% NSP, On OST 4.3% 0.41 0.15 – 1.12 0.48 0.17 – 1.33Minimal HR 9.8%

Adjusted for the following covariates: female gender (AOR 2.1); homeless in last year (2,9); injected crack in last month (1.9); duration injecting <2.5 years (1.0)

* Includes or ** Excludes 86 cases (involving 0 new HCV infections) who were on OST but reported no injections in the last month (cross-sectional studies) or last year (cohort studies).



BUT WHAT ABOUT THE EFFECT ON HCV PREVALENCE?

HCV prevalence has decreased over time in some settings

But none have decreased HCV to low levels

Recent data from England/Wales suggests might be increasing

ENGLAND AND WALES DATA

Sweeting, M., et al., AJE 2009. 170: 352-60



BRISTOL SURVEYS – 2006 : 2009

HCV Prevalence ~53% 2006 (n=299) ~57% 2009 (n=336)

Recent infections/incidence ~40% 2006 (15 Antibody-ve PCR+ve) <10% 2009 (3 Antibody-ve PCR+ve)

> 80% reduction in incidence



CAN SCALING UP THE COVERAGE OF EXISTING INTERVENTIONS REDUCE HCV PREVALENCE?



IMPACT OF CHANGING COVERAGE OF OST AND NSP FROM 50%: 0%, 60%, 70%, 80%

0%

10%

20%

30%

40%

50%

60%

70%

80%

Without 60% 70% 80% 60% 70% 80% 60% 70% 80%

NSP/OST 5 years 10 years 20 years

HC

V p

revale

nce

(baseli

ne w

as 4

0%

pre

vale

nce)

Effect of scaling up both OST and NSP to 60%, 70% and 80% coverage for different durations (baseline was 50% coverage)



IMPLICATIONS

NSP and OST can reduce HCV incidence. And have averted infections BUT unclear whether further scaling up

feasible or could lead to substantial reductions in HCV prevalence

Other prevention options needed Could HCV treatment have an impact?



HCV ANTIVIRAL TREATMENT: BARRIERS AMONG ACTIVE IDUS

Antiviral treatment effective (~60%) for curing HCV infection and approved for active injecting drug users (IDUs)

BUT few currently being treated (<1%) Perceived reluctance/concern over high rates of:

Non-completion/compliance Re-infection following treatment



MATHEMATICAL MODEL

Non-responder infected IDUs

HCV chronically

infected IDUs

Uninfectedactive IDUs

Antiviral treatment

Allow for reinfection

Infection

Death or cessation from each state

New injectors

Outcome: Impact on

HCV prevalence

Martin et al. J Hepatology 2011; J Theoretical Biology 2011



PROJECTIONS



RELATIVE PREVALENCE REDUCTIONS AT 10 YEARS WITH VARYING TREATMENT RATES

‘Baseline’: untreated endemic chronic infection prevalence

Martin et al. J Hepatology 2011



PREVALENCE REDUCTIONS AT 10 YEARS

Population of 3500 IDUs, 1400 chronic infections• 70 treated annually (20 per 1000 IDUs)

• 30% reduction by 2021 (40% 28%)• 140 treated annually (40 per 1000 IDUs)

• 58% reduction by 2021 (40% 17%)




PROJECTIONS THROUGH TIME (5, 10, 20 YEARS) ANNUALLY TREATING 20 PER 1000 IDUS

Swift and substantial reductions at low prevalence Significant reductions even at high prevalence 3500 IDUs, 1400 infected (40% prevalence), 70 treated/yr

15% reduction in 5 years (4034%) 30% reduction in 10 years (4028%) Halved in 20 years (40 20%)




INCREMENTAL COST PER QALY VS. NO TREATMENT: EQUAL EFFICACY (SVR) FOR EX- AND ACTIVE IDU

Treating IDUs may be highly cost effective – and more cost effective (at prevalences <60%) than treating ex/nonIDU Averts infections

Martin et al in preparation



IMPLICATIONS



SCALE-UP – FROM MODELLING TO REALITY – EMPIRICAL DATA NEEDED

Trouble with models Theoretical: projections not observations Need to introduce heterogeneity:

injecting risk/ HCV treatment uptake/ SVR Model combined effects of HCV Rx, OST & NSP

BUT models can raise hypotheses/ provide theoretical framework/ justification for future work

Now empirical evidence required



SCALING UP HCV TREATMENT

What are the best models/ways of delivering HCV treatment to injectors in community? Start with OST population Peer projects/ support Treatment advocacy

Who is not worth starting treatment with i.e. compliance/SVR too low

Documents

Department of SOCIAL MEDICINE University of BRISTOL HEPATITIS C AND LIVER DISEASE PREVENTION Dr. Natasha Martin, DPhil Matthew Hickman, Daniela De Angelis,