Time-to-Event Analysis in HEOR Explained | Kaplan-Meier, Hazard Ratio & Survival Analysis
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Time-to-Event Analysis in HEOR Explained | Kaplan-Meier, Hazard Ratio & Survival Analysis
62 просмотра · 2 нед. назад
HEOR insights
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62 просмотра · 2 нед. назад
What is Time-to-Event Analysis, and why is it important in Health Economics and Outcomes Research (HEOR)?
In this video, HEOR Insights introduces the fundamental concepts of Time-to-Event Analysis and Survival Analysis, statistical methods used to analyse the time until an event of interest occurs. These methods are important in clinical trials, real-world evidence (RWE), health technology assessment (HTA) and health economic modelling.
This video builds foundational knowledge of survival analysis and explains how its key concepts connect with clinical outcomes and cost-effectiveness analysis.
In this video, we discuss:
What is Time-to-Event Analysis?
The role of survival analysis in clinical research and HEOR
Survival function, hazard and censoring
Kaplan–Meier survival curves
Overall Survival (OS) versus Progression-Free Survival (PFS)
Hazard Ratio (HR) and its interpretation
Introduction to the Cox Proportional Hazards Model
Parametric survival models, including Weibull, Exponential and Log-normal distributions
The relevance of survival analysis in HTA and health economic evaluation
Survival extrapolation in cost-effectiveness analysis
Connections between survival outcomes, Quality-Adjusted Life Years (QALYs) and the Incremental Cost-Effectiveness Ratio (ICER)
Why survival analysis is a useful concept for aspiring HEOR professionals
Who should watch this video?
B.Pharm, M.Pharm and Pharm.D students
Life sciences and public health graduates
Aspiring HEOR analysts
Clinical research and real-world evidence professionals
Learners interested in HTA, economic modelling and pharmaceutical consulting
Understanding time-to-event analysis can help build a foundation for learning clinical evidence evaluation and survival modelling in HEOR.
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