November 6: Going Beyond the Standard: Exploring Advanced Survival Modeling Techniques - In Person at ISPOR Europe 2022
Survival modeling techniques are commonly used to extrapolate clinical trial outcomes like overall survival to a time horizon that is appropriate for health economic evaluations. Standard parametric distributions, such as the exponential and Weibull, have been the de-facto standard for conducting such extrapolations but, with the advent of novel potentially curative therapies, these standard parametric distributions fail to capture the underlying survival trend. Newer techniques like response based landmark models, parametric mixture models, mixture cure models and Bayesian model averaging provide novel ways to capture these more complex survival patterns. The purpose of this course is to enable participants to identify which methods are most appropriate in a specific context, considering underlying structural assumptions, and discuss how modeling choices propagate into health economic evaluations. To gain a more in-depth understanding of the impact of the choice for a specific method, participants will practice with several of the survival modeling techniques in hands-on exercises.
Deputy
Chief Scientific Officer
Evidence & Access
OPEN Health
Oxford, UK
Elleke Peterse, PhD
Associate Research Consultant
OPEN Health
Rotterdam, Netherlands
Lisanne Verburg-Baltussen, MSc, PhD
Research Consultant
OPEN Health Evidence & Access
Rotterdam, Netherlands
Kasper Johannesen, PhD, MSc
Director, Economic & Predictive Modeling
Worldwide HEOR
Bristol Myers Squibb
Solna, Sweden
November 6, 2022
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Going Beyond the Standard: Exploring Advanced Survival Modeling Techniques
LEVEL: Intermediate
TRACK: Methodological & Statistical Research
LENGTH: 4 Hours | Course runs 1 day
This short course will be offered in-person at the ISPOR Europe 2022 conference. Separate registration is required. Visit the ISPOR Europe 2022 website to register and learn more.
Sunday, 6 November 2022 | Course runs 1 Day
DESCRIPTION
Survival modeling techniques are commonly used to extrapolate clinical trial outcomes like overall survival to a time horizon that is appropriate for health economic evaluations. Standard parametric distributions, such as the exponential and Weibull, have been the de-facto standard for conducting such extrapolations but, with the advent of novel potentially curative therapies, these standard parametric distributions fail to capture the underlying survival trend. Newer techniques like response based landmark models, parametric mixture models, mixture cure models and Bayesian model averaging provide novel ways to capture these more complex survival patterns. The purpose of this course is to enable participants to identify which methods are most appropriate in a specific context, considering underlying structural assumptions, and discuss how modeling choices propagate into health economic evaluations. To gain a more in-depth understanding of the impact of the choice for a specific method, participants will practice with several of the survival modeling techniques in hands-on exercises.FACULTY MEMBERS
Elisabeth Fenwick, PhD, MScDeputy
Chief Scientific Officer
Evidence & Access
OPEN Health
Oxford, UK
Elleke Peterse, PhD
Associate Research Consultant
OPEN Health
Rotterdam, Netherlands
Lisanne Verburg-Baltussen, MSc, PhD
Research Consultant
OPEN Health Evidence & Access
Rotterdam, Netherlands
Kasper Johannesen, PhD, MSc
Director, Economic & Predictive Modeling
Worldwide HEOR
Bristol Myers Squibb
Solna, Sweden
Basic Schedule:
4 Hours | Course runs 1 Day