Characteristics of Mammographic Breast Density and Associated Factors for Chinese Women: Results from an Automated Measurement.


Journal

Journal of oncology
ISSN: 1687-8450
Titre abrégé: J Oncol
Pays: Egypt
ID NLM: 101496537

Informations de publication

Date de publication:
2019
Historique:
received: 10 08 2018
revised: 01 02 2019
accepted: 19 02 2019
entrez: 25 4 2019
pubmed: 25 4 2019
medline: 25 4 2019
Statut: epublish

Résumé

Characteristics of mammographic density for Chinese women are understudied. This study aims to identify factors associated with mammographic density in China using a quantitative method. Mammographic density was measured for a total of 1071 (84 with and 987 without breast cancer) women using an automatic algorithm AutoDensity. Pearson tests examined relationships between density and continuous variables and t-tests compared differences of mean density values between groupings of categorical variables. Linear models were built using multiple regression. Percentage density and dense area were positively associated with each other for cancer-free (r=0.487, p<0.001) and cancer groups (r=0.446, p<0.001), respectively. For women without breast cancer, weight and BMI (p<0.001) were found to be negatively associated (r=-0.237, r=-0.272) with percentage density whereas they were found to be positively associated (r=0.110, r=0.099) with dense area; age at mammography was found to be associated with percentage density (r=-0.202, p<0.001) and dense area (r=-0.086, p<0.001) but did not add any prediction within multivariate models; lower percentage density was found within women with secondary education background or below compared to women with tertiary education. For women with breast cancer, percentage density demonstrated similar relationships with that of cancer-free women whilst breast area was the only factor associated with dense area (r=0.739, p<0.001). This is the first time that mammographic density was measured by a quantitative method for women in China and identified associations should be useful to health policy makers who are responsible for introducing effective models of breast cancer prevention and diagnosis.

Sections du résumé

BACKGROUND BACKGROUND
Characteristics of mammographic density for Chinese women are understudied. This study aims to identify factors associated with mammographic density in China using a quantitative method.
METHODS METHODS
Mammographic density was measured for a total of 1071 (84 with and 987 without breast cancer) women using an automatic algorithm AutoDensity. Pearson tests examined relationships between density and continuous variables and t-tests compared differences of mean density values between groupings of categorical variables. Linear models were built using multiple regression.
RESULTS RESULTS
Percentage density and dense area were positively associated with each other for cancer-free (r=0.487, p<0.001) and cancer groups (r=0.446, p<0.001), respectively. For women without breast cancer, weight and BMI (p<0.001) were found to be negatively associated (r=-0.237, r=-0.272) with percentage density whereas they were found to be positively associated (r=0.110, r=0.099) with dense area; age at mammography was found to be associated with percentage density (r=-0.202, p<0.001) and dense area (r=-0.086, p<0.001) but did not add any prediction within multivariate models; lower percentage density was found within women with secondary education background or below compared to women with tertiary education. For women with breast cancer, percentage density demonstrated similar relationships with that of cancer-free women whilst breast area was the only factor associated with dense area (r=0.739, p<0.001).
CONCLUSION CONCLUSIONS
This is the first time that mammographic density was measured by a quantitative method for women in China and identified associations should be useful to health policy makers who are responsible for introducing effective models of breast cancer prevention and diagnosis.

Identifiants

pubmed: 31015834
doi: 10.1155/2019/4910854
pmc: PMC6444251
doi:

Types de publication

Journal Article

Langues

eng

Pagination

4910854

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Auteurs

Tong Li (T)

Medical Radiation Sciences, Faculty of Health Sciences, The University of Sydney, Cumberland Campus, 75 East Street, Lidcombe, NSW, Australia.

Lichen Tang (L)

Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai, China.

Ziba Gandomkar (Z)

Medical Radiation Sciences, Faculty of Health Sciences, The University of Sydney, Cumberland Campus, 75 East Street, Lidcombe, NSW, Australia.

Rob Heard (R)

Behaviour and Social Sciences, Faculty of Health Sciences, The University of Sydney, Cumberland Campus, 75 East Street, Lidcombe, NSW, Australia.

Claudia Mello-Thoms (C)

Medical Radiation Sciences, Faculty of Health Sciences, The University of Sydney, Cumberland Campus, 75 East Street, Lidcombe, NSW, Australia.

Qin Xiao (Q)

Department of Radiology, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai, China.

Yajia Gu (Y)

Department of Radiology, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai, China.

Genhong Di (G)

Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai, China.

Carolyn Nickson (C)

Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, 207 Bouverie Street, Melbourne, VIC 3010, Australia.

Zhimin Shao (Z)

Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai, China.

Patrick Brennan (P)

Medical Radiation Sciences, Faculty of Health Sciences, The University of Sydney, Cumberland Campus, 75 East Street, Lidcombe, NSW, Australia.

Classifications MeSH