Evidence map›Paper›PMID 40627186›Full record

ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2025

Patterns of medication use following breast cancer diagnosis: an Australian population-based study.

Huah Shin Ng, Christoffer Johansen, Ming Li, David Roder, Kerri Beckmann, Bogda Koczwara

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Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Huah Shin NgCollege of Medicine and Public Health, Flinders Health and Medical Research Institute, Flinders University, Adelaide, South Australia, Australia. huahshin.ng@flinders.edu.au.
Christoffer JohansenCenter for Cancer Late Effect Research CASTLE, Department of Oncology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
Ming LiCancer Epidemiology and Population Health Research Group, Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia.
David RoderCancer Epidemiology and Population Health Research Group, Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia.
Kerri BeckmannCancer Epidemiology and Population Health Research Group, Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia.
Bogda KoczwaraCollege of Medicine and Public Health, Flinders Health and Medical Research Institute, Flinders University, Adelaide, South Australia, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to examine patterns of medication use and polypharmacy following breast cancer diagnosis.

methodsThis retrospective cohort study used breast cancer data from the South Australian Cancer Registry linked with medication dispensing records, death registry, and inpatient hospital records. Women diagnosed with invasive 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) from Year-2 to Year-5 of breast cancer diagnosis were examined using generalised estimating equations models with binary logistic distribution.

resultsThe study included 2005 women (mean age = 61.1 years). The use of endocrine therapy for breast cancer decreased over time (odds ratio (OR) 0.88; 95%CI = 0.86-0.90). In contrast, the likelihood of being dispensed specific cardiovascular medicines increased with each successive time period including agents acting on renin-angiotensin system (OR 1.03; 95%CI = 1.01-1.05), lipid-modifying agents (OR 1.06; 95%CI = 1.03-1.08), beta-blockers (OR 1.08; 95%CI = 1.04-1.11), and cardiac therapy (OR 1.12; 95%CI = 1.06-1.18). There was an increased likelihood of polypharmacy over time (OR 1.08; 95%CI = 1.04-1.11) with the prevalence ranging from 25% (Year 2) to 29% (Year 5). Several characteristics were associated with polypharmacy including older age, a lower socioeconomic status, and a higher burden of comorbidities.

conclusionThe use of several medication classes increased over time suggesting development of new comorbidities and higher likelihood of polypharmacy. Medication management in breast cancer survivors offers potential to identify those with complex needs of polypharmacy and comorbidity.

Indexed as

Breast NeoplasmsDrug PrescriptionsPolypharmacyAgedAged, 80 and overFemaleHumansLogistic ModelsMiddle AgedOdds RatioPrevalenceRegistriesRetrospective StudiesSouth AustraliaTime FactorsBreast cancerMedication usePolypharmacyPopulation-basedSouth Australia

Identifiers

PMID40627186
PMCPMC12238185

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.