Transcript Document

A state of the art multi-criteria
model for drug benefit-risk
analysis
T. Tervonen (1), D. Postmus (2), H.L. Hillege (3)
(1) Faculty of Economics and Business, RUG.nl
(2) Department of Epidemiology /+ (3) Cardiology, UMCG.nl
What? Drug benefit-risk analysis is based on firm clinical
evidence expressing various factors. We propose a
supporting multi-criteria model that fully takes into
account the clinical evidence and allows quantifying
tradeoffs between drugs of the same therapeutic class.
How? Stochastic Multicriteria Acceptability Analysis
(SMAA) is used as the decision-aiding model in our study.
SMAA allows computing the typical value judgments that
support a decision, to quantify uncertainty, and to compute
a comprehensive benefit-risk profile. We constructed a
multi-criteria model for ranking drugs for depression with
respect to different benefit and risk criteria.
Methods. We analyzed Fluoxetine,
Paroxetine, Sertraline, and Venlafaxine
according to relative efficacy and absolute
rates of most common adverse drug reactions
using meta-analytical data from literature.
We did three analyses: one without
preference information and two with criteria
rankings elicited from an expert in the field
of antidepressants. We explained the SMAA
model and multi-attribute utility theory to
the expert and asked her to consider two
scenarios: mild and severe depression.
Our model showed that there
are clear tradeoffs within and
between the four drugs with
respect to the approach without
preference information
(Figure 1), mild depression
(Figure 2) and severe
depression (Figure 3).
Main results.
1.
We separated clinical data from subjective judgments, thereby increasing the transparency of the
decision making process.
2.
In contrast to previous applications of multi-criteria methods, our approach is based on the SMAA
methodology, that allows us to take into account the sampling variation that is inherent in outcome
measurements in clinical trials and/or observational studies.
3. Analysis without preferences allows to quantify tradeoffs
between drugs.
4. Scenario-based analysis incorporating preferences in the model
can be used to improve risk assessment and management of
new drugs.
This study was performed in the context of the Escher project (T6-202), a project of the Dutch Top Institute Pharma