The cost burden of breast cancer treatment and diagnosis in Australia – lessons from the Lifepool cohort2018-11-19T00:14:57+00:00

Project Description

The following is a summary of a research project by the authors. For more information please contact Karinna Saxby  at Monash University (email: Karinna.Saxby@monash.edu)

Karinna Saxby1, Dennis Petrie1, Carolyn Nickson2,3, Pietro Procopio2,3, Hannah Bromley2, Louiza Velentzis3, Bruce Mann4, Karen Canfell3

  1. Centre for Health Economics, Monash University
  2. Melbourne School of Population and Global Health , University of Melbourne
  3. Cancer Council NSW
  4. Breast Service, Peter MacCallum Cancer Centre and Royal Melbourne Hospital

Breast cancer is the most common cancer diagnosed among Australian women and its diagnosis and treatment is associated with significant government and individual expenditure. The BreastScreen Australia program provides free biennial mammographic screening, targeted to women aged 50-74 years and available from the age of 40. The primary aim of the program is earlier detection of breast cancer to reduce mortality and treatment intensity. Economic evaluation of the BreastScreen Australia program should incorporate the program’s impact on the costs of breast cancer diagnosis, treatment and management in the community (i.e. outside of BreastScreen and the hospital setting). However, to date, this has been overly simplified or omitted entirely.  To explore such costs, we use data from the Lifepool Cohort, which provides comprehensive demographic information for 50,000 Victorian women as well as details about any subsequent breast cancer diagnoses and, for a subset of the cohort, Medicare claims records (for both MBS and PBS items). Through analysing Medicare claims for those diagnosed with breast cancer, we found a significant increase in both government expenditure and patient contributions for out-of-hospital services 6 months before diagnosis and for up to three years after diagnosis.  Government and individual expenditure was higher for cancers that were of a higher grade, larger in size, or involving the lymph nodes. Screen-detected cancers were associated with reduced government expenditure and out-of-pocket costs compared to cancers diagnosed outside the BreastScreen program, before and after adjustment for multiple cancer characteristics at diagnosis. These differences appeared in both MBS and PBS items. It is important that these costs are considered in future evaluations, particularly when considering changes to the BreastScreen program that might influence cancer characteristics at diagnosis.  Such evaluations should also take into account the likely screen-detection and subsequent treatment of some cancers that would not have been diagnosed in the absence of screening (overdiagnosis). Moving forward, our group will aim to incorporate these costs into a population simulation model for breast cancer screening, diagnosis and treatment.

For further information please contact: Karinna Saxby (email: Karinna.Saxby@monash.edu)