What drives the cost of cancer treatment? Insights from an analysis of a longitudinal cohort (Cancer 2015) linked to administrative reimbursement data — ASN Events
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  3. What drives the cost of cancer treatment? Insights from an analysis of a longitudinal cohort (Cancer 2015) linked to administrative reimbursement data

What drives the cost of cancer treatment? Insights from an analysis of a longitudinal cohort (Cancer 2015) linked to administrative reimbursement data (#67)

Paula Lorgelly 1 , Brett Doble 1 , Mark Lucas 1 , John Parisot 2 , Stephen Fox 3 , David Thomas 4
  1. Monash University, Clayton, VIC, Australia
  2. Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
  3. Molecular Pathology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
  4. Garvan Institute, Sydney, NSW, Australia
Background: The Lancet Oncology Commission recently published the global challenges for delivering affordable cancer care. While the challenge of delivering affordable quality care is not unique to oncology, the growing dominance of (expensive) personalized medicine is.
Aim: We estimate current expenditure of delivering cancer care in Victoria; identify who bears this cost; and quantify the significant determinants of this burden, particularly focusing on the role of genomics.

Methods: Cancer 2015 is a large-scale prospective longitudinal population-based molecular cohort study.  Tumour samples and blood are collected and a baseline questionnaire completed, which elicits information on patient demographics, tumour site and stage, treatment intentions and health-related quality-of-life.  Patients also consented to have their Federal and State administrative health data linked.  This analysis uses the cohort data, including the genomic information, linked to administrative reimbursement data.  We quantify the cost of cancer across the range of payers and undertake regression analyses to estimate the determinants of this burden.


Results:  Cancer 2015 has recruited over 1,200 new incident cancers from five hospitals in Victoria since June 2011.  We have been able to identify genetic mutations in a large proportion of these cancers, and have linked this information with PBS/MBS and hospitalization records.  For an 18 month period we have administrative resource use records for 1194 indivdiuals.  The estimated burden is considerable; the mean expenditure is $288 for PBS, $586 for MBS and $1424 for hospitalisations, some drug treatments costing nearly $20,000 per month.  Targeted therapies (the testing for and treatment of) are a significant driver of cost, and this is irrespective of cancer site or stage.


Conclusions: The burden of cancer is considerable, and while it is borne across health funders, a large proportion of the expenditure is due to pharmaceuticals.   The burden incurred by the State is mainly for those cancers which are operable.  Actionable mutations are positively correlated with the lines of treatment; as more mutations become actionable the burden of cancer is predicted to further increase.
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