Docetaxel with prednisone or prednisolone for the treatment of ...

TABLE 27 Cost-effectiveness results based on revised assumptions
approach to estimating mean survival, based on
the extrapolation of survival data, appears
robust and is necessary in order to quantify the
potential lifetime consequences of the different
interventions. However, the ICER does appear to
be potentially sensitive to the time horizon and
demonstrates that the assumption that benefits are
maintained over a longer time horizon may be an
important assumption in relation to the potential
cost-effectiveness of docetaxel plus prednisone.
The study does, however, suffer from several
potential limitations. Some of these are simply due
to a lack of transparency regarding some of the
assumptions applied to the costs of the first-line
chemotherapy phase and also the main approach
used to handle censoring in the cost data. In order
to address the first of these potential limitations,
two additional sensitivity analyses were conducted
to examine the robustness of the base-case results
to a reasonable set of alternative assumptions. In
particular, in the review of resource utilisation and
costs, it was noted that a higher mean body
surface area of 1.9 m 2 should be applied to each of
the trial arms. This figure represents the only
value reported in the clinical trials considered and
corresponds to normal values reported for males
in the general population. In addition, the
reviewers reported that the analysis had not
included the additional premedication costs
associated with the use of oral dexamethasone for
patients receiving docetaxel-based regimens. It
also highlighted that the robustness of the results
to variation in the number of cycles should be
considered, due to the marked skewness in this
distribution. As an alternative scenario, the
reviewers applied the median number of cycles
reported in TAX 327. They explored the
robustness of the base-case model to these revised
assumptions using two separate analyses:
Health Technology Assessment 2007; Vol. 11: No. 2
Analysis Intervention Mean costs (£) Mean life-years gained ICER (£)
Revised analysis 1
Within trial Docetaxel 16,168 1.575 32,285
Mitoxantrone 9,711 1.375 NA
Extrapolation Docetaxel 16,168 1.865 20,773
Mitoxantrone 9,711 1.554 NA
Revised analysis 2
Within trial Docetaxel 18,776 1.575 46,095
Mitoxantrone 9,557 1.375 NA
Extrapolation Docetaxel 18,776 1.865 29,659
Mitoxantrone 9,557 1.554 NA
© Queen’s Printer and Controller of HMSO 2007. All rights reserved.
● Revised analysis 1 – a revised body surface area
of 1.9 m 2 was assumed and the additional costs
of premedication of oral dexamethasone were
applied.
● Revised analysis 2 – as above but also replacing
the mean number of cycles with the median
number of cycles.
The results of these additional sensitivity analyses
are presented in Table 27. Applying a higher body
surface area and including the additional costs of
premedication did not appear to have much of an
impact on the overall results. However, the
application of median (as opposed to mean)
number of cycles had a more marked impact on
the ICER, increasing from £30,283 to £46,095 per
life-year gained in the within-trial analysis and
from £19,483 to £29,659 in the lifetime analysis.
This demonstrates that the results are potentially
sensitive to the assumption related to the number
of cycles and clearly illustrates that it is important
to quantify this appropriately in order to reflect
the resulting decision uncertainty.
The methods used to assess the robustness of the
base-case results to parameter uncertainty are
extremely limited and are confined to a one-way
sensitivity analysis of survival data. The report
states that a probabilistic analysis was not
undertaken since “it was felt that the assumptions
required to characterise the variation in most
variables was too high to make this approach
robust” (Ref. 61, p. 55). It could equally be argued
that it is precisely in these situations (e.g.
situations with high parameter uncertainty) when
it is most critical to characterise appropriately
uncertainty and to reflect the resulting decision
uncertainty. Consequently, it is not possible to
assess the robustness of the results to the
uncertainty surrounding other parameters.
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