As statisticians in the medical field, we’re used to studying subgroups of patients with respect to all kinds of biological variables: from demographics to genomics. This provides us with a good understanding of what the benefit-risk profile for a given patient looks like.
However, the patient might have a completely different view on the importance of the different benefits and risks. And importantly, these preferences might be less driven by biological factors and more by personal experiences and situations as well as psychological traits. How can we assess patient preferences in this regard?
Marco Boeri and I worked on such questions in the past and some work has been presented at last year’s PSI conference. In today’s episode, we give you some insights into what’s possible and how you can approach this problem.
We’ll dive into questions like:
- Why is exploring heterogeneity for preference data different, than for the usual endpoints in clinical studies?
- What kind of factors, do we need to consider for patient preferences?
- Is it also possible to cluster patients based on similar preferences?
- What are the potential implications in terms of treatment decisions or the benefit-risk ratio in different subgroups?
References
MDIC Patient Centered Benefit-Risk Framework Report Public Release, May 13, 2015.… – see references from ordinal data
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Marco Boeri
Marco Boeri, PhD, is a Senior Research Economist at RTI-HS. Dr. Boeri was previously a lecturer in Environmental Economics and has 10 years of experience in preference assessment in environmental and health economics and 2 years of experience in the private financial sector in Marketing. Dr. Boeri has extensive knowledge and experience in experimental design, survey development, and modeling data from discrete choice studies in health, food, and environmental economics. His research focuses on comparing different and innovative preference analysis methods (i.e., regret minimization vs. utility maximization or structural choice modeling) at the individual and household levels. He has co-authored the first applications of the Random Regret Minimization model in both environmental and health economics and he has published in several applied economics journals across different disciplines including Pharmacoeconomics, Journal of Health Economics, Social Science and Medicine, Value in Health, Medical Decision Making, Preventive Medicine, Environmental and Resource Economics, Energy Economics, Transportation Research Part A, and the Journal of Economic Behavior and Organization, demonstrating the applicability of his methodological tool at top levels in different topics and fields.
Dr. Marco Boeri is interested in environmental and resource economics, health economics, energy economics, micro-econometrics, non-market valuation, choice experiments, preference analysis: regret minimization versus utility maximization, and consumer behavior.
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I want to help the community of statisticians, data scientists, programmers and other quantitative scientists to be more influential, innovative, and effective. I believe that as a community we can help our research, our regulatory and payer systems, and ultimately physicians and patients take better decisions based on better evidence.
I work to achieve a future in which everyone can access the right evidence in the right format at the right time to make sound decisions.
When my kids are sick, I want to have good evidence to discuss with the physician about the different therapy choices.
When my mother is sick, I want her to understand the evidence and being able to understand it.
When I get sick, I want to find evidence that I can trust and that helps me to have meaningful discussions with my healthcare professionals.
I want to live in a world, where the media reports correctly about medical evidence and in which society distinguishes between fake evidence and real evidence.
Let’s work together to achieve this.
