Cost-effectiveness of tiotropium in patients with asthma poorly controlled on inhaled glucocorticosteroids
and long-acting beta-agonists
Technical appendix
1 WinBUGS model for computation of transitions
A sample of 793 patients with complete sets of ACQ data was used to construct model transition probabilities
representing 87% of the 912 patients enrolled in the PrimoTinA-asthma® trials. To obtain the model transition
probabilities imputation methods were used to assign each patient to either an asthma control state (controlled
asthma, partly controlled asthma or uncontrolled asthma) or to one of three asthma exacerbation health states
each week throughout the 48 week trial period. These methods have been described in the main text of this
article.
Once this 48-week health state dataset had been created Bayesian methods were used to derive weekly transition
probabilities. Two sets of weekly transition probabilities were computed; one set reflected weekly transitions
over week 0 to 8 in the trial and one reflected weekly transition over week 9 to 48 in the trial.
WinBUGS (version 1.4) was used to compute the model transition probabilities. WinBUGS is a statistical
software for Bayesian analysis using Markov chain Monte Carlo methods. Table 1 presents the code for the
WinBUGS model. ‘## Model’ indicates the start and ‘## End of Model’ indicates the last code. Following that
the data used in the model is listed. The model was compiled with two chains; inits for these were generated by
WinBUGS. The p.plac node or the p.tio node was monitored. The model was run with 50,000 simulations (plus
a burn-in of 20,000). Convergence was confirmed visually.
Table 1: WinBUGS model
WinBUGS model
## MODEL
#
Model is based on Briggs, Ades and Price (Medical Decision Making
(2003);23:341-350)
model{
## Multinomial distribution for r,
## i = 6 for non-absorbing states
for (i in 1 : 6){
r.tio[i, 1:6] ~ dmulti(p.tio[i, 1:6], n.tio[i])
r.plac[i, 1:6] ~ dmulti(p.plac[i, 1:6], n.plac[i])
}
## Dirchlet prior distributions for the transition probabilities
for(i in 1:6){
p.tio[i, 1:6] ~ ddirch(prior.tio[i, 1:6])
p.plac[i, 1:6] ~ ddirch(prior.plac[i, 1:6])
}
}
## End of model
##DATA – From Trial 416 day 56 (placebo)a
list(
r.plac=structure(.Data=c(96, 0, 0, 1, 2,
3, 162, 1, 5, 1,
20, 28, 1172, 26, 12,
3, 3, 22, 4, 1,
2, 0, 9, 0, 13,
1, 0, 1, 0, 0),.Dim=c(6,6)),
n.plac=c(99, 172, 1260, 33, 24, 4),
prior.plac=structure(.Data=c(1,1,1,1,1,1,
1,1,1,1,1,1,
1,1,1,1,1,1,
1,1,1,1,1,1,
1,1,1,1,1,1,
1,1,1,1,1,1),.Dim=c(6,6)),
)
## End of Data
a
Example for placebo data from trial 416 for the first 8 weeks.
2 Model transition probabilities
The two transition matrices (“early response phase” and “late response phase”) are presented inTable 2 and
Table 3 for the tiotropium and usual care arm respectively.
Ta ble 2 : M o del t ra ns it i o n pro ba b il iti es , tio t ro pi u m a r m
Partly
to
Controlled
controlled Uncontrolled
Non-severe
From
asthma
asthma
exacerbation
asthma
Day 0-56 “Early response phase”
Controlled
0.945
asthma
Partly
controlled
0.057
asthma
Severe
exacerbation without
hospitalisation
Severe
exacerbation –
with
hospitalisation
0.004
0.008
0.025
0.013
0.004
0.889
0.025
0.020
0.007
0.002
to
From
Controlled
asthma
Partly
controlled
asthma
Uncontrolled
0.018
asthma
Non-severe
0.110
exacerbation
Severe
exacerbation 0.041
without
hospitalisation
Severe
exacerbation –
0.166
with
hospitalisation
Day 57-336 “Late response phase”
Controlled
0.954
asthma
Partly
controlled
0.029
asthma
Uncontrolled
0.006
asthma
Non-severe
0.081
exacerbation
Severe
exacerbation 0.097
without
hospitalisation
Severe
exacerbation –
0.062
with
hospitalisation
Table 3:
From
Uncontrolled
asthma
Non-severe
exacerbation
Severe
exacerbation without
hospitalisation
Severe
exacerbation –
with
hospitalisation
0.022
0.930
0.021
0.008
0.000
0.069
0.616
0.137
0.055
0.014
0.042
0.417
0.042
0.437
0.021
0.167
0.167
0.167
0.166
0.167
0.019
0.010
0.010
0.007
0.000
0.913
0.033
0.019
0.005
0.002
0.016
0.939
0.030
0.010
0.001
0.092
0.576
0.237
0.009
0.004
0.078
0.292
0.019
0.510
0.004
0.125
0.281
0.063
0.031
0.438
Severe
exacerbation without
hospitalisation
Severe
exacerbation –
with
hospitalisation
M o del t ra n si t i o n pro ba b il iti es , u s ua l ca re a r m
Partly
to
Controlled
controlled Uncontrolled
Non-severe
asthma
asthma
exacerbation
asthma
Day 0-56 “Early response phase”
Controlled
0.950
asthma
Partly
controlled
0.030
asthma
Uncontrolled
0.015
asthma
Non-severe
0.060
exacerbation
0.006
0.006
0.017
0.017
0.006
0.875
0.034
0.041
0.017
0.002
0.023
0.927
0.025
0.009
0.001
0.107
0.631
0.143
0.036
0.024
to
From
Controlled
asthma
Partly
controlled
asthma
Severe
exacerbation 0.083
without
hospitalisation
Severe
exacerbation –
0.167
with
hospitalisation
Day 57-336 “Late response phase”
Controlled
0.943
asthma
Partly
controlled
0.031
asthma
Uncontrolled
0.005
asthma
Non-severe
0.123
exacerbation
Severe
exacerbation 0.066
without
hospitalisation
Severe
exacerbation –
0.118
with
hospitalisation
Uncontrolled
asthma
Non-severe
exacerbation
Severe
exacerbation without
hospitalisation
Severe
exacerbation –
with
hospitalisation
0.063
0.292
0.042
0.500
0.021
0.083
0.250
0.083
0.084
0.333
0.015
0.008
0.023
0.010
0.001
0.901
0.027
0.030
0.009
0.001
0.011
0.933
0.037
0.012
0.001
0.107
0.551
0.208
0.009
0.002
0.061
0.352
0.017
0.499
0.006
0.029
0.294
0.088
0.030
0.441
3. Parameter ranges used in the one way sensitivity analyses
The impact of variation in the health state cost, rescue medication cost and utility parameters was tested in the
one-way sensitivity analysis.
