Impact of structural assumptions within breast cancer natural history models on estimates of the benefits of screening. May 5, 2009

Jason Madan (research fellow) - health economics and decision science, University of Sheffield will be presenting this seminar as part of a series from Salford's Management & Management Sciences Research Institute.

A range of health economic models have been used to evaluate breast cancer screening programmes. These models vary in the way they represent breast cancer progression, and all have short-comings in terms of how well they represent current knowledge of cancer biology.

To illustrate the impact of model structure on predictions of the survival benefit from screening, a range of natural history survival models of increasing sophistication were fitted to a common dataset. These were combined with treatment/survival models matched to each structure, to assess the impact of model design on survival and resource use.

A wide range of predictions of both intermediate parameters (sojourn time, test sensitivity) and survival were obtained. This demonstrates the dependence of modelling results on choices made in the model development process, and the importance of reviewing the clinical plausibility of mathematical statements in health care modelling.

Official Website: http://www.salford.ac.uk/events/details/928