Abstract
Background and Objectives
A relation between the size of treatment efficacy and severity of the disease has
been postulated and observed as linear for a few therapies. We have called this relation
the effect model. Our objectives were to demonstrate that the relation is general
and not necessarily linear.
Study Design and Setting
We extend the number of observed effect model. Then we established three numerical
models of treatment activity corresponding to the three modes of action we have identified.
Using these models, we simulated the relation.
Results
Empirical evidence confirms the effect model and suggests that it may be linear over
a short range of event frequency. However, it provides an incomplete understanding
of the phenomenon because of the inescapable limitations of data from randomized clinical
trials. Numerical modeling and simulation show that the real effect model is likely
to be more complicated. It is probably linear only in rare instances. The effect model
is general. It depends on factors related to the individual, disease and outcome.
Conclusion
Contrarily to common, assumption, since the effect model is often curvilinear, the
relative risk cannot be granted as constant. The effect model should be taken into
account when discovering and developing new therapies, when making, health care policy
decisions or adjusting clinical decisions to the patient risk profile.
Keywords
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Article info
Publication history
Published online: November 29, 2007
Accepted:
July 10,
2007
Identification
Copyright
© 2008 Elsevier Inc. Published by Elsevier Inc. All rights reserved.