The health state cost and rescue medication cost have been calculated by multiplying the relevant elements of
resource use by their unit costs. A lower and an upper bound were fitted around these variables by varying each
elements of resource use within its 95% confidence interval but assuming unit costs remain constant. For the
utility parameters the 95% confidence interval was calculated from the trial data and this is used as the lower
and upper bound for the one-way sensitivity analysis input.
Ta ble 4 : Pa ra me t er ra n g es u se d i n t he o n e - w a y se n sit iv ity a na ly s i s
Parameter
Health state cost
Base case value
Lower bound
Upper bound
Parameter
Health state costs, controlled asthma, per
cycle
Health state costs, partly controlled
asthma, per cycle
Health state costs, uncontrolled asthma, per
cycle
Health state costs, non-severe
exacerbation, per cycle
Health state costs, severe exacerbations
without hospitalisation, per cycle
Health state costs, severe exacerbations
with hospitalisation, per cycle
Utilities
Base case value
Lower bound
Upper bound
7.18
1.92
41.56
11.61
2.95
57.48
41.80
17.89
98.34
65.58
40.99
113.31
83.50
64.99
109.65
1,021.33
620.35
1,550.45
Utility for controlled asthma state
0.937
0.923
0.952
Utility for partly controlled asthma state
Utility for uncontrolled asthma state
Utility for mild/moderate exacerbation
state
Utility for severe exacerbations without
hospitalisation state
Utility for severe exacerbations with
hospitalisation state
Rescue medication cost
Rescue medication costs, controlled
asthma, per cycle, Tiotropium
Rescue medication costs, partly controlled
asthma, per cycle, Tiotropium
Rescue medication costs, uncontrolled
asthma, per cycle, Tiotropium
Rescue medication costs, non-severe
exacerbation, per cycle, Tiotropium
Rescue medication costs, severe
exacerbations without hospitalisation, per
cycle, Tiotropium
Rescue medication costs, severe
exacerbations with hospitalisation, per
cycle, Tiotropium
Rescue medication costs, controlled
asthma, per cycle, Usual Care
Rescue medication costs, partly controlled
asthma, per cycle, Usual Care
Rescue medication costs, uncontrolled
asthma, per cycle, Usual Care
Rescue medication costs, non-severe
exacerbation, per cycle, Usual Care
Rescue medication costs, severe
exacerbations without hospitalisation, per
cycle, Usual Care
0.907
0.728
0.879
0.707
0.934
0.749
0.649
0.584
0.714
0.570
0.513
0.627
0.330
0.297
0.363
0.06
0.05
0.06
0.08
0.07
0.08
0.15
0.14
0.15
0.17
0.14
0.19
0.20
0.17
0.23
0.21
0.19
0.23
0.06
0.05
0.06
0.09
0.08
0.09
0.17
0.16
0.18
0.15
0.13
0.17
0.22
0.19
0.25
Parameter
Rescue medication costs, severe
exacerbations with hospitalisation, per
cycle, Usual Care
Base case value
Lower bound
Upper bound
0.21
0.19
0.23
4 Distributions around model parameters used in probabilistic
sensitivity analyses
The impact of uncertainty in health state related resource use, rescue medication resource use, utilities and
model transition probabilities was tested in the probabilistic sensitivity analysis,
The efficacy parameters take the form of a transition matrix where there are 36 possible transitions. All
transitions are therefore inter-related due to the nature of the transition matrix structure. Due to this interdependence, the uncertainty around the transition probabilities in the transition matrix was captured in the model
by using a Dirichlet distribution. As there is no built-in function for the Dirichlet distribution in Excel, it was
approximated using a Gamma distribution (or a Normal distribution in cases where the number of patient
transitions were more than 340) as described by Briggs et al. 2003 1. The six possible transitions from each
health state were based on observed patient numbers in the RCT data which were subsequently divided by the
row sum of all six transitions to derive the transition probability. The numbers of transitions (rather than the
probabilities) were sampled in the probabilistic sensitivity analysis, and the probability was again then computed
by dividing by the row sum of all six possible transitions from each health state. Each transition approximated
using the Gamma distribution had an alpha parameter which was equal to the ‘number of transitions that had
been observed in the trial plus 1’ and beta was set to ‘1’. The transitions approximated by the Normal
distribution were specified using the mean, which was equal to the number of transitions observed, and the
standard deviation, which was the square root of the number of transitions observed. Thus, the degree of
uncertainty in the Dirichlet distribution directly depends on the number of transitions observed in the trial as
well as the total number of transitions from one particular health state. Table 5 and Table 6 display each
1
Briggs AH, Ades AE, Price MJ. Probabilistic sensitivity analysis for decision trees with multiple branches: use of the
Dirichlet distribution in a Bayesian framework. Med Decis Making 2003; 23(4):341-50.
