Summary
Background: With the Act on the Reform of the Market for Medicinal Products (AMNOG) in Germany,
pharmaceutical manufacturers are obliged to submit a dossier demonstrating added benefit
of a new drug compared to an appropriate comparator. Underlying evidence was planned
for registration purposes and therefore often does not meet the appropriate comparator
as defined by the Federal Joint Committee (G-BA). For this reason AMNOG allows indirect
comparisons to assess the extent of added benefit.
Objectives: The aim of this study is to evaluate the characteristics and applicability of adjusted
indirect comparison described by Bucher and Matching-Adjusted Indirect Comparison
(MAIC) in various situations within the early benefit assessment according to §35a
Social Code Book 5. In particular, we consider time-to-event endpoints.
Methods: We conduct a simulation study where we consider three different scenarios: I) similar
study populations, II) dissimilar study populations without interactions and III)
dissimilar study populations with interactions between treatment effect and effect
modifiers. We simulate data from a Cox model with Wei- bull distributed survival times.
Desired are unbiased effect estimates. We compare the power and the proportion of
type 1 errors of the methods.
Results: I) Bucher and MAIC perform equiva- lently well and yield unbiased effect estimates
as well as proportions of type 1 errors below the significance level of 5%. II) Both
Bucher and MAIC yield unbiased effect estimates, but Bucher shows a higher power for
detection of true added benefit than MAIC. III) Only MAIC, but not Bucher yields unbiased
effect estimates. When using robust variance estimation MAIC yields a proportion of
type 1 error close to 5%.
In general, power of all methods for indirect comparisons is low. An increasing loss
of power for the indirect comparisons can be observed as the true treatment effects
decrease.
Conclusion: Due to the great loss of power and the potential bias for indirect comparisons, head-to-head
trials using the appropriate comparator as defined by the Federal Joint Committee
should be conducted whenever possible. However, indirect comparisons are needed if
no such direct evidence is available. To conduct indirect comparisons in case of a
present common comparator and similar study populations in the trials to be compared,
both Bucher and MAIC can be recommended. In case of using adjusted effect measures
(such as Hazard Ratio), the violation of the similarity assumption has no relevant
effect on the Bucher approach as long as interactions between treatment effect and
effect modifiers are absent. Therefore Bucher can still be considered appropriate
in this specific situation. In the authors’ opinion, MAIC can be considered as an
option (at least as sensitivity analysis to Bucher) if such interactions are present
or cannot be ruled out. Nevertheless, in practice MAIC is potentially biased and should
always be considered with utmost care.
Keywords
Indirect comparisons - Bucher - MAIC - AMNOG - dissimilarity
