Oral Presentation Clinical Oncology Society of Australia Annual Scientific Meeting 2024

Patterns of medication use following breast cancer diagnosis: an Australian population-based study (#18)

Huah Shin Ng 1 2 3 , Christoffer Johansen 4 , Ming Li 2 5 , David Roder 2 , Kerri Beckmann 2 , Bogda Koczwara 1 6
  1. College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
  2. Cancer Epidemiology and Population Health Research Group, Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia
  3. SA Pharmacy, SA Health, Adelaide, SA, Australia
  4. Center for Cancer Late Effect Research CASTLE, Department of Oncology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
  5. Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
  6. Department of Medical Oncology, Flinders Medical Centre, Bedford Park, SA, Australia

Aims: Cancer survivors are at increased risks of developing comorbidities and may take multiple medications. This study examined the patterns of medication use following breast cancer diagnosis.

Methods: A retrospective cohort study using the South Australian Cancer Registry linked with medication dispensing records, death registry and inpatient hospital data. Women diagnosed with breast cancer between July 2012 and March 2014 were followed for 5 years from diagnosis. All medications were defined using the Anatomical Therapeutic Chemical classification and patterns of use were analysed in one-yearly intervals. The changes in the use of medications and polypharmacy (≥5 concomitant medications versus not) over time from Year 2 to Year 5 of breast cancer diagnosis were examined using generalised estimating equations models with binary logistic distribution.

Results: The study included 2005 women (mean age=61.1 years). There was an increased likelihood of polypharmacy over time (Odds Ratio (OR):1.06; 95%CI=1.04-1.09) with the prevalence ranged from 24% (Year 2) to 29% (Year 5). The likelihood of being dispensed cardiovascular medicines including agents acting on renin-angiotensin system (OR:1.03, 95%CI=1.01-1.05), beta-blockers (OR:1.08, 95%CI=1.04-1.11), cardiac therapy (OR:1.16, 95%CI=1.06-1.18), and lipid-modifying agents (OR:1.06; 95%CI=1.03-1.08) increased over time. The medication uses for thyroid (OR:1.04; 95%CI=1.02-1.07), diabetes (OR:1.08; 95%CI=1.05-1.11), obstructive airway (OR:1.09; 95%CI=1.05-1.13), and bone diseases (OR:1.12; 95%CI=1.08-1.17) also increased over time. In contrast, the use of endocrine therapy for breast cancer decreased by 12% (OR:0.88; 95%CI=0.86-0.90). There were no significant changes in other medications including antibacterial for systemic use, antirheumatics and anti-anaemic preparations over time. Several characteristics were associated with polypharmacy including older age, a lower socioeconomic status, and a higher burden of comorbidity.

Conclusion: The use of several medication classes increased over time which may link to the development of new comorbidities. An integrated approach to both polypharmacy and multimorbidity should be considered in the management of cancer survivors.