Health: Psychology

A Primer, Upcoming Webinar Hosted by Xtalks

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Xtalks Life Science Webinars

Advanced techniques have recently been developed to account for complex challenges such as interval censoring, cured patients and treatment crossover.


TORONTO (PRWEB)

Economic evaluations for health technology assessments (HTAs) often rely on estimates of “time-to-event” for patient outcomes, such as time to disease progression, time to first stroke, or time to death to assess the costs and benefits of a treatment or intervention.

Analysis of time-to-event data – also known as survival analysis – can provide estimates of survivor functions and event rates that inform these economic analyses. As well as characterising event rates over an observed period of time, such as the duration of a clinical trial, survival analysis techniques are used to extrapolate the results over a lifetime to generate estimates of mean survival benefit.

Estimates of an intervention’s cost-effectiveness can be sensitive to the methods applied in modelling and extrapolating survival data. Typically, these projections are performed using various parametric models, with each model making different assumptions about the underlying hazard function. Advanced techniques have recently been developed to account for complex challenges such as interval censoring, cured patients and treatment crossover.

Join Victoria Paly, MHS, Principal, Global Health Economics, ICON and Dhvani Shah, MS, Principal, Global Health Economics, ICON in a live webinar on Friday, May 15, 2020 at 11am EDT (4pm BST/UK).

For more information or to register for this event, visit Survival Analysis in HTA Submissions: A Primer.

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