confidence in numbers; the evidence base for assessing thepublic health impact of vaccines against...

THE EVIDENCE BASE FOR ASSESSING THE PUBLIC HEALTH IMPACT OF VACCINES AGAINST INVASIVE

MENINGOCOCCAL DISEASESUK/BEX/13-0047f

Date of prep: Oct 2013

Disclosure statement• Prof Richard Moxon is a member of the Scientific

Advisory Boards of Novartis Vaccines and Diagnostics (NVD) and GlycoVaxyn from whom he receives financial compensation for his time; he holds no intellectual property and has no financial holdings or potential gains relating to 4CMenB.

Milestones in meningococcal vaccines

• 1970s Polysaccharide vaccines• 1992 First conjugates for MenA and MenC• 1999 MenC licensed in UK• 2003 MenACYW licensed in USA (aged >11y)• 2010 MenA licensed in Africa• 2013 MenACYW licensed (aged >2 months)• 2013 EMA licenses 4CMenB (Bexsero ®▼)

Bexsero prescribing information can be found on the last slide

July 2013: JCVI watershed recommendation*

• «.......on the basis of the available evidence .... immunization using Bexsero is highly unlikely to be cost- effective ......

• ...and could not be recommended» * JCVI interim position statement on use of Bexsero meningococcal B vaccine in the UK

Models of cost effectiveness

• Models simplify: they are supposed to ….

• Some factors are omitted

• Can these omissions introduce bias?- familiar examples: climate change, markets

In defence of models: “Better to be roughly right than precisely wrong – or not to make any estimate at all ”

John Maynard Keynes In opposition to models:“ Not appropriate tools for decision making as their use assumes a level of knowledge and precision that is illusory ”

Robert Pindyck

Aims of breakfast session • To provide information and stimulate discussion on the

evidence base used to inform decision making on the potential public health impact of 4CMenB (Bexsero)

• Measuring disease burden and estimating vaccine impactDr Jamie FindlowDeputy Head of Vaccine Evaluation Unit, Public Health England, Manchester

• Challenges to quantifying the severity of meningococcal diseaseDr Simon NadelConsultant in Paediatric Intensive Care, St Mary’s Hospital, London

• Panel discussion

Measuring disease burden and estimating vaccine impact

[email protected]

Vaccine Evaluation Unit, Public Health England, Manchester, UK.

Jamie Findlow

10 Measuring disease burden and estimating vaccine impact

Jamie Findlow undertakes research, advisory and educational activities on behalf of Novartis as well as other vaccine manufacturers. All income and payments associated with these activities are made to his employers, Public Health England or independent charity.

Disclosure statement


Background information Model input parameters

Evidence base for determining- Disease burden Vaccine strain coverage Vaccine impact on carriage (herd protection)

Summary and conclusions

Presentation overview

Epidemiological parameters Disease burden/incidence Case fatality rate Years of life lost

Treatment costs Ambulance & hospital costs Specialist/intensive care costs Follow up care costs

Long-term effects of disease Sequelae QALY

What are the input parameters into a model?


Vaccination parameters Vaccination coverage Vaccine efficacy Vaccine strain coverage Impact (reduction) on carriage Adverse reactions Vaccine cost Delivery costs

Public Health response Response to each case

Aim: present the scientific data for deriving an input value for each of these parameters

1998/991999/00

2000/012001/02

2002/032003/04

2004/052005/06

2006/072007/08

2008/092009/10

2010/112011/12

2012/130

20

40

60

80

100

120

140

Num

ber o

f cas

es


Changing epidemiology- Laboratory confirmed meningococcal disease cases in England & Wales1

