| 11. |
- Nichols, Hazel B., et al.
(författare)
-
The Premenopausal Breast Cancer Collaboration : A Pooling Project of Studies Participating in the National Cancer Institute Cohort Consortium
- 2017
-
Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : AMER ASSOC CANCER RESEARCH. - 1055-9965 .- 1538-7755. ; 26:9, s. 1360-1369
-
Forskningsöversikt (refereegranskat)abstract
- Breast cancer is a leading cancer diagnosis among premenopausal women around the world. Unlike rates in postmenopausal women, incidence rates of advanced breast cancer have increased in recent decades for premenopausal women. Progress in identifying contributors to breast cancer risk among premenopausal women has been constrained by the limited numbers of premenopausal breast cancer cases in individual studies and resulting low statistical power to subcategorize exposures or to study specific subtypes. The Premenopausal Breast Cancer Collaborative Group was established to facilitate cohort-based analyses of risk factors for premenopausal breast cancer by pooling individuallevel data from studies participating in the United States National Cancer Institute Cohort Consortium. This article describes the Group, including the rationale for its initial aims related to pregnancy, obesity, and physical activity. We also describe the 20 cohort studies with data submitted to the Group by June 2016. The infrastructure developed for this work can be leveraged to support additional investigations.
|
|
| 12. |
- Playdon, Mary C., et al.
(författare)
-
Metabolomics Analytics Workflow for Epidemiological Research : Perspectives from the Consortium of Metabolomics Studies (COMETS)
- 2019
-
Ingår i: Metabolites. - : MDPI. - 2218-1989 .- 2218-1989. ; 9:7
-
Tidskriftsartikel (refereegranskat)abstract
- The application of metabolomics technology to epidemiological studies is emerging as a new approach to elucidate disease etiology and for biomarker discovery. However, analysis of metabolomics data is complex and there is an urgent need for the standardization of analysis workflow and reporting of study findings. To inform the development of such guidelines, we conducted a survey of 47 cohort representatives from the Consortium of Metabolomics Studies (COMETS) to gain insights into the current strategies and procedures used for analyzing metabolomics data in epidemiological studies worldwide. The results indicated a variety of applied analytical strategies, from biospecimen and data pre-processing and quality control to statistical analysis and reporting of study findings. These strategies included methods commonly used within the metabolomics community and applied in epidemiological research, as well as novel approaches to pre-processing pipelines and data analysis. To help with these discrepancies, we propose use of open-source initiatives such as the online web-based tool COMETS Analytics, which includes helpful tools to guide analytical workflow and the standardized reporting of findings from metabolomics analyses within epidemiological studies. Ultimately, this will improve the quality of statistical analyses, research findings, and study reproducibility.
|
|
| 13. |
- Schoemaker, Minouk J, et al.
(författare)
-
Association of Body Mass Index and Age With Subsequent Breast Cancer Risk in Premenopausal Women.
- 2018
-
Ingår i: JAMA Oncology. - : American Medical Association (AMA). - 2374-2437 .- 2374-2445. ; 4:11
-
Tidskriftsartikel (refereegranskat)abstract
- Importance: The association between increasing body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) and risk of breast cancer is unique in cancer epidemiology in that a crossover effect exists, with risk reduction before and risk increase after menopause. The inverse association with premenopausal breast cancer risk is poorly characterized but might be important in the understanding of breast cancer causation.Objective: To investigate the association of BMI with premenopausal breast cancer risk, in particular by age at BMI, attained age, risk factors for breast cancer, and tumor characteristics.Design, Setting, and Participants: This multicenter analysis used pooled individual-level data from 758 592 premenopausal women from 19 prospective cohorts to estimate hazard ratios (HRs) of premenopausal breast cancer in association with BMI from ages 18 through 54 years using Cox proportional hazards regression analysis. Median follow-up was 9.3 years (interquartile range, 4.9-13.5 years) per participant, with 13 082 