The BD4QoL Deliverable D6.1 Benchmark risk stratification models, has produced interesting models that can predict Health Related Quality of Life (HRQoL) trajectories, based on demographic and clinical variables.

The BD4QoL Consortium is now analysing such models through a Health Technology Assessment exercise, to assess their value potential, when deployed in the clinical practice.

To do this, a workflow for the application of the predictive model in the clinical workflow must be hypothesized, and a Markov Model for simulating such “augmented” workflow and comparing it to the standard of care, must be designed and run.

For example, since the model would allow to predict which cancer survivors are more at risk of HRQoL decrease, an appropriate intervention to mitigate such risks could be enacted for these individuals, lowering the proportion of them that would transition to lower HRQoL levels.

Overall Quality of Life gained (measured in Quality Adjusted Life Years, or QALY) and costs saved (e.g., because of less Adverse Events to be treated, or swifter return to work, etc.) are then computed and aggregated by the Markov Model. From this, the final Incremental Cost Effectiveness Ratio (ICER) would be derived, expressing how much one additional QALY gained would cost or save.

If the ICER is under the Willingness-to-pay threshold (normally, around several tens of thousands of Euros per QALY) then the application of the D6.1 predictive models is indeed cost-effective and worth considering for addition into clinical guidelines.

Results will be reported in the Project Deliverable D8.1 Cost-effectiveness analysis, which the Consortium will dedicate to the public domain.