2000/01 “Hajj” outbreakNatural fluctuation

1998/991999/00

2000/012001/02

2002/032003/04

2004/052005/06

2006/072007/08

2008/092009/10

2010/112011/12

2012/130

20

40

60

80

100

Num

ber o

f cas

es

MenW

MenY

Natural fluctuation

1 Public Health England Meningococcal Reference Unit, Unpublished data

17 cases

87 cases

21 cases

58 cases


1984

/85

1985

/86

1986

/87

1987

/88

1988

/89

1989

/90

1990

/91

1991

/92

1992

/93

1993

/94

1994

/95

1995

/96

1996

/97

1997

/98

1998

/99

1999

/00

2000

/01

2001

/02

2002

/03

2003

/04

2004

/05

2005

/06

2006

/07

2007

/08

2008

/09

2009

/10

2010

/11

2011

/12

2012

/130

500

1000

1500

2000

2500

3000 NG/ND Z/29E W Y X C B A

No.

of c

ases

Laboratory confirmed cases of meningococcal disease from England & Wales, 1984/85 to 2012/131

1 Public Health England Meningococcal Reference Unit, Unpublished data

PCR confirmation introduced in 1996

Lowest MenB burden344 cases

Highest MenB burden1624 MenB cases

‘Latest’ MenB burden622 cases

2004/05 to 2005/06Ave 1174 MenB cases per year



Last two years (2011/12 to 2012/13)

Ave 633 MenB cases per year

Which data source should be used? PHE Meningococcal Reference Unit (MRU). PHE infectious disease surveillance reports (LabBase). Hospital Episode Statistics (HES). Office National Statistics (ONS) death registrations.

Disease burden varies across age groups (and varies by capsular group).

Meningococcal epidemiology is unpredictable- Naturally fluctuates with peaks and troughs. Outbreaks may occur.

Other considerations when determining disease burden


Meningococcal Antigen Typing System (MATS)

Are any of the Bexsero components in the test strain: (i) Expressed to a sufficient degree?

and(ii) Similar enough to the antigens in the

vaccine such that the antibodies generated by Bexsero will kill the bacteria?

MATS ELISA determines the minimum amount of recognisable antigen needed to result in bacterial killing for each of fHbp, Nad A and NHBA (PorA characterised by

sero/genotyping).

For a strain to be ‘covered’, at least one antigen must be greater than the positive bactericidal threshold (PBT) or possess homologous PorA.


20 Measuring disease burden and estimating vaccine impact20

England and Wales

France Germany Italy Norway Combined0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

4Ag>PBT*3Ag>PBT*2Ag>PBT*1Ag>PBT*

Vogel U et al., Lancet Infect Dis 2013;13:416-25.

*> MATS PBT for fHBP, NadA and NHBA/homologous PorA.

MATS predicted coverage of European MenB isolates from 2007/08

73% 85% 82% 87% 85% 78% Overall coverage (57-87) (69-93) (69-92) (70-93) (76-98) (63-90) (95% CI)



Considerations for interpreting MATS data

MATS concept is “conservative” and does not account for- Any antibody synergy.1-3

Any responses against minor OMV components.1-3

1Donnelly J et al., Proc Natl Acad Sci USA 2010;107:19490-5.2Frosi G et al., Vaccine 2013: in press3Vogel U et al., Lancet Infect Dis 2013;13:416-25.

MATS PBT derived using pooled sera from 12-13 month toddlers post booster.1

Infants antibody responses are less cross-reactive. Older children's and adolescents antibody responses may be

more cross-reactive.

MATS may underestimate NadA expression due NadR repression during the in-vitro assay growth conditions.1,3


Percentage of 40 strain subset killed in hSBA assay


MATS Prediction(535 MenB strains from

2007/07)1

MATS Prediction (40 MenB strains

subset)

MATS prediction (full data set)

MATS prediction (40 sub set)

Toddler sera Adolescent sera0

20

40

60

80

100

Per

cent

age

cove

rage

73%(95% CI 57-87)

88%(95% CI 72-95)

88%(95% CI 72-95)

70%(95% CI 55-85)

1Vogel U et al., Lancet Infect Dis 2013;13:416-25.


Capsular group distribution of laboratory confirmed meningococcal disease, England

and Wales, 2012/131

Other1%

C4%

W7%

Y10%

B78%

1 Public Health England Meningococcal Reference Unit, Unpublished data2Claus et al., Poster 273, International Pathogenic Neisseria Conference 2012, Wurzburg, Germany, 9-14 September 2012.

