Overview:
Health economic models often rely on estimates of time-to-event for outcomes – e.g. time to disease progression, time to first stroke, time to death – to estimate costs and health outcomes over lifetime. Time-to-event, or “survival”, analysis is used to provide estimates of survivor functions and event rates that inform these models. As well as characterising event rates over an observed period, such as the duration of a clinical trial, survival analysis techniques are employed to extrapolate over lifetime to generate estimates of mean survival benefit.
Estimates of the cost-effectiveness of an intervention can be sensitive to the methods applied in modelling and extrapolating survival data. Standard parametric models are preferred when the underlying distribution of survival times is well-understood and can be adequately described by a specific parametric form; advanced survival methods are needed for more complex or heterogeneous data.
Join us to review the techniques of survival analysis and a review of lessons learnt in applying to immature data, including:
- What is survival analysis and how is it used in economic evaluations
- Recent applications in the field of survival analysis
- Lessons learnt when conducting survival analysis on immature data
- Challenges in conducting survival analyses on different outcomes (overall survival, progression-free survival, duration of treatment)
Audience:
This program is intended for professionals from pharmaceutical, biotech, and medical device companies involved in:
- Health technology assessment (HTA)
- Health economics & outcomes research (HEOR)
- Marketing
- Market access, pricing & reimbursement
- Medical affairs
- Regulatory affairs
- Pharmacovigilance and risk management
Presenters:
Tim Baker
Tim has been working in HEOR research and economic modeling since 2000. With experience in economic model design and implementation in multiple disease areas, he has supported HTA submissions in more than a dozen countries, including integration and leverage of survival extrapolation from trial data.
Manikanta Dasari
With more than ten years of experience in health economics and outcomes research (HEOR), Manikanta specialises in developing early economic models, global submission models, as well as supporting country specific HTA submissions. His expertise encompasses a wide range of therapeutic areas, with a notable focus on oncology. In this field, he has conducted complex survival analyses and performed parametric extrapolations on trial data, ensuring robust and reliable outcomes for health economic evaluations.