Factors associated with being diagnosed with high severity of breast cancer: a population-based study in Queensland, Australia.


Journal

Breast cancer research and treatment
ISSN: 1573-7217
Titre abrégé: Breast Cancer Res Treat
Pays: Netherlands
ID NLM: 8111104

Informations de publication

Date de publication:
Dec 2020
Historique:
received: 15 07 2020
accepted: 29 08 2020
pubmed: 15 9 2020
medline: 24 6 2021
entrez: 14 9 2020
Statut: ppublish

Résumé

This study explores factors that are associated with the severity of breast cancer (BC) at diagnosis. Interviews were conducted among women (n = 3326) aged 20-79 diagnosed with BC between 2011 and 2013 in Queensland, Australia. High-severity cancers were defined as either Stage II-IV, Grade 3, or having negative hormone receptors at diagnosis. Logistic regression models were used to estimate odds ratios (ORs) of high severity BC for variables relating to screening, lifestyle, reproductive habits, family history, socioeconomic status, and area disadvantage. Symptom-detected women had greater odds (OR 3.38, 2.86-4.00) of being diagnosed with high-severity cancer than screen-detected women. Women who did not have regular mammograms had greater odds (OR 1.78, 1.40-2.28) of being diagnosed with high-severity cancer than those who had mammograms biennially. This trend was significant in both screen-detected and symptom-detected women. Screen-detected women who were non-smokers (OR 1.77, 1.16-2.71), postmenopausal (OR 2.01, 1.42-2.84), or employed (OR 1.46, 1.15-1.85) had greater odds of being diagnosed with high-severity cancer than those who were current smokers, premenopausal, or unemployed. Symptom-detected women being overweight (OR 1.67, 1.31-2.14), postmenopausal (OR 2.01, 1.43-2.82), had hormone replacement therapy (HRT) < 2 years (OR 1.60, 1.02-2.51) had greater odds of being diagnosed with high-severity cancer than those of healthy weight, premenopausal, had HRT > 10 years. Screen-detected women and women who had mammograms biennially had lower odds of being diagnosed with high-severity breast cancer, which highlighted the benefit of regular breast cancer screening. Women in subgroups who are more likely to have more severe cancers should be particularly encouraged to participate in regular mammography screening.

Identifiants

pubmed: 32926317
doi: 10.1007/s10549-020-05905-x
pii: 10.1007/s10549-020-05905-x
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

937-950

Subventions

Organisme : Cancer Australia
ID : 1006339

Auteurs

Kou Kou (K)

Cancer Council Queensland, Brisbane, Australia.

Jessica Cameron (J)

Cancer Council Queensland, Brisbane, Australia.
School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia.

Joanne F Aitken (JF)

Cancer Council Queensland, Brisbane, Australia.
School of Public Health, The University of Queensland, Brisbane, Australia.
School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia.
Institute for Resilient Regions, University of Southern Queensland, Brisbane, Australia.

Philippa Youl (P)

Cancer Alliance Queensland, Metro South Hospital and Health Service, Woolloongabba, Australia.

Gavin Turrell (G)

Centre for Research and Action in Public Health, Health Research Institute, University of Canberra, Canberra, Australia.

Suzanne Chambers (S)

Faculty of Health, University of Technology Sydney, Sydney, Australia.

Jeff Dunn (J)

Prostate Cancer Foundation of Australia, Sydney, Australia.

Chris Pyke (C)

Mater Hospitals South Brisbane, Brisbane, Australia.

Peter D Baade (PD)

Cancer Council Queensland, Brisbane, Australia. peterbaade@cancerqld.org.au.
School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia. peterbaade@cancerqld.org.au.
Menzies Health Institute Queensland, Griffith University, Gold Coast Campus, Parklands Drive, Southport, QLD, Australia. peterbaade@cancerqld.org.au.
Cancer Council Queensland, PO Box 201, Spring Hill, QLD, 4001, Australia. peterbaade@cancerqld.org.au.

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Classifications MeSH