Body composition patterns and breast cancer risk in Chinese women with breast diseases: A latent class analysis

2019 ◽  
Vol 75 (11) ◽  
pp. 2638-2646
Author(s):  
Jinyu Zhang ◽  
Jichuan Wang ◽  
Jie Zhou ◽  
Qiong Fang ◽  
Nan Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Body Composition ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Chinese Women ◽  
Breast Diseases ◽  
Class Analysis

scholarly journals Association Between Dietary Patterns and Plasma Lipid Biomarker and Female Breast Cancer Risk: Comparison of Latent Class Analysis (LCA) and Factor Analysis (FA)

2021 ◽  
Vol 8 ◽  
Author(s):  
Shang Cao ◽  
Linchen Liu ◽  
Qianrang Zhu ◽  
Zheng Zhu ◽  
Jinyi Zhou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Factor Analysis ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Latent Class Analysis ◽  
Dietary Patterns ◽  
Latent Class ◽  
Plasma Lipid ◽  
Apolipoprotein A1 ◽  
Class Analysis

Background: Diet research focuses on the characteristics of “dietary patterns” regardless of the statistical methods used to derive them. However, the solutions to these methods are both conceptually and statistically different.Methods: We compared factor analysis (FA) and latent class analysis (LCA) methods to identify the dietary patterns of participants in the Chinese Wuxi Exposure and Breast Cancer Study, a population-based case-control study that included 818 patients and 935 healthy controls. We examined the association between dietary patterns and plasma lipid markers and the breast cancer risk.Results: Factor analysis grouped correlated food items into five factors, while LCA classified the subjects into four mutually exclusive classes. For FA, we found that the Prudent-factor was associated with a lower risk of breast cancer [4th vs. 1st quartile: odds ratio (OR) for 0.70, 95% CI = 0.52, 0.95], whereas the Picky-factor was associated with a higher risk (4th vs. 1st quartile: OR for 1.35, 95% CI = 1.00, 1.81). For LCA, using the Prudent-class as the reference, the Picky-class has a positive association with the risk of breast cancer (OR for 1.42, 95% CI = 1.06, 1.90). The multivariate-adjusted model containing all of the factors was better than that containing all of the classes in predicting HDL cholesterol (p = 0.04), triacylglycerols (p = 0.03), blood glucose (p = 0.04), apolipoprotein A1 (p = 0.02), and high-sensitivity C-reactive protein (p = 0.02), but was weaker than that in predicting the breast cancer risk (p = 0.03).Conclusion: Factor analysis is useful for understanding which foods are consumed in combination and for studying the associations with biomarkers, while LCA is useful for classifying individuals into mutually exclusive subgroups and compares the disease risk between the groups.

Association between dietary patterns and risk of breast cancer in Chinese female population: a latent class analysis

2020 ◽  
pp. 1-24
Author(s):  
Shang Cao ◽  
Shurong Lu ◽  
Jinyi Zhou ◽  
Zheng Zhu ◽  
Wei Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Latent Class Analysis ◽  
Dietary Patterns ◽  
Latent Class ◽  
Chinese Women ◽  
Premenopausal Women ◽  
Positive Association ◽  
Class Analysis ◽  
Female Population ◽  
Soy Foods

ABSTRACT Objective: To determine if specific dietary patterns are associated with breast cancer risk in Chinese women. Design: Latent class analysis (LCA) was performed to identify generic dietary patterns based on daily food-frequency data. Setting: The Chinese Wuxi Exposure and Breast Cancer Study (2013-2014). Participants: A population-based case-control study (695 cases, 804 controls). Results: Four dietary patterns were identified, Prudent, Chinese traditional, Western, and Picky, the proportion in the controls and cases were 0.30/0.32/0.16/0.23 and 0.29/0.26/0.11/0.33, respectively. Women in Picky class were characterized by higher extreme probabilities of non-consumption on specific foods, the highest probabilities of consumption of pickled foods, and the lowest probabilities of consumption of cereals, soy foods, and nuts. Compared with Prudent class, Picky class was associated with a higher risk (OR=1.42, 95%CI=1.06, 1.90), while the relevant association was only in post- (OR=1.44, 95%CI=1.01, 2.05) but not premenopausal women. The Western class characterized by high-protein, -fat, and -sugar foods, the Chinese traditional class characterized by typical consumption of soy foods and white meat over red meat, both of them showed no difference in BC risk compared with Prudent class did. Conclusions: LCA capture the heterogeneity of individuals embedded in the population, could be a useful approach in the study of dietary pattern and disease. Our results indicated that the Picky class might have a positive association with the risk of breast cancer.

Association of polymorphisms in intron 2 of FGFR2 and breast cancer risk in Chinese women

2016 ◽  
Vol 50 (5) ◽  
pp. 312-317 ◽  
Author(s):  
Z. Pan ◽  
Y. Bao ◽  
X. Zheng ◽  
W. Cao ◽  
W. Cheng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Chinese Women ◽  
Intron 2

Associations between polymorphisms at microRNA-binding sites in TYMS and breast cancer risk among Chinese women

2020 ◽  
Author(s):  
Meng Wang ◽  
Jia Yao ◽  
Yi Zheng ◽  
Yuyao Yao ◽  
Shuqian Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Chinese Women ◽  
Microarray Dataset ◽  
Tumor Stage ◽  
Recessive Model ◽  
Breast Cancer Patients ◽  
Chinese Han ◽  
Expression Levels

Abstract Studies have suggested that thymidylate (TYMS) polymorphisms are associated with breast cancer. However, inconsistent results were obtained and data from Asian populations are largely lacking. In this study, the relationships between two common TYMS polymorphisms (rs2790 and rs1059394) and the breast cancer risk were evaluated. We also studied the TYMS expression between tumor and para-carcinoma tissues, and the association between TYMS levels and prognosis of breast cancer. This hospital-based study included 434 patients and 450 cancer-free individuals. Genotying was performed using Sequenom Mass-ARRAY. The microarray dataset GSE115144 was downloaded to compare the differences in TYMS expression between tumor and para-carcinoma tissues. The microarray dataset GSE20685 was used to analysis the metastasis free survival (MFS) and overall survival (OS) of patients. The rs2790 polymorphism was related to a higher risk of breast cancer (recessive model: OR=1.50, 95%CI=1.02-2.21, P=0.038) and the C allele of rs1059394 was overrepresented in patients with tumor stage III-IV (heterozygote model: OR=0.60, 95%CI=0.39-0.94, P=0.025; dominant model: OR=0.59, 95%CI=0.39-0.89, P=0.013). The tumor tissues had a higher TYMS expression levels and patients with higher TYMS expression levels had worse OS. Overall, TYMS polymorphism may increase susceptibility to breast cancer in Chinese Han women and TYMS expression levels may be a predictive factor for breast cancer patients.

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