transition probability alongside the parameters of the distributions used to sample the associated number of
transitions for the tiotropium and usual care arms respectively.
The uncertainty in cost estimates was captured by uncertainties in resource use while the unit costs of the
resources were assumed to be fixed. Distributions were fitted around the elements of resource use used to
calculate the health state specific costs and rescue medication costs. Distributional information was available
because resource use parameters were either obtained from the survey of 15 health care providers or from the
RCT data. The Lognormal distribution was used to represent the uncertainty in outpatient visit (Table 7), home
visit (Table 8), test and procedure resource use (Table 9) and rescue medication use (Table 12) variables. The
beta distribution was used to represent uncertainty in co-medication use (Table 10) and hospitalisation resource
use (Table 11). A beta distribution was fitted to the utility parameters (Table 13).
Ta ble 5 : M o del t ra ns it i o n pro ba b il iti es a n d di str ib ut io na l i nfo r ma t io n , t io tro pi u m
arm
Partly
to
Severe
Severe
Controlled controlled Uncontrolled
Non-severe exacerbation
exacerbation
From
asthma
asthma
exacerbation
- without
asthma
– with hosp.
hosp.
Day 0-56 “Early response phase”
Probability
0.945
0.004
0.008
0.025
0.013
0.004
Controlled
Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
asthma
Distribution
α: 224 β:
α: 1 β: 1
α: 2 β: 1
α: 6 β: 1
α: 3 β: 1
α: 1 β: 1
parameters
1
Probability
0.057
0.889
0.025
0.020
0.007
0.002
Partly
Distribution
Gamma
Normal
Gamma
Gamma
Gamma
Gamma
controlled
Distribution
μ: 391
asthma
α: 25 β: 1
α: 11 β: 1
α: 9 β: 1
α: 3 β: 1
α: 1 β: 1
parameters
sd:19.8
Probability
0.018
0.022
0.930
0.021
0.008
0.000
Uncontrolled Distribution
Gamma
Gamma
Normal
Gamma
Gamma
Gamma
asthma
Distribution
μ: 2223 sd:
α: 43 β: 1
α: 52 β: 1
α: 51 β: 1
α: 20 β: 1
α: 1 β: 1
parameters
47.1
Probability
0.110
0.069
0.616
0.137
0.055
0.014
Non-severe
Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
exacerbation Distribution
α: 8 β: 1
α: 5 β: 1
α: 45 β: 1
α: 10 β: 1
α: 4 β: 1
α: 1 β: 1
parameters
Probability
0.041
0.042
0.417
0.042
0.437
0.021
Severe
exacerbation Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
- without
Distribution
α: 2 β: 1
α: 2 β: 1
α: 20 β: 1
α: 2 β: 1
α: 21 β: 1
α: 1 β: 1
hosp.
parameters
Probability
0.166
0.167
0.167
0.167
0.166
0.167
Severe
Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
exacerbation
Distribution
– with hosp.
α: 1 β: 1
α: 1 β: 1
α: 1 β: 1
α: 1 β: 1
α: 1 β: 1
α: 1 β: 1
parameters
to
From
Controlled
asthma
Partly
controlled
asthma
Uncontrolled
asthma
Non-severe
exacerbation
Severe
exacerbation
- without
hosp.
Severe
exacerbation
– with hosp.
Day 57-336 “Late response phase”
Probability
0.954
0.019
0.010
0.010
0.007
0.000
Controlled
Distribution
Normal
Gamma
Gamma
Gamma
Gamma
Gamma
asthma
Distribution
μ: 3448
α: 70 β: 1
α: 36 β: 1
α: 35 β: 1
α: 26 β: 1
α: 1 β: 1
parameters
sd: 58.7
Probability
0.029
0.913
0.033
0.019
0.005
0.002
Partly
Distribution
Gamma
Normal
Gamma
Gamma
Gamma
Gamma
controlled
Distribution
μ: 2679
asthma
α: 84 β: 1
α: 97 β: 1
α: 55 β: 1
α: 14 β: 1
α: 5 β: 1
parameters
sd: 51.8
Probability
0.006
0.016
0.939
0.030
0.010
0.001
Uncontrolled Distribution
Gamma
Gamma
Normal
Gamma
Gamma
Gamma
asthma
Distribution
α: 133 β:
μ: 8014 sd:
α: 49 β: 1
α: 252 β: 1
α: 82 β: 1
α: 9 β: 1
parameters
1
89.5
Probability
0.081
0.092
0.576
0.237
0.009
0.004
Non-severe
Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
exacerbation Distribution
α: 37 β: 1
α: 42 β: 1
α: 262 β: 1
α: 108 β: 1
α: 4 β: 1
α: 2 β: 1
parameters
Probability
0.097
0.078
0.292
0.019
0.510
0.004
Severe
exacerbation Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
- without
Distribution
α: 25 β: 1
α: 20 β: 1
α: 75 β: 1
α: 5 β: 1
α: 131 β: 1
α: 1 β: 1
hosp.
parameters
Probability
0.062
0.125
0.281
0.063
0.031
0.438
Severe
Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
exacerbation
Distribution
– with hosp.
