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Mao X, Omeogu C, Karanth S, Joshi A, Meernik C, Wilson L, Clark A, Deveaux A, He C, Johnson T, Barton K, Kaplan S, Akinyemiju T. Association of reproductive risk factors and breast cancer molecular subtypes: a systematic review and meta-analysis. BMC Cancer 2023; 23:644. [PMID: 37430191 DOI: 10.1186/s12885-023-11049-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 06/08/2023] [Indexed: 07/12/2023] Open
Abstract
BACKGROUND Associations between reproductive factors and breast cancer (BC) risk vary by molecular subtype (i.e., luminal A, luminal B, HER2, and triple negative/basal-like [TNBC]). In this systematic review and meta-analysis, we summarized the associations between reproductive factors and BC subtypes. METHODS Studies from 2000 to 2021 were included if BC subtype was examined in relation to one of 11 reproductive risk factors: age at menarche, age at menopause, age at first birth, menopausal status, parity, breastfeeding, oral contraceptive (OC) use, hormone replacement therapy (HRT), pregnancy, years since last birth and abortion. For each reproductive risk factor, BC subtype, and study design (case-control/cohort or case-case), random-effects models were used to estimate pooled relative risks and 95% confidence intervals. RESULTS A total of 75 studies met the inclusion criteria for systematic review. Among the case-control/cohort studies, later age at menarche and breastfeeding were consistently associated with decreased risk of BC across all subtypes, while later age at menopause, later age of first childbirth, and nulliparity/low parity were associated with increased risk of luminal A, luminal B, and HER2 subtypes. In the case-only analysis, compared to luminal A, postmenopausal status increased the risk of HER2 and TNBC. Associations were less consistent across subtypes for OC and HRT use. CONCLUSION Identifying common risk factors across BC subtypes can enhance the tailoring of prevention strategies, and risk stratification models can benefit from subtype specificity. Adding breastfeeding status to current BC risk prediction models can enhance predictive ability, given the consistency of the associations across subtypes.
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Affiliation(s)
- Xihua Mao
- Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Chioma Omeogu
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC, USA
| | - Shama Karanth
- UF Health Cancer Canter, University of Florida, Gainesville, FL, USA
| | - Ashwini Joshi
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC, USA
| | - Clare Meernik
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC, USA
| | - Lauren Wilson
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC, USA
| | - Amy Clark
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC, USA
| | - April Deveaux
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC, USA
| | - Chunyan He
- The Cancer Prevention and Control Research Program, University of Kentucky Markey Cancer Center, Lexington, KY, USA
| | - Tisha Johnson
- Department of Preventive Medicine and Environmental Health, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Karen Barton
- Duke University Medical Center Library & Archives, Duke University School of Medicine, Durham, NC, USA
| | - Samantha Kaplan
- Duke University Medical Center Library & Archives, Duke University School of Medicine, Durham, NC, USA
| | - Tomi Akinyemiju
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC, USA.
- Duke Cancer Institute, Duke University, Durham, NC, USA.
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Zuo Q, Park NH, Lee JK, Madak Erdogan Z. Liver Metastatic Breast Cancer: Epidemiology, Dietary Interventions, and Related Metabolism. Nutrients 2022; 14:2376. [PMID: 35745105 PMCID: PMC9228756 DOI: 10.3390/nu14122376] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 05/22/2022] [Accepted: 05/28/2022] [Indexed: 02/06/2023] Open
Abstract
The median overall survival of patients with metastatic breast cancer is only 2-3 years, and for patients with untreated liver metastasis, it is as short as 4-8 months. Improving the survival of women with breast cancer requires more effective anti-cancer strategies, especially for metastatic disease. Nutrients can influence tumor microenvironments, and cancer metabolism can be manipulated via a dietary modification to enhance anti-cancer strategies. Yet, there are no standard evidence-based recommendations for diet therapies before or during cancer treatment, and few studies provide definitive data that certain diets can mediate tumor progression or therapeutic effectiveness in human cancer. This review focuses on metastatic breast cancer, in particular liver metastatic forms, and recent studies on the impact of diets on disease progression and treatment.
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Affiliation(s)
- Qianying Zuo
- Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; (Q.Z.); (N.H.P.)
| | - Nicole Hwajin Park
- Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; (Q.Z.); (N.H.P.)
| | - Jenna Kathryn Lee
- Department of Neuroscience, Northwestern University, Evanston, IL 60208, USA;
| | - Zeynep Madak Erdogan
- Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; (Q.Z.); (N.H.P.)
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Carl R. Woese Institute of Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Department of Biomedical and Translational Sciences, Carle-Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
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