A systematic review of the effectiveness of adalimumab

98
Health economics
TABLE 45 Times to quitting DMARD
DMARD a b (years) Mean (years) Source
Adal 0.73 5.96 7.26 Assumed same as infliximab
AZA 0.39 4.35 15.53 GPRD database 188
CyA 0.5 4.35 8.70 GPRD database 188
Etan 0.73 12.34 15.03 Geborek 171
GST 0.48 1.81 3.91 GPRD database 188
HCQ 0.49 3.52 7.31 GPRD database 188
Infl 0.73 5.96 7.26 Geborek 171
LEF 1 5.98 5.98 GPRD database 188
MTX 0.51 15.73 30.35 GPRD database 188
DPen 0.57 2.60 4.20 GPRD database 188
SSZ 0.46 4.66 11.01 GPRD database 188
Combination CyA+MTX 1 1.74 1.74 Tugwell, 189 Gerards 190
MTX+SSZ 0.46 4.66 11.01 As for SSZ alone
MTX+SSX+HCQ 0.49 3.52 7.31 As for HCQ alone
GPRD, General Practice Research Database.
In implementation, the values of u1 and u2 are
compared with critical values calculated so that
zones A, B and C in Figure 49 have the
appropriate areas to represent the probabilities
given in Table 44. This method means that early
withdrawal for inefficacy coincides with the
minimum HAQ improvement.
For patients who remain on treatment after
24 weeks, the time on treatment is assumed to be
independent of HAQ improvement. The value of
u2 is converted to a value from a Weibull
distribution, represented in the curved part of
Figure 48.
A random variable X has a Weibull distribution
with shape parameter a and scale parameter b if
X a
( ––)
has an exponential distribution with unit
b
mean. The Weibull distribution is more general
than the constant-risk exponential distribution in
that it reduces to the exponential distribution
when a = 1. If a < 1, then the risk decreases over
time, while if a > 1, the risk increases over time.
Parameters a and b are shown in Table 45. For
convenience, the mean of the distribution is also
shown.
HAQ changes on treatment
The model assumes a constant risk of increase in
HAQ score while in treatment and that an
individual’s HAQ score increases gradually and in
steps of 0.125, apart from the effects of starting
and ending treatment. While HAQ can change at
any stage of disease, and is known to be more
labile in early disease, the assumption of a gradual
increase in HAQ is reasonable for the parts of the
model where comparisons are being made, as the
model applies to the later stages of the disease.
The rate of increase in HAQ was chosen to reflect
the empirically observed increase reported by
Scott and Strand. 191
Toxicity
Toxicity of treatments beyond 24 weeks was only
an issue if it potentially affected later choices of
treatment, as shown in Table 44. Thus, it was only
an issue for methotrexate, ciclosporin and the
combination methotrexate plus sulfasalazine. For
other treatments, cessation because of toxicity or
inefficacy has the same consequence in the model;
that is, use of the treatment next in sequence. For
ciclosporin it was assumed that drug cessation was
due to toxicity with a probability of 0.8 regardless
of time spent on drug. 192 For methotrexate, the
probability p was set to depend on the time t years
on the drug, by the formula p = 0.362 +
0.115e –0.457t , which was derived from a comparison
between the survival curves given in Maetzel. 193
For methotrexate plus sulfasalazine, it was
assumed that the probability for methotrexate
alone applies.
Costs
Costs are made up of drug costs plus monitoring
costs. For all treatments, there are higher costs on
starting than there are for continued use. The
total cost for time on any treatment is modelled as
a one-off starting cost followed by a steady annual
usage cost. For completeness, all costs are shown.
The price year is 2004 in each case. The unit costs
of the various inputs are shown in Tables 46 and
47. The monitoring assumptions are listed in
Table 48.