α: 2 β: 1
α: 4 β: 1
α: 9 β: 1
α: 2 β: 1
α: 1 β: 1
α: 14 β: 1
parameters
Source: PrimoTinA-asthma® clinical trials.
α: alpha parameter of gamma distribution, β: beta parameter of gamma distribution, μ: mean of normal distribution, sd:
standard deviations, hosp.: hospitalisation.
Ta ble 6 : M o del t ra ns it i o n pro ba b il iti es a n d di str ib ut io na l i nfo r ma t io n, us ua l ca r e
arm
Partly
to
Severe
Severe
Controlled controlled Uncontrolled
Non-severe exacerbation
exacerbation
From
asthma
asthma
exacerbation
- without
asthma
– with hosp.
hosp.
Day 0-56 “Early response phase”
Probability
0.950
0.006
0.006
0.017
0.017
0.006
Controlled
Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
asthma
Distribution
α: 170 β:
α: 1 β: 1
α: 1 β: 1
α: 3 β: 1
α: 3 β: 1
α: 1 β: 1
parameters
1
Probability
0.030
0.875
0.034
0.041
0.017
0.002
Partly
Distribution
Gamma
Normal
Gamma
Gamma
Gamma
Gamma
controlled
Distribution
μ: 406 sd:
asthma
α: 14 β: 1
α: 16 β: 1
α: 19 β: 1
α: 8 β: 1
α: 1 β: 1
parameters
20.1
Probability
0.015
0.023
0.927
0.025
0.009
0.001
Uncontrolled
asthma
Distribution
Gamma
Gamma
Normal
Gamma
Gamma
Gamma
to
From
Controlled
asthma
Partly
controlled
asthma
Uncontrolled
asthma
Non-severe
exacerbation
Severe
exacerbation
- without
hosp.
Severe
exacerbation
– with hosp.
Distribution
μ: 2253 sd:
α: 36 β: 1
α: 57 β: 1
α: 61 β: 1
α: 21 β: 1
α: 3 β: 1
parameters
47.5
Probability
0.060
0.107
0.631
0.143
0.036
0.024
Non-severe
Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
exacerbation
Distribution
α: 5 β: 1
α: 9 β: 1
α: 53 β: 1
α: 12 β: 1
α: 3 β: 1
α: 2 β: 1
parameters
Probability
0.083
0.063
0.292
0.042
0.500
0.021
Severe
exacerbation
Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
- without
Distribution
α: 4 β: 1
α: 3 β: 1
α: 14 β: 1
α: 2 β: 1
α: 24 β: 1
α: 1 β: 1
hosp.
parameters
Probability
0.167
0.083
0.250
0.083
0.084
0.333
Severe
Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
exacerbation
Distribution
– with hosp.
α: 2 β: 1
α: 1 β: 1
α: 3 β: 1
α: 1 β: 1
α: 1 β: 1
α: 4 β: 1
parameters
Day 57-336 “Late response phase”
Probability
0.954
0.019
0.010
0.010
0.007
0.000
Controlled
Distribution
Normal
Gamma
Gamma
Gamma
Gamma
Gamma
asthma
Distribution
μ: 3081
α: 49 β: 1
α: 26 β: 1
α: 75 β: 1
α: 32 β: 1
α: 4 β: 1
parameters
sd: 55.5
Probability
0.029
0.913
0.033
0.019
0.005
0.002
Partly
Distribution
Gamma
Normal
Gamma
Gamma
Gamma
Gamma
controlled
Distribution
μ: 2233
asthma
α: 78 β: 1
α: 68 β: 1
α: 75 β: 1
α: 22 β: 1
α: 3 β: 1
parameters
sd: 47.3
Probability
0.006
0.016
0.939
0.030
0.010
0.001
Uncontrolled
Distribution
Gamma
Gamma
Normal
Normal
Gamma
Gamma
asthma
Distribution
α: 104 β:
μ: 8556 sd:
μ: 340 sd:
α: 44 β: 1
α: 114 β: 1
α: 10 β: 1
parameters
1
92.5
18.4
Probability
0.081
0.092
0.016
0.237
0.009
0.004
Non-severe
Distribution
Gamma
Gamma
Normal
Gamma
Gamma
Gamma
exacerbation
Distribution
μ: 354 sd:
α: 79 β: 1
α: 69 β: 1
α: 134 β: 1
α: 6 β: 1
α: 1 β: 1
parameters
18.8
Probability
0.097
0.078
0.292
0.019
0.510
0.004
Severe
exacerbation
Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
- without
Distribution
α: 24 β: 1
α: 22 β: 1
α: 127 β: 1
α: 6 β: 1
α: 180 β: 1
α: 2 β: 1
hosp.
parameters
Probability
0.062
0.125
0.281
0.063
0.031
0.438
Severe
Distribution
Gamma
Gamma
Gamma
Gamma
Gamma
Gamma
exacerbation
Distribution
– with hosp.
