Objective. Survival extrapolation using a single, best-fit model ignores 2 sources of model
uncertainty: uncertainty in the true underlying distribution and uncertainty about the stability …

Background. It is widely recommended that health technology appraisals adopt a lifetime
horizon to assess the relative costs and benefits of an intervention. However, most trials or …

Previous work examined the suitability of relying on routine methods of model selection
when extrapolating survival data in a health technology appraisal setting. Here we explore …

Background In decision modeling with time-to-event data, there are a variety of parametric
models that can be used to extrapolate the survival function. Each model implies a different …

Abstract Background and Objective The extrapolation of estimated hazard functions can be
an important part of cost-effectiveness analyses. Given limited follow-up time in the sample …

Background Health policy decisions are often informed by estimates of long-term survival
based primarily on short-term data. A range of methods are available to include longer-term …

Background Extrapolation of survival data is a key task in health technology assessments
(HTAs), which may be improved by incorporating general population mortality data via …

Extrapolations of parametric survival models fitted to censored data are routinely used in the
assessment of health technologies to estimate mean survival, particularly in diseases that …

Background Expected value of sample information (EVSI) quantifies the expected value to a
decision maker of reducing uncertainty by collecting additional data. EVSI calculations …

Background Different parametric survival models can lead to widely discordant
extrapolations and decision uncertainty in cost-effectiveness analyses. The use of excess …