Economic modelling – experience counts
HTAnalysts have produced 200+ de novo models in the majority of therapeutic areas.
The challenge
HTAnalysts were recently asked to build a multi-indication platform model for a targeted oncology therapy. One aim was to identify gaps in the data for future reimbursement planning.
Actions
- Data Worksheet
HTAnalysts built a data worksheet, capturing data on the population, intervention, comparator and outcome as well as high cost post-progression therapies, co-dependent tests, market information and quality of life assumptions - Preliminary Analyses
Then a series of preliminary Markov-model-based cost-utility analyses (CUA) were built which linked to indication-specific and weighted incremental cost-effectiveness ratios.
What else?
Each of the Markov models employed a common structure consisting of three health states:
Stable Disease • Progressive Disease • Death
All cohorts entered in the Stable Disease health state. Transitions between states were assumed to follow a common parametric survival distribution, altered for individual indications.
The model included actuarial life-tables from Australia to capture general gender and age-based estimates of all cause mortality.
Finally a gap analysis was undertaken to identify key areas of uncertainty for future reimbursement submissions.