Health Technology Assessment (HTA) information, and in particular cost-effectiveness data is needed to guide decisions, preferably already in early stages of technological development. However, at that moment there is usually a high degree of uncertainty, because evidence is limited and different development paths are still possible. We developed a multi-parameter framework to assess dynamic aspects of a technology -still in development-, by means of scenario drafting to determine the effects, costs and cost-effectiveness of possible future diffusion patterns. Secondly, we explored the value of this method on the case of the clinical implementation of the 70-gene signature for breast cancer, a gene expression profile for selecting patients who will benefit most from chemotherapy.
To incorporate process-uncertainty, ten possible scenarios regarding the introduction of the 70-gene signature were drafted with European experts. Out of 5 most likely scenarios, 3 drivers of diffusion (non-compliance, technical failure, and uptake) were quantitatively integrated in a decision-analytical model. For these scenarios, the cost-effectiveness of the 70-gene signature expressed in Incremental Cost-Effectiveness Ratios (ICERs) was compared to clinical guidelines, calculated from the past (2005) until the future (2020).
In 2005 the ICER was €1,9 million/quality-adjusted-life-year (QALY), meaning that the 70-gene signature was not yet cost-effective compared to the current clinical guideline. The ICER for the 70-gene signature improved over time with a range of €1,9 million to €26,145 in 2010 and €1,9 million to €11,123/QALY in 2020 depending on the separate scenario used. From 2010, the 70-gene signature should be cost-effective, based on the combined scenario. The uptake-scenario had strongest influence on the cost-effectiveness.
When optimal diffusion of a technology is sought, incorporating process-uncertainty by means of scenario drafting into a decision model may reveal unanticipated developments and can demonstrate a range of possible cost-effectiveness outcomes. The effect of scenarios give additional information on the speed with cost effectiveness might be reached and thus provide a more realistic picture for policy makers, opinion leaders and manufacturers.