Mackenzie Bourke presented “Incorporating individual-level preferences into cost-effectiveness analysis of population genomic risk screening: a discrete event simulation.”

Lizzy Liu presented “Risk in preferences for breast cancer genomic risk screening and subsequent prevention protocols.”

Julia Steinberg presented “Community preferences for population-wide genomic risk stratification (using polygenic risk scores) and risk-tailored cancer screening.”

📄 pubmed.ncbi.nlm.nih.gov/38459833/
📄 pubmed.ncbi.nlm.nih.gov/39725011/
humgenomics.biomedcentral.com/articles/10....

📄 pubmed.ncbi.nlm.nih.gov/35181209/
📄 nature.com/articles/s41...
📄 pubmed.ncbi.nlm.nih.gov/34099885/
📄 pubmed.ncbi.nlm.nih.gov/37489581/
📄 pubmed.ncbi.nlm.nih.gov/40172779/

Links to the papers referenced in the presentation are included below.
📄 pubmed.ncbi.nlm.nih.gov/32266555/
📄 pubmed.ncbi.nlm.nih.gov/39522058/
📄 pubmed.ncbi.nlm.nih.gov/32024983/
📄 pubmed.ncbi.nlm.nih.gov/32371919/
📄 nature.com/articles/s41...
📄 pubmed.ncbi.nlm.nih.gov/32839572/

Read more here: link.springer.com/article/10.1...

This systematic review highlights where genomic medicine is likely cost-effective across the cancer care continuum, from:
🔹 Prevention & early detection
🔹 Diagnosis, staging & planning
🔹 Treatment
🔹 Managing refractory/relapsed disease
🔹 Palliative & end-of-life care

Using #MCDA, we elicited expert preference values for the diagnostic, clinical, family, economic, and societal components of genomic utility. This enabled the development of a scoring system ranging from 0% to 100%. The utility indicators used in the scale are shown in the table.

Our team is proud to have led the health economics component of the evidence review that informed this Framework.

Read our evidence review: canceraustralia.gov.au/sites/defaul...