Q1- Could protection be afforded against non-MenB strains?

Q2- Should any ‘additional’ protection be considered?

<1 1-4 5-9 10-14 15-19 20-24 25-44 45-64 >=650

50

100

150

200

Age breakdown of MenW cases in England and Wales 2006/07 to

2012/131

Age group

Num

ber o

f cas

es

One study suggested that 27/57 (48%) of MenC and 14/20 (70%) of MenW strains could be killed in the SBA assay by pooled post-Bexsero vaccination sera from toddlers.2

69% of cases in >20 years of

age

31% of cases in <20 years of

age

25 Measuring disease burden and estimating vaccine impact25

Why is carriage and herd protection important?

1Takala AK et al., J Infect Dis 1991;164:982-6. 2Dagan R et al., J Infect Dis. 1996;174:1271-8. 3Maiden MC et al., J Infect Dis. 2008;197:737-743. 4Kristiansen PA et al., Clin infect Dis 2013;56:354-63. 5Ramsay ME et al., BMJ; 326:365-6.


Glycoconjugate vaccines reduce the acquisition of nasopharyngeal carriage of Haemophilus influenzae type b1, Streptococcus pneumoniae2, MenC3 and MenA4.

Imparts herd protection, and impacts on immunisation strategy.

1999 2000 20010

1

2

3

Per

cent

age

of M

enC

isol

ates

71% reduction 81%

reduction

Reduction in MenC carriage3

(immunised 15-19 year olds)Direct and Herd protection5

Unvaccinated 1998/99

Unvaccinated 2001/2002

Vaccinated 2001/2002

0

2

4

6

8

Atta

ck ra

te p

er 1

00,0

00 67% reduction in rate in unvaccinated cohort 2001/02


Impact of outer membrane vesicle vaccines on carriage

Bjune G et al., 19921

Rosenqvist E et al., 19942

Holmes JD et al., 20083

Delbos V et al., 20134

Country Norway Norway New Zealand France

Subject age range 13-21 13-14 17-24 3-7

Number of subjects

(vaccinated/controls)

Observations from multiple phase II trials

529/265 57/152 321/761

Vaccine MenBvac MenBvac MeNZB MenBvac

Reduction of carriage No No

Yes (100% for

vaccine/outbreak strain)

Yes (85% for all

meningococci)

Prevention of acquisition No

Yes (59% for all

meningococci)No ND

1Bjune G et al., Lancet 1992;340:315. 2Rosenqvist et al., In VIII International Pathogenic Neisseria conference, 1994, Cuernavaca, Mexico, 4-9 October 1992. 3Holmes JD et al., Epidemiol Infect 2008;136:790-9. 4Delbos V et al., Vaccine 2013;31:4416-20.

ND: Not determined

Do OMV vaccines have an impact on carriage?

Conflicting results/inconclusive.

Small numbers of subjects in each study.

Low carriage rates have hindered evaluations.


Bexsero carriage study1,2

Group Visit 1Day 1

Visit 2Month 1

Visit 3Month 2

Visit 4Month 4

Visit 5Month 6

Visit 6Month 12

Bexsero SwabBexsero

SwabBexsero

Swab Swab Swab SwabMenveo

Control SwabJE vaccine

SwabJE vaccine

Swab Swab Swab SwabMenveo

MenACWY SwabMenACWY

SwabPlacebo

Swab Swab Swab Swab-

Primary analysis- Carriage of disease associated sequence types (ST) of N. meningitidis capsular group B, 1 month post-2nd dose of Bexsero.

Trial Design

JE- Japanese Encephalitis vaccine

1Read R et al., In The 31st meeting of the European Society for paediatric infectious diseases. 2013, Milan, Italy, 28th May-1st June 2013. 2Borrow et al., In The 13th European Meningococcal Disease Society, 2013, Bad Loipersdorf, Austria, 17-19th September 2013.

Enrolled

974

983

984


* Analyses adjusted for baseline carriage, treatment group, centre and significant risk factors as identified within the multivariate model.

