MSR15 Using Advanced Parametric Survival Models for HTA Submissions in the Face of Short-Term Patient Follow-Up

Abstract

Complex survival patterns commonly arise in randomized clinical trial (RCT) data, for example in immuno-oncology therapies, which typically lead to heterogeneity in patient response and hence long-term survivorship in a proportion of the study population. Such effects are often poorly represented by standard parametric models (SPMs), which consequently tend to yield unreliable short- and long-term extrapolations that are used in clinical- and cost-effectiveness analyses for health technology assessment (HTA) submissions, especially when RCT event data is limited.