Use of Advanced Flexible Modeling Approaches for Survival Extrapolation from Early Follow-up Data in two Nivolumab Trials in Advanced NSCLC with Extended Follow-up.

M A Chaudhary,M Edmondson-Jones,G Baio, E Mackay, J R Penrod,D J Sharpe, G Yates,S Rafiq, K Johannesen,M K Siddiqui, J Vanderpuye-Orgle,A Briggs

Medical decision making : an international journal of the Society for Medical Decision Making(2023)

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摘要
Flexible advanced parametric modeling methods can provide improved survival extrapolations for immuno-oncology cost-effectiveness in health technology assessments from early clinical trial data that better anticipate extended follow-up.Advantages include leveraging additional observable trial data, the systematic integration of external data, and more detailed modeling of underlying processes.Bayesian multiparameter evidence synthesis performed particularly well, with well-matched external data.Mixture cure models also performed well but may require relatively longer follow-up to identify an emergent plateau, depending on the specific setting.Landmark response models offered marginal benefits in this scenario and may require greater numbers in each response group and/or increased follow-up to support improved extrapolation within each subgroup.
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关键词
bayesian multiparameter evidence synthesis,bayesian statistics,cost-effectiveness analysis,external data,extrapolation,survival analysis
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