Bexsero carriage study- Primary analysis1,2

Bexsero Group

Control Group

Efficacy % (95% CI)

Visit 3(Month 2)

Number 87 75

-18.2(-73.7 to

19.4)% 9.50 8.08

N 916 928


Primary analysis- Carriage of disease associated sequence types (ST) of N. meningitidis capsular group B, 1 month post-2nd dose of Bexsero.*

Study limitations

High baseline carriage rates (~33%).

Access to students prior to period of high transmission not possible.

Assessment of individual impact, not of herd protection.


* Analyses adjusted for baseline carriage, treatment group, centre and significant risk factors as identified within the multivariate model.

Bexsero carriage study- Further analyses1,2

Further analysis- Efficacy % (95% CI) of Bexsero group compared to control group undertaken for visits 4 to 6 (months 4 to 12).*

GroupCapsular group B (all STs)

Capsular group B, C, W & Y

Any N. meningitidis

All 15.6(-11.0 to 35.9)

26.6(10.5 to 39.9)

18.2(3.4 to 30.8)


Early enrollers (<30 days after start of semester)

17.0(-28.9 to 46.5)

32.0(8.2 to 49.6)

33.7(13.9 to 49.0)

Smokers 38.1(-9.1 to 64.9)

44.8(14.0 to 64.5)

32.2(2.5 to 52.9)

<21 years of age at enrolment

23.9(-4.0 to 44.4)

28.0(9.9 to 42.4)

22.5(6.3 to 35.9)

Risk factor subgroups with high

transmission/acquisition

Summary and conclusionsDisease burden

Meningococcal epidemiology is unpredictable and continually fluctuating.


Strain coverage MATS is “conservative” with recent data indicating higher coverage than that predicted by MATS.

Should protection against non-MenB strains be included in coverage?

Carriage impact Although the Bexsero carriage study failed to show any positive impact for the primary analysis, due to various limitations, further analyses demonstrated an impact.

Other considerations The scientific data behind each input parameter is variable and it is difficult to decide upon which is the appropriate or ‘correct’ value.

Any value derived is a prediction of the future, which may or may not be accurate.

Acknowledgements


Vaccine Evaluation Unit, Public Health England, Manchester

Ray Borrow.

Meningococcal Reference Unit, Public Health England, Manchester

Ed Kaczmarski, Steve Gray and Tony Carr.

Immunisation, Hepatitis and Blood Safety Department, Public Health England, London

Mary Ramsay, Shamez Ladhani and Helen Campbell.

Challenges to quantifying the severity of

meningococcal disease.

Novartis Symposium 2013 Dr Simon Nadel

Disclosure statement

Dr Simon Nadel undertakes research, advisory and educational activities on behalf of Novartis, Pfizer and the National Meningitis charities.

Challenges in quantifying disease

• Can we accurately quantify mortality and morbidity?

• Can wider impacts of meningococcal disease (social, economic and public health considerations ) be quantified?

Variability in reported mortality & morbidity

• Key differences in study inclusion criteria and definitions:– Disease focus (meningitis, septicaemia, IMD, acute life-threatening illness)– Study populations (age, geography, hospitalisation/ ICU admission)– Follow-up period (acute vs long-term)– Categorisation, scoring and weighting of sequelae (impact on QoL) – Physical +/- neuro-psychological impact on individuals

• No consensus on how to weigh the impact of different sequelae– Do “major” and “minor” sequelae have different impact on Quality of Life?– Include immediate and long-term effects of sequelae?– Can we effectively quantify Quality of Life loss in children?– Impact on patients +/- carers +/- families +/- healthcare system +/- society?

