Possible risk modifications in the association between MnSOD Ala-9Val polymorphism and breast cancer risk: subgroup analysis and evidence-based sample size calculation for a future trial

Background Several studies have reported correlations between BRCA1 polymorphisms rs799917 and rs1799966 with the risk of breast cancer (BC). However, this relationship remains controversial. Methods We conducted a meta-analysis of seven studies to assess the associations between BRCA1 rs799917 and rs1799966 and BC risk, with the aim of more accurately determining the potential correlation. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated to evaluate the correlation of rs799917 and rs1799966 with BC risk. Results There was no overall correlation between BRCA1 rs799917 and BC risk (TT vs CC: OR = 0.87, 95% CI = 0.66–1.16; CT vs CC: OR = 1.02, 95% CI = 0.89–1.15; dominant model: OR = 0.99, 95% CI = 0.88–1.11; recessive model: OR = 0.87, 95% CI = 0.65–1.16). Subgroup analysis by ethnicity also revealed no significant correlation between rs799917 and BC risk in either Asians or Caucasians. There was also no significant association between BRCA1 rs1799966 and BC risk (GG vs AA: OR = 0.70, 95% CI = 0.33–1.47; AG vs AA: OR = 0.68, 95% CI = 0.35–1.30; dominant model: OR = 0.76, 95% CI = 0.49–1.06; recessive model: OR = 0.82, 95% CI = 0.49–1.36). Conclusion BRCA1polymorphisms rs799917 and rs1799966 were not significantly associated with BC risk in this meta-analysis.

Download Full-text

Breast Cancer Risk in Rheumatoid Arthritis: An Update Meta-Analysis

BioMed Research International ◽

10.1155/2014/453012 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9 ◽

Cited By ~ 10

Author(s):

Guo Tian ◽

Jia-Ning Liang ◽

Zhuo-Yun Wang ◽

Dian Zhou

Keyword(s):

Breast Cancer ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Subgroup Analysis ◽

Meta Analysis ◽

Random Effect ◽

Random Effect Model ◽

Cochrane Library ◽

Number Of Patients ◽

The Impact

Background. The incidence of breast cancer in RA patients remains controversial. Thus we performed a meta-analysis to investigate the impact of RA on breast cancer.Methods. Published literature was available from PubMed, Embase, and Cochrane Library. Pooled standardized incidence rate (SIR) was computed by random-effect model analysis.Results. We identified 16 separate studies in the present study, in which the number of patients ranged from 458 to 84,475. We did not find the increased cancer risk in RA patients (SIR=0.86, 95%CI=0.72–1.02). However, subgroup analysis showed that breast cancer risk in RA patients was positively different in Caucasians (SIR=0.82, 95%CI=0.73–0.93) and non-Caucasians (SIR=1.21, 95%CI=1.19–1.23), respectively. In subgroup analysis by style, a reduced incidence was found in hospital-based case subjects (SIR=0.82, 95%CI=0.69–0.97). Similarly, subgroup analysis for adjusted factors indicated that in A3 (age and sex) and A4 (age, sex, and race/ethnicity) the risk was decreased (SIR=0.87, 95%CI=0.76–0.99;SIR=0.63, 95%CI=0.59–0.67).Conclusions. The meta-analysis revealed no increased breast cancer risk in RA patients. However, in the subgroup analysis, the risk of breast cancer is increased in non-Caucasians patients with RA while it decreased in Caucasian population, hospital-based case subjects, and A3 group. Such relationship may provide preference for risk of breast cancer in different population.

Download Full-text

The association between blood lipid and breast cancer risk: Evidence based on a dose-response meta-analysis comprising 900,669 participants.

Journal of Clinical Oncology ◽

10.1200/jco.2018.36.15_suppl.e24331 ◽

2018 ◽

Vol 36 (15_suppl) ◽

pp. e24331-e24331

Author(s):

Kang Liu ◽

Dingli Song ◽

Shuai Lin ◽

Meng Wang ◽

Tian Tian ◽

...

Keyword(s):

Breast Cancer ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Dose Response ◽

Meta Analysis ◽

Blood Lipid ◽

Evidence Based

Download Full-text

Same data sources, different pooled analysis result: the ongoing uncertainty in the subgroup analysis of RAD51 135G/C polymorphism and breast cancer risk

Breast Cancer Research and Treatment ◽

10.1007/s10549-010-1189-0 ◽

2010 ◽

Vol 125 (1) ◽

pp. 299-300 ◽

Cited By ~ 2

Author(s):

Pei-Hua Lu ◽

Chen Li ◽

Hong-Yi Zhou ◽

Tong Wang ◽

Chun-Qiang Chu ◽

...

Keyword(s):

Breast Cancer ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Subgroup Analysis ◽

Pooled Analysis ◽

Data Sources

Download Full-text

Underweight Indian Women at a Risk for Developing Breast Cancer: A Retrospective Study

Asian Pacific Journal of Cancer Care ◽

10.31557/apjcc.2021.6.3.305-309 ◽

2021 ◽

Vol 6 (3) ◽

pp. 305-309

Author(s):

Mrunal Ketkar ◽

Amrita Ulhe ◽

Minal Mahajan ◽

Karamchand Patil ◽

Ruchika Kaul-Ghanekar

Keyword(s):

Breast Cancer ◽

Body Mass Index ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Sample Size ◽

Body Mass ◽

Body Fat ◽

Research Centre ◽

Indian Women ◽

Positive Correlation

Background: Breast cancer is the leading cancer diagnosed in Indian women. Lifestyle related factors such as high body mass index (BMI) and obesity have been recognized as major risk factors for the development of breast cancer. However, India has higher proportion of underweight population and recently positive correlation has been reported between underweight and increased risk of breast cancer. We have attempted to study an association between low BMI and total body fat percentage with breast cancer risk by performing retrospective analysis on a small sample size of 41 female patients diagnosed with breast cancer. The data was collected from Department of Oncology, Bharati Vidyapeeth Hospital and Research Centre (BVHRC), Pune, India. Methods: Binary logistic regression was performed to estimate odds ratios (ORs) and to examine the predictive effect of each factor on the breast cancer risk. Results: It was observed that underweight population displayed higher risk of breast cancer development based on BMI (OR-15.40) and body fat % (OR-1.33). Conclusion: This pilot study suggests that low body mass index may be related to poor prognosis in breast cancer and thus warrants further studies on a larger sample size to establish a positive correlation.

Download Full-text