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.