α: 4 β: 1
α: 1 β: 1
α: 10 β: 1
α: 3 β: 1
α: 1 β: 1
α: 15 β: 1
parameters
Source: PrimoTinA-asthma® clinical trials.
α: alpha parameter of gamma distribution, β: beta parameter of gamma distribution, μ: mean of normal distribution, sd:
standard deviations, hosp.: hospitalisation.
Ta ble 7 : O ut pa t ie nt v i s it v a r ia b le s te st ed i n P SA
Variable
Applied distribution
Expected mean
Standard deviation
Variable
Applied distribution
Expected mean
Standard deviation
Outpatient visits: GP, controlled asthma,
per cycle
Lognormal
0.031
0.0382
Outpatient visits: GP, partly controlled
asthma, per cycle
Lognormal
0.039
0.0452
Outpatient visits: GP, uncontrolled asthma,
per cycle
Lognormal
0.138
0.1397
Outpatient visits: GP, non-severe
exacerbation, per exacerbation
Lognormal
0.597
0.4775
Outpatient visits: GP, severe exacerbation
without hospitalisation, per exacerbation
Lognormal
1.367
0.8013
Outpatient visits: GP, severe exacerbation
with hospitalisation, per exacerbation
Lognormal
0.590
0.4936
Outpatient visits: nurse, controlled asthma,
per cycle
Lognormal
0.050
0.0414
Outpatient visits: nurse, partly controlled
asthma, per cycle
Lognormal
0.068
0.0497
Outpatient visits: nurse, uncontrolled
asthma, per cycle
Lognormal
0.158
0.2060
Outpatient visits: nurse, non-severe
exacerbation, per exacerbation
Lognormal
0.430
0.4199
Lognormal
0.903
0.7316
Lognormal
1.380
1.7493
Outpatient visits: specialist, controlled
asthma, per cycle
Lognormal
0.016
0.0209
Outpatient visits: specialist, partly
controlled asthma, per cycle
Lognormal
0.033
0.0414
Outpatient visits: specialist, uncontrolled
asthma, per cycle
Lognormal
0.094
0.0930
Outpatient visits: specialist, non-severe
exacerbation, per exacerbation
Lognormal
0.094
0.1613
Lognormal
0.339
0.5004
Expected mean
Standard deviation
Outpatient visits: nurse, severe
exacerbation without hospitalisation, per
exacerbation
Outpatient visits: nurse, severe
exacerbation with hospitalisation, per
exacerbation
Outpatient visits: specialist, severe
exacerbation without hospitalisation, per
exacerbation
Source: Survey of UK HCPs (IMS Health)
Table 8: Home visit variables tested in PSA
Variable
Applied distribution
Variable
Applied distribution
Expected mean
Standard deviation
Home visits: GP, controlled asthma, per
cycle
Lognormal
0.001
0.0008
Home visits: GP, partly controlled asthma,
per cycle
Lognormal
0.010
0.0258
Home visits: GP, uncontrolled asthma, per
cycle
Lognormal
0.025
0.0551
Home visits: GP, non-severe exacerbation,
per exacerbation
Lognormal
0.034
0.1027
Home visits: GP, severe exacerbation
without hospitalisation, per exacerbation
Lognormal
0.220
0.3730
Home visits: GP, severe exacerbation with
hospitalisation, per exacerbation
Lognormal
0.102
0.1733
Home visits: nurse, uncontrolled asthma,
per cycle
Lognormal
0.001
0.0020
Home visits: nurse, severe exacerbation
without hospitalisation, per exacerbation
Lognormal
0.003
0.0129
Home visits: nurse, severe exacerbation
with hospitalisation, per exacerbation
Lognormal
0.005
0.0136
Source: Survey of UK HCPs (IMS Health)
Nurse home visits for the following health states were not sampled in the PSA, as no events were assumed to occur in
the base case: controlled asthma, partly controlled asthma, non-severe exacerbation.
Table 9: Test and procedure resource use variables tested in PSA
Variable
Applied distribution
Expected mean
Standard deviation
Spirometry tests: controlled asthma, per
cycle
Lognormal
0.026
0.0331
Spirometry tests: partly controlled asthma,
per cycle
Lognormal
0.028
0.0329
Spirometry tests: uncontrolled asthma, per
cycle
Lognormal
0.049
0.0422
Spirometry tests: non-severe exacerbation,
per exacerbation
Lognormal
0.287
0.4486
Spirometry tests: severe exacerbation
without hospitalisation, per exacerbation
Lognormal
0.288
0.4477
Spirometry tests: severe exacerbation with
hospitalisation, per exacerbation
Lognormal
0.463
0.6061
Desensitisation of asthma use: controlled
asthma, per cycle
Lognormal
0.005
0.02
Desensitisation of asthma use: partly
controlled asthma, per cycle
Lognormal
0.008
0.02
Variable
Desensitisation of asthma use:
uncontrolled asthma, per cycle
Applied distribution
Expected mean
Standard deviation
Lognormal
0.009
0.02
Source: Survey of UK HCPs (IMS Health)
Flu vaccination was not sampled in the PSA, as it was assumed that patients receive one flu vaccination per year.
