1. Development of an Integrated Framework for
Quantitative Risk Benefit Assessment
John Doyle, DrPH and Lona Vincent, MPH
Prepared for the 47th Annual DIA Conference Workshop
Development of an Integrated Framework for
Quantitative Risk Benefit Assessment
John Doyle and Lona Vincent
In the last decade, over a dozen high-profile inclusion of patient preference, population of
brand name drugs were removed from the interest, utility, health states, time on drug,
market due to unfavorable risk profiles in and costs. Secondly, we will demonstrate how
post-marketing safety data. Though many we assign relative importance to the
complex factors weigh into the process of parameters based on their application to
drug withdrawals, there is a question of specific clinical scenarios and/or therapeutic
whether a more structured approach to risk area/indication. Lastly, we will exhibit the
and benefit assessment could have improved predictive value of the framework by applying
predictability and provided a more robust it to market analogs, one withdrawn drug and
report on the benefit and risk implications of one drug currently on the market in order to
these products. The U.S. Food and Drug provide an example of how using a predictive
Administration (FDA) in 2007, called for risk-benefit assessment framework can
more creative approaches to conceptualizing, substantially improve drug decision making.
measuring, and improving the assessment of
risk and benefit. Though in 2010, they began
work on a potential qualitative framework;
there is still an unmet need for a quantitative
framework that can provide strategic insight
on the issues relevant to regulatory decision
making and drug safety study design.
Therefore, our aim is to leverage the five-item
FDA qualitative risk-benefit grid and present
a novel approach to quantitative RBA. Using a
framework based on 12 well-accepted models
of risk-benefit measurement, including
Quality Adjusted Time Without Symptoms
and Toxicity (Q-TWiST) and Number Needed
to Treat. (NNT), this workshop will present
the integrated approach in three parts. First,
we will classify the quantitative
measurements according to key themes and
research parameters, such as trial design,