Case study:
Structural uncertainty in
human papillomavirus
vaccination
Mark Jit
modelling
Modelling and Economics
Unit
1 and WJ Edmunds1,3
MHealth
Jit1,2, YProtection
Choi1, N GayAgency,
London
1Centre for Infections, Health Protection Agency
2University of Birmingham
3London School of Hygiene & Tropical Medicine
Outline
• Introduction to the problem
• Representing structural uncertainty
• Selecting optimal scenarios
• Presenting results
HPV vaccines
GardasilTM
• Protects against HPV 6, 11, 16, 18.
• Doses at 0, 2, 6 months.
• Aluminium adjuvanted.
• Licensed widely, in use in several
countries.
CervarixTM
• Protects against HPV 16, 18.
• Doses at 0, 1, 6 months.
• AS04 adjuvanted.
• Licensed in Europe and Australia.
Female HPV prevalence in UK
DNA studies
UK HPV prevalence
KITCHENER(ARTISTIC). Manchester, 2001-2003
45%
PETO. Manchester, 1987-1993
40%
CUZICK(HART). 5 UK cities, 1998-2001
7%
6%
HIBBITS. S Wales, 2004
30%
25%
20%
CUSCHIERI. Edinburgh, 2000
5%
Warts at GPs. England and Wales, 2005
4%
Warts at GUM. UK, 2005
3%
15%
NA
/6
5
60
-6
4/
69
/N
A/
A/
59
/5
5+
50
-5
4
45
-4
9
40
-4
4
514
/u
nd
er
55
-5
9/
69
/6
0/
N
Age group
35
-3
9
0%
30
-3
4
0%
25
-2
9
1%
20
-2
4
5%
15
-1
9
2%
16
10%
Warts incidence (% pop)
WOODMAN. Birmingham, 1988-1992
35%
HPV prevalence (%)
8%
Structural uncertainty
Epidemiological
uncertainty
Progression and regression of HPVrelated neoplastic states.
Duration of HPV infection.
Prevalence of anogenital warts among
HPV 6 and 11 infected people.
Natural regression of HPV-related
neoplasias.
Existence of natural immunity to HPV.
Pattern of sexual partnerships
between age and risk groups.
Vaccine protection against nonvaccine HPV types.
Duration of vaccine protection.
Coverage of vaccination programme.
Uncertainty about disease burden
Cost and QoL impact of screening.
Cost and QoL impact of treating neoplasias, cancer, warts.
Accuracy of cytological screening and DNA testing.
Types of models used
Type specific HPV
prevalence by
cytological status
(ARTISTIC trial)
Diagnosed
anogenital warts
cases
(GP and GUM clinic
returns)
Cost and quality of
life data
(current literature)
Natural history
stage
Progression and
regression rates
Sexual transmission
stage
Changes in disease
end points after
vaccine introduction
Economic stage
Changes in the
economic burden
(cost and quality of
life)
Cytological status at
time of screening
(Cervical screening
programme)
Sexual partnership
patterns
(Sexual lifestyle
survey 2000)
Duration, QoL
detriment of warts
episode
(York GUM study)
Natural history
stage
HPV type
3 scenarios
(16, 18, others)
Progression and
regression rates
Sexual transmission
stage
HPV prevalence
3 scenarios
Changes in disease
end points after
vaccine introduction
Economic stage
Changes in the
economic burden
(cost and quality of
life)
Transition rates
8 parameters
(in range [0,1])
Disease
progression
162 models
Clinical
specificity of
DNA test
3 scenarios
(100%, 99.75%,
99.5%)
Regression
2 scenarios
(stepwise,
immediate)
Accuracy of
cytological
screening
3 scenarios
(High, Medium,
Low)
Natural history
stage
Progression and
regression rates
Sexual transmission
stage
Changes in disease
end points after
vaccine introduction
Economic stage
Changes in the
economic burden
(cost and quality of
life)
Jit M, Gay N, Soldan K, Choi YH, Edmunds WJ. Estimating progression rates for human
papillomavirus infection from epidemiological data. Medical Decision Making (in press).
Natural history
stage
Duration of
natural immunity
5 scenarios
(0, 3, 10, 20, 
years)
Progression and
regression rates
Sexual transmission
stage
Duration of
infection
5 scenarios
(6, 9, 12, 15, 18
months)
Changes in disease
end points after
vaccine introduction
Economic stage
Changes in the
economic burden
(cost and quality of
life)
Parameters
governing sexual
partnerships
2 parameters
(in range [0,1])
Disease
transmission
450 models
Assortativeness
of sexual
partnerships
3 scenarios
(low, medium,
high)
Duration of
vaccine
protection
3 scenarios
(10, 20,  years)
Risk of HPV
transmission per
partnership
2 scenarios
(low, high)
Natural history
stage
Progression and
regression rates
Sexual transmission
stage
Changes in disease
end points after
vaccine introduction
Economic stage
Changes in the
economic burden
(cost and quality of
life)
Natural history
stage
Progression and
regression rates
Sexual transmission
stage
Changes in disease
end points after
vaccine introduction
Economic stage
Changes in the
economic burden
(cost and quality of
life)
Natural history
stage
Sexual transmission
stage
Changes in disease
end points after
vaccine introduction
Economic stage
Changes in the
economic burden
(cost and quality of
life)
2,000
Squamous cell cancers per year
Progression and
regression rates
1,500
1,000
Mean
Median
500
Minimum
Maximum
0
0
50
100
Sum of squared residuals cutoff
150
Natural history
stage
Progression and
regression rates
Sexual transmission
stage
Changes in disease
end points after
vaccine introduction
Economic stage
Changes in the
economic burden
(cost and quality of
life)
Natural history
stage
Scenario
variables
12 variables
(integer coded)
Progression and
regression rates
Sexual transmission
stage
Cost variables
14 variables
(continuous)
Changes in disease
end points after
vaccine introduction
Economic stage
Changes in the
economic burden
(cost and quality of
life)
Distribution of
incremental
cost
effectiveness
ratios
Economic
evaluation
50,000
samples
Duration of
vaccine
protection
3 scenarios
(10, 20, 
years)
QALY
variables
14 variables
(continuous)
Model
parameter
variables
9 variables
(continuous)
Natural history
stage
Progression and
regression rates
Sexual transmission
stage
Changes in disease
end points after
vaccine introduction
Economic stage
Changes in the
economic burden
(cost and quality of
life)
Jit M, Choi YH, Edmunds WJ. Economic evaluation of human papillomavirus vaccination in
the United Kingdom. BMJ 2008; 337:a769.
Some relevant issues that were raised
during this work
When is uncertainty structural rather than
parametric?
How should different structural scenarios be
weighed or selected?
How can we improve the computational
efficiency of structural uncertainty analysis?