A systematic review of the effectiveness of adalimumab

To estimate the long-term consequences of RA
and model the natural history of RA, a Markov
model was used based on ARAMIS. This is not
described in detail in the report. ARAMIS is a
North American database consisting of 4258
prospectively enrolled patients with RA from nine
centres followed for over 17,000 patient-years.
The issue here is how a population of patients
seen in private practices in the USA and Canada
between 1981 and 1995 can reflect practice in the
NHS in 2005. The model has states defined in
terms of HAQ score (e.g. HAQ 0.1–1.0) and states
defined in terms of treatments (e.g. methotrexate
and one or more DMARD). Each health state, in
terms of disability score and treatment, determines
the transitional probability. During any cycle,
patients may change or retain the same treatment,
with the exception that the other treatments could
not change to infliximab plus methotrexate. It is
unclear why a change to infliximab and
methotrexate is not permitted as this is a fairly
common practice for people not doing well on a
DMARD. An assumption was made that when
infliximab was continued beyond the trial
duration, the HAQ score would be preserved but
not improved, and would be discontinued with
worsening HAQ or side-effects. HAQ in RA or in
the normal population tends to decline with age,
therefore assuming that long-term stability is
unreasonable.
Clinically significant radiographic progression was
determined from cohort data using the smallest
detectable difference (SDD) based on the Outcome
Measures in Rheumatoid Arthritis Clinical Trials
(OMERACT) definition. Although SDD is an
important starting point for determining whether
radiographic changes are clinically meaningful, it
is by no means accepted that the two are the same.
In addition, the SDD needs to be determined for
each trial since it is a statistical concept and
depends on the performance of two or more
assessors in a particular setting, so SDDs from
different settings vary considerably. Patients were
divided into radiographic SDD progressors and
non-progressors, with progressors having higher
mean HAQ scores owing to physical disability
from the progressing disease. Therefore, an
absence of radiographic progression improved
HAQ by 0.27 after 5–6 years. However, since there
is a relationship between HAQ and radiographic
change, and since HAQ changes are incorporated
into the model, it appears that HAQ
improvements are being double-counted.
Radiographic data were used in the model, such
that evidence of radiographic stabilisation was
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Health Technology Assessment 2006; Vol. 10: No. 42
applied to the Markov model as increasing the
chance that a patient would remain in the same
HAQ group, thereby decreasing the annual
likelihood of HAQ progression. However,
radiographic changes are likely to be greater in
early RA and it is unreasonable to assume that
similar changes could apply to the ATTRACT
population. This analysis also calibrated the model
to assume benefits 5 years from trial onset.
Radiographic benefit was applied to patients
treated for more than 6 weeks, so patients who
discontinued infliximab where no ACR20 response
was evident by week 14 did not receive this
benefit. Most patients in trials do not show
radiographic changes. Therefore, assuming this
radiographic benefit several years later in patients
with 6 weeks of treatment and an ACR20 response
at 14 weeks is rather generous.
Estimates of the impact of infliximab on disease
progression were obtained from the ATTRACT
and from ASPIRE, with the likelihood of improved
or worsened HAQ score estimated from the
methotrexate and methotrexate/infliximab arms of
the trials. However, using all arms of
infliximab/methotrexate regardless of dose or
dosing interval from ATTRACT may weigh in
favour of infliximab as, although outcomes looked
similar, patients on 10 mg kg –1 of infliximab
did appear to be doing better. Health state values
were based on a personal communication from
G Kobelt to the company, as follows:
● HAQ 0 = 0.819
● HAQ 0.1–1.0 = 0.682
● HAQ 1.1–2.0 = 0.454
● HAQ 2.1–3.0 = 0.192.
UK-based sources for resource-use data and for
unit costs were used (ERA study). Discount rates of
6% for costs and 1.5% for benefits were applied. A
wide range of one-way and multiway sensitivity
analyses was undertaken.
The base-case cost-effectiveness results are
summarised in Table 30. The results are
interpreted as yielding “costs per QALY that
fall well within the range of such estimates for
health care interventions typically funded in the
UK. The high CRP subset has a better costeffectiveness
ratio because of faster radiological
progression compared to the overall ASPIRE
group.”
The sensitivity analyses looked at stopping rules,
discount rates, RA mortality assumptions,
utility scores, resource use and radiographic
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