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This Wednesday, 5.02.2025, at 4:00pm CET, we will be hosting Dr Samuel Livingstone from University College London. He is an expert in Bayesian computing, with a particular focus on Markov chain-based Monte Carlo methods. We will have the opportunity to hear a very interesting lecture on 'Survival Analysis for Health Technology Assessment: new Bayesian approaches to modelling and computation.'

Link to the meeting.

Survival analysis, the study of time-to-event data, is critical in understanding patient outcomes across healthcare contexts. In health technology assessment (HTA), accurate survival predictions inform decisions on the cost-effectiveness and long-term value of new interventions.  This talk will explore some novel Bayesian approaches to fitting survival models, which offer a principled framework for model selection and extrapolation while providing calibrated uncertainty estimates essential for decision-making. By incorporating prior information and systematically handling complex data structures, Bayesian methods yield more robust and interpretable survival predictions. Key motivating applications include survival times for stroke survivors and kidney transplant patients, which demonstrate how these methods can enhance HTA by supporting more informed policy and clinical decisions. Based on joint work with Luke Hardcastle & Gianluca Baio, preprint available here.