Table 10: Co-medication use variables tested in the PSA
Applied
distribution
Expected mean
Alpha
Beta
Prednisolone use: controlled asthma, per
cycle, per patient
Beta
0.290
29
71
Prednisolone use: partly controlled
asthma, per cycle, per patient
Beta
0.340
34
66
Prednisolone use: uncontrolled asthma, per
cycle, per patient
Beta
0.510
51
49
Prednisolone use: non-severe
exacerbation, per exacerbation, per patient
Beta
0.570
57
43
Beta
0.810
81
19
Beta
0.870
87
13
Amoxicillin use: uncontrolled asthma, per
cycle, per patient
Beta
0.300
30
70
Amoxicillin use: non-severe exacerbation,
per exacerbation, per patient
Beta
0.540
54
46
Beta
0.710
71
29
Beta
0.700
70
30
Beta
0.830
83
17
Beta
0.810
81
19
Beta
0.740
74
26
Variable
Prednisolone use: severe exacerbation
without hospitalisation, per exacerbation,
per patient
Prednisolone use: severe exacerbation
with hospitalisation, per exacerbation, per
patient
Amoxicillin use: severe exacerbation
without hospitalisation, per exacerbation,
per patient
Amoxicillin use: severe exacerbation with
hospitalisation, per exacerbation, per
patient
Singulair use: uncontrolled asthma, per
cycle, per patient
Hydrocortisone IV use: severe
exacerbation with hospitalisation, per
exacerbation, per patient
Magnesium IV: severe exacerbation with
hospitalisation, per exacerbation, per
patient
Source: Survey of UK HCPs (IMS Health)
IV: Intravenous
Table 11: Hospitalisation and hospital related resource use parameters tested in
the PSA
Applied
distribution
Expected mean
Alpha
Beta
Beta
0.003%
2
1224
Beta
0.004%
2
1100
Beta
0.006%
12
4094
Beta
39.1%
18
28
A&E visits + hospitalisation, per
exacerbation, per patient
Beta
41.3%
19
27
Ambulance use with hospitalisation, per
exacerbation, per patient
Beta
2.2%
1
45
Ambulance use with A&E visit and
hospitalisation, per exacerbation, per
patient
Beta
4.3%
2
44
Hospitalisations incl. ICU stay, per
exacerbation, per patient
Beta
13.0%
6
40
Beta
5.8%
28
451
Variable
Asthma related unscheduled
hospitalisations: controlled asthma, per
cycle, per patient
Asthma related unscheduled
hospitalisations: partly controlled asthma,
per cycle, per patient
Asthma related unscheduled
hospitalisations: uncontrolled asthma, per
cycle, per patient
Regular hospitalisations: severe
exacerbation with hospitalisation, per
exacerbation, per patient
A&E visits, severe exacerbation without
hospitalisation, per exacerbation, per
patient
Source: PrimoTinA-asthma® clinical trials.
A&E: Accident and emergency department
Table 12: Rescue medication use variables tested in PSA
Variable
Applied distribution
Expected mean
Standard error
Rescue medication use, controlled asthma,
per day, Tiotropium
Lognormal
1.12
0.04
Rescue medication use, partly controlled
asthma, per day, Tiotropium
Lognormal
1.51
0.05
Rescue medication use, uncontrolled
asthma, per day, Tiotropium
Lognormal
2.81
0.07
Rescue medication use, non-severe
exacerbation, per day, Tiotropium
Lognormal
3.23
0.24
Lognormal
3.83
0.28
Lognormal
3.97
0.21
Rescue medication use, severe
exacerbations without hospitalisation, per
day, Tiotropium
Rescue medication use, severe
exacerbations with hospitalisation, per
day, Tiotropium
Variable
Applied distribution
Expected mean
Standard error
Rescue medication use, controlled asthma,
per day, Usual care
Lognormal
1.11
0.05
Rescue medication use, controlled asthma,
per day, Usual care
Lognormal
1.65
0.06
Rescue medication use, uncontrolled
asthma, per day, Usual care
Lognormal
3.26
0.08
Rescue medication use, non-severe
exacerbation, per day, Usual care
Lognormal
2.90
0.21
Lognormal
4.22
0.29
Lognormal
3.97
0.21
Rescue medication use, severe
exacerbations without hospitalisation, per
day, Usual care
Rescue medication use, severe
exacerbations with hospitalisation, per
day, Usual care
Source: PrimoTinA-asthma® clinical trials.
Table 13: Utility variables tested in PSA
Applied
distribution
Expected
mean
Standard
error
alpha
beta
Source
Utility for controlled
asthma state
Beta
0.937
0.0075
982.39
66.05
PrimoTinAasthma®
clinical trials
Utility for partly controlled
asthma state
Beta
0.907
0.0142
378.51
38.81
PrimoTinAasthma®
clinical trials
Utility for uncontrolled
asthma state
Beta
0.728
0.0109
1212.60
453.06
PrimoTinAasthma®
clinical trials
Utility for non-severe
exacerbation state
Beta
0.649
0.0109a
1251.35
676.77
Assumption
Utility for severe
exacerbation without
hospitalisation state
Beta
0.570
0.0109a
1182.54
892.09
Lloyd et al.,
2007b
Variable
Utility for severe
Lloyd et al.,
exacerbation with
Beta
0.330
0.0109a
617.56
1253.83
2007b
hospitalisation state
a
Standard error was not available. Hence the average standard error across the utility parameters for asthma control
states was used as approximation for the exacerbation states.
b
Lloyd A, Price D, Brown R. The impact of asthma exacerbations on health-related quality of life in moderate to
severe asthma patients in the UK. Prim Care Respir J 2007; 16(1):22-7.