Variability in reported mortality:CFR

Age-group (y)

Causative organism(s)

Data collection

Datasource Reference

23% - 2% 0-18 All capsular groups

1992-1997 St. Mary’s Hospital PICU Booy, 2001

5.2% 0-19 Capsular group B

2006/7-2010/11

HPA enhanced surveill, England & Wales

Ladhani, 2013

4% All ages Not specified 1997/8-2005/6

HES data, England Christensen, 2013

4.9% All ages All capsular groups

1999-2010 English national linked database

Goldacre, 2013

12.4% - 10.6% 0-19 All capsular groups

1995, 2000, 2005

Severe mening sepsis data from 7 US states

Hartmann, 2013

4.4% 0-1 All capsular groups

1985-7 England & Wales De Louvois, 1991

Variability in reported morbidity:Meningococcal disease and meningitis

Invasive meningococcal serogroup B disease in children and adolescents (MOSAIC)

244 survivors of group B meningococcal disease

Meningitis in infancy in England and Wales: follow up at age 5 years

402 survivors of meningococcal meningitis

1% disabling amputations 2.9% severe disability

9% major disabling deficits 6.5% moderate disability

36% at least one deficit 29.8% mild disorder

2% profound bilateral SNHL 60.7% no disability

5% moderate bilateral SNHL

6% any SNHL (control <1%)

4% speech/ communication difficulty

IQ, memory and executive function significantly worse

Significantly higher risk of mental health disorder (26% vs 10%)

Viner, 2012 Bedford, 2001

Variability in reported morbidity:Survivors of meningococcal septic shock that required PICU treatment

Long term skin-scarring & orthopaedic sequelae

n=170, 4-16y after discharge

Long term overall outcome and health-related QoL

n=120, 3-18y after discharge

Long term health status

n=120, 10y after discharge

34% scarring 61% had 1 of 4 major adverse outcome variables

35% one or more neurological impairment

5.8% amputations 21.7% had >1 major adverse outcome

4% severe mental retardation

4.1% lower limb length discrepancy

39.2% had 1 major adverse outcome

3% epilepsy

All had higher severity of illness scores

7.6% major physical adverse outcome

2% hearing loss

15.8% mild neurological outcome 6% focal neurology (i.e. paresis)

5.8% problem behaviour

6.7% had IQ<85

Longer LOS and higher severity score predicted worse outcome

Buysse, 2009 Buysse, 2010 Buysse, 2008

Main determinants of outcome

• Severity/pathophysiology

• Management

• Pre-morbid condition

• Genetics

• Family

• Other factors

Challenges in quantifying disease

• Can we accurately quantify mortality and morbidity?

• Can wider impacts of meningococcal disease (social, economic and public health considerations ) be quantified?

Clinical evidence of longer-term effects

• “Longer-term psychiatric adjustment of children and parents after meningococcal disease”Garralda ME, Gledhill J, Nadel S, Neasham D, O'Connor M, Shears D. Pediatr Crit Care Med. 2009 Nov;10(6):675-80. doi: 10.1097/PCC.0b013e3181ae785a.

• Prospective cohort study of 70 children aged 3-16y with MD, admitted to 3 PICUs and 22 general paediatric wards in London–Parents and children seen 2-5d after hospital admission, and followed up following discharge at 3m (postal questionnaire) and 12m (interview)–Psychiatric risk assessed in children (SDQ), parents (GHQ) and both (IES)

• Summary: 50% of children develop mostly new psychopathology following MD (primarily depressive and anxiety-related disorders). In 25% this persisted at one year

Outcomes in children and parents, 3 months and 12 months post discharge

Children < 6y Children >6y Parents

3 monthspost discharge

11% had PTSD

Psychological symptoms linked to: PICU admission, illness severity, similar symptoms in parents and pre-morbid psychological symptoms

MD associated with emotional and hyperactivity symptoms

~50% mothers and ~25% fathers had PTSD symptoms

12 monthspost discharge

11% children at risk for PTSD

Psychological symptoms linked to illness-related changes in parenting

24% mothers and 15% fathers at high risk for PTSD

Maternal PTSD linked to paternal PTSD

1 child developed PTSD

22% scored above cut-off for psychiatric disorder

Problems: tantrums, difficult to manage, sleep problems, fears and feeding problems

50% at least one disorder16% major depression10% minor depression8% adjustment disorder8% oppositional defiant disorder2% phobic disorder2% panic disorder2% organic psychotic disorder

Psychological after effects in parents & carers

Garralda ME, et al. Pediatr Crit Care Med. 2009;10(6):675-80

Clinical evidence of neuropsychological effects

• “Neuropsychologic function three to six months following admission to the PICU with meningoencephalitis, sepsis, and other disorders: a prospective study of school-aged children”Als LC, Nadel S, Cooper M, Pierce CM, Sahakian BJ, Garralda ME.Crit Care Med. 2013 Apr;41(4):1094-103. doi: 10.1097/CCM.0b013e318275d032.

