Rapid Fire Best of the Best Poster Oral Clinical Oncology Society of Australia Annual Scientific Meeting 2021

Budget impact modelling for listing new cancer treatments in different cancer stages using real-world data (#272)

Fanny Franchini 1 , Koen Degeling 1 , Benjamin Daniels 2 , Sallie Pearson 2 , Karen Trapani 1 , Yuting Zhang 1 , Peter Gibbs 3 , Ben Solomon 4 , Grant McArthur 4 , Jayesh Desai 4 , Stephen Fox 4 , Maarten J IJzerman 1 4
  1. University of Melbourne, Parkville, VIC, Australia
  2. University New South Wales, Sydney
  3. Walter and Eliza Hall Research Institute, Melbourne
  4. Peter MacCallum Cancer Centre, Melbourne, VIC, Australia

Objectives

The listing of new cancer treatments in the Pharmaceutical Benefits Scheme (PBS) and Medical Benefits Schedule (MBS) has become a very complicated undertaking, because of the many uncertainties in the submitted evidence to support listing for increasingly smaller populations. Internationally, several initiatives are taken to use real-world, population level, data to better understand uptake of new treatments and to facilitate the approval process. The MRFF funded "PRedicting the population health economic IMpact of new CAncer Treatments” (PRIMCAT) program aims to estimate population health economic impact of new cancer treatments ahead of market approval.

Methods

We take a data-driven modelling approach to quantify the population health economic impact of new cancer treatments for colorectal cancer, non-small cell lung cancer and melanoma. Clinical registries, real-world hospital and administrative data for state-wide retrospective patient cohorts (n=200,000 over 10 years) are analysed for patient characteristics, treatment patterns and outcomes from everyday oncology practice, as well as their associated costs. Potential future cancer treatments are screened using horizon scanning and multi-criteria decision analysis, with inputs from expert and consumer panels. Discrete Event Simulation models will be established to forecast the population health impact of new treatment introduction at applicable points in the treatment pathways. 

Results

Treatment pathways are mapped using available treatment data from clinical registries and were further refined using clinician-developed treatment algorithms, which represent current PBS and standard of care. Based on these treatment pathways, a modelling framework will be presented for each cancer stream. Further data analysis, including modelling of the new cancer treatments for each nominated cancer as identified from the horizon scanning, is underway. 

Conclusions

Estimating the population health impact of new cancer treatments ahead of market approval remains a complicated undertaking.  The PRIMCAT research project will provide evidence-based data to inform Health Technology Assessment (HTA) in Australia.