5 Resource use questionnaire
Note: The cost-effectiveness model health state names used throughout the questionnaire document are different to those
used in the main text of this article; however the definition of the six health states remains consistent. ‘Optimal control’
corresponds to the ‘controlled asthma’ health state and ‘acceptable control’ corresponds to the ‘partly controlled’ health
state.
Resource used questionnaire sent to 15 UK based health care providers:
Dear <name of GP/nurse/specialist>,
Thank you very much for agreeing to participate in our survey.
Background to this survey:
A health economic model was developed to assess the cost-effectiveness of a controller therapy as an add-on therapy on
top of usual care (i.e. high dose inhaled corticosteroids plus long-acting Beta agonists) versus usual care alone in adult
patients with severe persistent asthma in the UK. The definition of severe asthma is presented in Table 14.
Table 14: Definition of asthma s everity
Definition of severe asthma
Patients receiving

high-dose inhaled corticosteroids

and a long-acting beta-2 agonist
 with or without an oral corticosteroid or omalizumab
(refers to BTS/SIGN step 4-5)
BTS = British Thoracic Society; SIGN = Scottish Intercollegiate Guidelines Network.
Source: British Guideline on the Management of Asthma, URL: http://www.sign.ac.uk/pdf/sign101.pdf
Seven model states were defined: 1) Optimal asthma control; 2) Acceptable asthma control; 3) Uncontrolled asthma; 4)
Non-severe exacerbation; 5) Severe exacerbation - without hospitalisations; 6) Severe exacerbation - with hospital-related
resource use; and 7) Death (Figure 1). Please note that the health states are mutually exclusive.
Figure 1: Cost-effectiveness model structure
The model enables to simulate the long-term costs and health outcomes in a cohort of adult asthma patients and to
perform the comparative assessment of cost and health outcomes of asthma treatments. It is expected that the additional
controller therapy would increase the degree of control of the symptoms and both keep patients’ asthma under control and
reduce the frequency of asthma exacerbations. Treatment efficacy in the model is therefore defined as a reduction in
(severe) exacerbations and an improvement of asthma control, measured via the Asthma Control Questionnaire (ACQ).
Health states are defined as follows Table 15:
Table 15: Health states defined in the asthma cost -effectiveness model
Health state
Definition
A. Patients without exacerbations
Optimal asthma control
Patients with an ACQ-6 score <1.0
Acceptable asthma control
Patients with an ACQ-6 score ≥1.0 and <1.5
Uncontrolled asthma
Patients with an ACQ-6 score ≥1.5
B. Patients with exacerbations
Mild/moderate exacerbation
A mild/moderate exacerbation is an episode of progressive increase in one or more
asthma symptoms, like shortness of breath, cough, wheezing, or chest tightness, or
some combination of these symptoms. The symptoms are outside the patient’s
usual range of day-to-day asthma and last for at least 2 consecutive days and/or a
decrease of patient’s best morning PEF of ≥ 30% from the patient’s mean morning
PEF for at least 2 consecutive days.
Severe exacerbation without
hospital-related resource use
A severe exacerbation without hospitalisation is an exacerbation according to the
above definition but also requiring an initiation of treatment with systemic
(including oral) corticosteroids for at least 3 days or, in case of ongoing and preexisting systemic corticosteroid therapy, requiring at least doubling of previous
daily doses of systemic corticosteroids for at least 3 days. No hospitalisation is
required.
Severe exacerbation with hospitalrelated resource use
As for severe exacerbation without hospitalisation but patients additionally require
a hospitalisation with at least one overnight stay.
Model input data were derived from the following sources:

Clinical treatment efficacy data were obtained from phase III randomised clinical trials.

Health related utilities associated with different model states were defined using the EQ-5D2.

Inpatient resource usage, namely additional resources associated with severe exacerbations and the frequency of
asthma-related hospitalisations of patients in different asthma control states, as well as rescue medication usage
(salbutamol) could be taken from the phase III clinical trials.
Outpatient resource use in UK clinical practice associated with the three asthma control states and the three exacerbation
states was neither available from the published literature nor from the clinical trials and hence should be estimated by
UK-based health care providers for asthma patients
Objective of survey/ what we are asking you to do:
This survey is conducted to fill the gap regarding outpatient medical resource use information.
Outpatient resource use includes

Outpatient visits,

Home visits,

Tests and Procedures conducted (e.g. Spirometry test or a vaccination) – this also would include training or
monitoring or asthma management programmes, and

Co-medication prescribed. Please note that we do not seek input in ‘background medication’ (including stable
maintenance treatment of at least high dose ICS and LABA) or rescue medication (number of puffs of
salbutamol)). Instead we would ask you to think of most frequently prescribed co-medication associated with the
patients’ condition, especially the co-medication required during exacerbations (e.g. systemic corticosteroids, or
i.v. antibiotic treatment).
We are further keen to learn how many workdays (in fully employed persons) are approximately lost due to the patients’
condition.
The information collected in this survey will be used to inform the resource use inputs to the cost-effectiveness study.