• Prospective observational case-control study of 88 children aged 5-16y admitted to ICUs between 2007-2010 c.f. 100 healthy controls–Follow-up 3-6 months after PICU admission–Data encompassing demographic and critical illness details were obtained, and children were assessed using tests of intellectual function, memory, and attention –Questionnaires addressing academic performance were returned by teachers.–Measurement tools: WASI, WRIT, CMS, Cambridge Neuropsychological Test Automated, Battery (CANTAB)

Psychiatric risk PTSD risk

Neuropsychologic function after PICU admissionCognitive function

• Summary: Meningoencephalitis and sepsis particularly associated with reduced neuropsychological function

• Are these effects fully considered in evaluation of new vaccines?

Adapted from Als LC, et al. Crit Care Med. 2013;41(4):1094-103

Can social, economic and public health considerations

be quantified?

Counting the cost of Meningitis:Estimates for the management costs of a severe case of meningitis

Wright C, Wordsworth R, Glennie L. Meningitis Research Foundation: Counting the costs of meningitis. 2011.

Discounted costs

Undiscounted costs

Costs to NHSAcute costs26 days in PICU, 155 days on rehabilitation ward

Outpatient appointments, including:-Physiotherapists-Speech and language therapists-Occupational therapists

Other specialist treatments

£600,000 to

£1,000,000

£1,230,000to

£2,360,000

Costs to Personal Social ServicesSocial care assessment, direct pay payments, short break provision, residential

Costs to governmentEducation, disabled facilities grant, specialised vehicle fund, lost income tax revenue, transfer payments

£1,300,000 to

£1,700,000

£2,980,000 to

£4,280,000

?Day to day costs to the family

with a disabled child are

three times more than with a non-disabled child

(Minimum budget to bring up a disabled child £7,355 per year compared to £2,100 for a non-

disabled child2 )

Families are

four times more likely

to be living in poverty

(84% of mothers of disabled children do not work compared to 39% of mothers of non-

disabled children1)

Siblings of disabled children are more likely to experience

behavioural and emotional problems1

1. New Philanthropy Capital, 20072. Joseph Rowntree Foundation, 1998

Depression and anxiety

are more common among family members1

Costs to society

Summary• Estimates of mortality and morbidity (frequency and impact) vary

considerably

• The values selected for inclusion directly affect cost-effectiveness calculations

• HE models currently include values to represent:– Case fatality rate– Proportion of survivors with ‘minor’ sequalae– Proportion of survivors with ‘major’ sequalae– QALY for survivors without sequalae– QALY loss for survivors with sequalae

• Can we be confident that the selected data adequately capture the clinical burden of meningococcal disease?

PANEL DISCUSSION

UK/BEX/13-0047f Date of prep: Oct 2013

Strengths of models• Validated method for assessing complex outcomes:

multiple components and non-linearity result in counterintuitive results

• Provides systematic benchmarking of economic gains or losses to facilitate policy decisions

• Rigorous exploration (e.g. through sensitivity analyses) of worst case and best case scenarios – parameter space

Weaknesses of models

• Results depend crucially on the confidence -- or lack of it -- in the data used to construct the models

• Biases are introduced because some essential factors are not easily quantified

• It is only one of many methodologies used to assemble an evidence base.

• A blunt tool for assessing public health impact as compared to economic gains

THE EVIDENCE BASE FOR ASSESSING THE PUBLIC HEALTH IMPACT OF VACCINES AGAINST INVASIVE

MENINGOCOCCAL DISEASESUK/BEX/13-0047f

Date of prep: Oct 2013

confidence in numbers; the evidence base for assessing thepublic health impact of vaccines against...

Health & Medicine