incident cases of breast cancer. Participants were recruited from January 1, 1963, through December 31, 2013, and data were analyzed from September 1, 2013, through December 31, 2017.Exposures: Body mass index at ages 18 to 24, 25 to 34, 35 to 44, and 45 to 54 years.Main Outcomes and Measures: Invasive or in situ premenopausal breast cancer.Results: Among the 758 592 premenopausal women (median age, 40.6 years; interquartile range, 35.2-45.5 years) included in the analysis, inverse linear associations of BMI with breast cancer risk were found that were stronger for BMI at ages 18 to 24 years (HR per 5 kg/m2 [5.0-U] difference, 0.77; 95% CI, 0.73-0.80) than for BMI at ages 45 to 54 years (HR per 5.0-U difference, 0.88; 95% CI, 0.86-0.91). The inverse associations were observed even among nonoverweight women. There was a 4.2-fold risk gradient between the highest and lowest BMI categories (BMI≥35.0 vs <17.0) at ages 18 to 24 years (HR, 0.24; 95% CI, 0.14-0.40). Hazard ratios did not appreciably vary by attained age or between strata of other breast cancer risk factors. Associations were stronger for estrogen receptor-positive and/or progesterone receptor-positive than for hormone receptor-negative breast cancer for BMI at every age group (eg, for BMI at age 18 to 24 years: HR per 5.0-U difference for estrogen receptor-positive and progesterone receptor-positive tumors, 0.76 [95% CI, 0.70-0.81] vs hormone receptor-negative tumors, 0.85 [95% CI: 0.76-0.95]); BMI at ages 25 to 54 years was not consistently associated with triple-negative or hormone receptor-negative breast cancer overall.Conclusions and Relevance: The results of this study suggest that increased adiposity is associated with a reduced risk of premenopausal breast cancer at a greater magnitude than previously shown and across the entire distribution of BMI. The strongest associations of risk were observed for BMI in early adulthood. Understanding the biological mechanisms underlying these associations could have important preventive potential.
|
|
| 14. |
- Shu, Xiang, et al.
(författare)
-
Associations of obesity and circulating insulin and glucose with breast cancer risk : a Mendelian randomization analysis
- 2019
-
Ingår i: International Journal of Epidemiology. - : OXFORD UNIV PRESS. - 0300-5771 .- 1464-3685. ; 48:3, s. 795-806
-
Tidskriftsartikel (refereegranskat)abstract
- Background: In addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the development of this common malignancy. Findings from previous studies, however, have been inconsistent, and the nature of the associations is unclear. Methods: We conducted Mendelian randomization analyses to evaluate the association of breast cancer risk, using genetic instruments, with fasting insulin, fasting glucose, 2-h glucose, body mass index (BMI) and BMI-adjusted waist-hip-ratio (WHRadj BMI). We first confirmed the association of these instruments with type 2 diabetes risk in a large diabetes genome-wide association study consortium. We then investigated their associations with breast cancer risk using individual-level data obtained from 98 842 cases and 83 464 controls of European descent in the Breast Cancer Association Consortium. Results: All sets of instruments were associated with risk of type 2 diabetes. Associations with breast cancer risk were found for genetically predicted fasting insulin [odds ratio (OR) = 1.71 per standard deviation (SD) increase, 95% confidence interval (CI) = 1.26-2.31, p = 5.09 x 10(-4)], 2-h glucose (OR = 1.80 per SD increase, 95% CI = 1.3 0-2.49, p = 4.02 x 10(-4)), BMI (OR = 0.70 per 5-unit increase, 95% CI = 0.65-0.76, p = 5.05 x 10(-19)) and WHRadj BMI (OR = 0.85, 95% CI = 0.79-0.91, p = 9.22 x 10(-6)). Stratified analyses showed that genetically predicted fasting insulin was more closely related to risk of estrogen-receptor [ER]-positive cancer, whereas the associations with instruments of 2h glucose, BMI and WHRadj BMI were consistent regardless of age, menopausal status, estrogen receptor status and family history of breast cancer. Conclusions: We confirmed the previously reported inverse association of genetically predicted BMI with breast cancer risk, and showed a positive association of genetically predicted fasting insulin and 2-h glucose and an inverse association of WHRadj BMI with breast cancer risk. Our study suggests that genetically determined obesity and glucose/insulin-related traits have an important role in the aetiology of breast cancer.
|
|
| 15. |
|
|