Guidance on answering the questions:
This questionnaire contains two sections:

Section A. Patients without exacerbations

Section B. Patients with exacerbations
Section A. Patients without exacerbations:
2
The EQ-5D™ is a standardised instrument for use as a measure of health outcomes. For more information, please refer to URL:
http://www.euroqol.org.
To estimate the outpatient resource use, please think of 100 adult patients who are not adequately controlled: Which
medical resources are at average consumed by those patients per quarter (3 months)?
Please imagine that these patients remain in this asthma-control state for a quarter, i.e. the asthma does not
improve/worsen nor does the patient experience an exacerbation.
Example: If 70% of the patients who are optimally controlled (health state #1) usually see the GP once every 3 months
and 50% of the patients also see a nurse once every month, please fill in as:
Table 16: EXAMPLE
Optimal asthma control
Number of patients (out of 100)
Resource use (number)
Outpatient visits
Visits to GP
Visits to nurse
…
70
50
…
1 (once per quarter)
3 (once every month of a quarter)
…
Section B. Patients with exacerbations:
To estimate the outpatient resource use, please think of 100 adult patients: Which medical resources are at average
consumed by those patients as a result of the exacerbation event?
Please note that whilst the trials have given us data on the frequency of ER visits and hospitalisations, we are seeking
specific input into procedures that may typically occur during such an event (such as an intubation or the administration
of i.v. antibiotics). In addition, we are looking for input into the outpatient resource use associated with an exacerbation
(e.g. follow-up visits during the weaning of oral corticosteroids, if appropriate). Please estimate the resource utilisation
based on your experience.
Thank you very much in advance for your valuable input.
A. Patients without exacerbations:
Please think of 100 adult patients with severe asthma who are not adequately controlled: Which medical resources are at average consumed by those
patients per quarter (3 months)?
Table 17: Patients without exacerbations
Optimal asthma control
Resource use
Number of
(number per
patients
patient and
(out of 100)
quarter)
Outpatient visits
Visits to GP
Visits to nurse
Visits to specialist:
______________
(please specify specialist)
Visits to ‘other’:
______________
(please specify)
Home visits
GP visits
Nurse visits
Visits by a specialist:
______________
(please specify specialist)
Visits by ‘other’:
______________
(please specify)
Tests and procedures
Spirometry test
Acceptable asthma control
Resource use
Number of
(number per
patients
patient and
(out of 100)
quarter)
Uncontrolled asthma
Resource use
Number of
(number per
patients
patient and
(out of 100)
quarter)
Vaccination:
______________
(please specify)
Desensitisation for allergic
asthma
Other:
______________
(please specify)
Other:
______________
(please specify)
Optimal asthma control
Lost workdays
How many out of 100 fully
employed patients would miss
workdays due this asthma state?
For how many days in 3 months
would they at average be absent
from work?
Acceptable asthma control
Uncontrolled asthma
Table 18: Patients without exacerbations, most frequently prescribed co-medication
Number of patients
(out of 100)
Co-medication
Optimal asthma control
Product/ molecule:
Product/ molecule:
Product/ molecule:
Acceptable asthma control
Product/ molecule:
Product/ molecule:
Product/ molecule:
Uncontrolled asthma
Product/ molecule:
Product/ molecule:
Product/ molecule:
____________________________
Administration
(e.g. oral, i.v., s.c.)
Dosage and unit
(e.g. mcg, mg)
Frequency per day
Duration of treatment
(in days)
B. Patients with exacerbations:
Please think of 100 adult patients with severe asthma who are not adequately controlled: Which medical resources are at average consumed by those
patients as a result of the exacerbation event?
Table 19: Patients with exacerbations
Mild/ moderate exacerbation
Number of
patients
(out of 100)
Outpatient visits
Visits to GP
Visits to nurse
Visits to specialist:
______________
(please specify specialist)
Visits to ‘other’:
______________
(please specify)
Home visits
GP visits
Nurse visits
Visits by a specialist:
______________
(please specify specialist)
Visits by ‘other’:
______________
(please specify)
Spirometry test
Intubation
Resource use
(number, per event
and patient)
Severe exacerbation
without hospitalisation
Resource use
Number of
(number, per
patients
event and
(out of 100)
patient)
Severe exacerbation
with hospitalisation
Number of
patients
(out of 100)
Resource use
(number, per event
and patient)
Other:
______________
(please specify)
Other:
______________
(please specify)
Other:
______________
(please specify)
Mild/ moderate exacerbation
Lost workdays
How many out of 100 fully
employed patients would miss
workdays due this asthma state?
While an exacerbation is onset,
for how many days would they
at average be absent from work?
Severe exacerbation
without hospitalisation
Severe exacerbation
with hospitalisation
Table 20: Patients without exacerbations, most frequently prescribed co -medication
Number of patients
(out of 100)
Co-medication
Mild/ moderate exacerbation
Product/ molecule:
Product/ molecule:
Product/ molecule:
Severe exacerbation without hospitalisation
Product/ molecule:
Product/ molecule:
Product/ molecule:
Severe exacerbation with hospitalisation
Product/ molecule:
Product/ molecule:
Product/ molecule:
____________________
Administration (e.g.
oral, i.v., s.c.)
Dosage and unit (e.g.
mcg, mg)
Frequency per day
Duration of treatment
(in days)