Review of non-clinical risk models to aid prevention of breast cancer.

A disease risk model is a statistical method which assesses the probability that an individual will develop one or more diseases within a stated period of time. Such models take into account the presence or absence of specific epidemiological risk factors associated with the disease and thereby potentially identify individuals at higher risk. Such models are currently used clinically to identify people at higher risk, including identifying women who are at increased risk of developing breast cancer. Many genetic and non-genetic breast cancer risk models have been developed previously. We have evaluated existing non-genetic/non-clinical models for breast cancer that incorporate modifiable risk factors. This review focuses on risk models that can be used by women themselves in the community in the absence of clinical risk factors characterization. The inclusion of modifiable factors in these models means that they can be used to improve primary prevention and health education pertinent for breast cancer. Literature searches were conducted using PubMed, ScienceDirect and the Cochrane Database of Systematic Reviews. Fourteen studies were eligible for review with sample sizes ranging from 654 to 248,407 participants. All models reviewed had acceptable calibration measures, with expected/observed (E/O) ratios ranging from 0.79 to 1.17. However, discrimination measures were variable across studies with concordance statistics (C-statistics) ranging from 0.56 to 0.89. We conclude that breast cancer risk models that include modifiable risk factors have been well calibrated but have less ability to discriminate. The latter may be a consequence of the omission of some significant risk factors in the models or from applying models to studies with limited sample sizes. More importantly, external validation is missing for most of the models. Generalization across models is also problematic as some variables may not be considered applicable to some populations and each model performance is conditioned by particular population characteristics. In conclusion, it is clear that there is still a need to develop a more reliable model for estimating breast cancer risk which has a good calibration, ability to accurately discriminate high risk and with better generalizability across populations.

Association of Nongenetic Factors With Breast Cancer Risk in Genetically Predisposed Groups of Women in the UK Biobank Cohort.

Importance: The association between noninherited factors, including lifestyle factors, and the risk of breast cancer (BC) in women and the association between BC and genetic makeup are only partly characterized. A study using data on current genetic stratification may help in the characterization. Objective: To examine the association between healthier lifestyle habits and BC risk in genetically predisposed groups. Design, Setting, and Participants: Data from UK Biobank, a prospective cohort comprising 2728 patients with BC and 88 489 women without BC, were analyzed. The data set used for the analysis was closed on March 31, 2019. The analysis was restricted to postmenopausal white women. Classification of healthy lifestyle was based on Cancer Research UK guidance (healthy weight, regular exercise, no use of hormone replacement therapy for more than 5 years, no oral contraceptive use, and alcohol intake <3 times/wk). Three groups were established: favorable (≥4 healthy factors), intermediate (2-3 healthy factors), and unfavorable (≤1 healthy factor). The genetic contribution was estimated using the polygenic risk scores of 305 preselected single-nucleotide variations. Polygenic risk scores were categorized into 3 tertiles (low, intermediate, and high). Main Outcomes and Measures: Cox proportional hazards regression was used to assess the hazard ratios (HRs) of the lifestyles and polygenic risk scores associated with a malignant neoplasm of the breast. Results: Mean (SD) age of the 2728 women with BC was 60.1 (5.5) years, and mean age of the 88 489 women serving as controls was 59.4 (4.9) years. The median follow-up time for the cohort was 10 years (maximum 13 years) (interquartile range, 9.44-10.82 years). Women with BC had a higher body mass index (relative risk [RR], 1.14; 95% CI, 1.05-1.23), performed less exercise (RR, 1.12; 95% CI, 1.01-1.25), used hormonal replacement therapy for longer than 5 years (RR, 1.23; 95% CI, 1.13-1.34), used more oral contraceptives (RR, 1.02; 95% CI, 0.93-1.12), and had greater alcohol intake (RR, 1.11; 95% CI, 1.03-1.19) compared with the controls. Overall, 20 657 women (23.3%) followed a favorable lifestyle, 60 195 women (68.0%) followed an intermediate lifestyle, and 7637 women (8.6%) followed an unfavorable lifestyle. The RR of the highest genetic risk group was 2.55 (95% CI, 2.28-2.84), and the RR of the most unfavorable lifestyle category was 1.44 (95% CI, 1.25-1.65). The association of lifestyle and BC within genetic subgroups showed lower HRs among women following a favorable lifestyle compared with intermediate and unfavorable lifestyles among all of the genetic groups: women with an unfavorable lifestyle had a higher risk of BC in the low genetic group (HR, 1.63; 95% CI, 1.13-2.34), intermediate genetic group (HR, 1.94; 95% CI, 1.46-2.58), and high genetic group (HR, 1.39; 95% CI, 1.11-1.74) compared with the reference group of favorable lifestyle. Intermediate lifestyle was also associated with a higher risk of BC among the low genetic group (HR, 1.40; 95% CI, 1.09-1.80) and the intermediate genetic group (HR, 1.37; 95% CI, 1.12-1.68). Conclusions and Relevance: In this cohort study of data on women in the UK Biobank, a healthier lifestyle with more exercise, healthy weight, low alcohol intake, no oral contraceptive use, and no or limited hormonal replacement therapy use appeared to be associated with a reduced level of risk for BC, even if the women were at higher genetic risk for BC.

Risk of breast cancer in the UK biobank female cohort and its relationship to anthropometric and reproductive factors.

BACKGROUND: Anthropometric and reproductive factors have been reported as being established risk factors for breast cancer (BC). This study explores the contribution of anthropometric and reproductive factors in UK females developing BC in a large longitudinal cohort. METHODS: Data from the UK Biobank prospective study of 273,467 UK females were analyzed. Relative risks (RRs) and 95% confidence intervals (CIs) for each factor were adjusted for age, family history of BC and deprivation score. The analyses were stratified by the menopausal status. RESULTS: Over the 9 years of follow up the total number of BC cases were 14,231 with 3,378 (23.7%) incident cases with an incidence rate of 2.09 per 1000 person-years. In pre-menopausal, increase in age, height, having low BMI, low waist to hip ratio, first degree family history of BC, early menarche age, nulliparous, late age at first live birth, high reproductive interval index, and long contraceptive use duration were all significantly associated with an increased BC risk. In post-menopausal, getting older, being taller, having high BMI, first degree BC family history, nulliparous, late age at first live birth, and high reproductive interval index were all significantly associated with an increased risk of BC. The population attributable fraction (PAF) suggested that an early first live birth, lower reproductive interval index and increased number of children can contribute to BC risk reduction up to 50%. CONCLUSIONS: This study utilizes the UK Biobank study to confirm associations between anthropometric and reproductive factors and the risk of breast cancer development. Result of attributable fraction of risk contributed by each risk factor suggested that lifetime risk of BC can be reduced by controlling weight, reassessing individual approaches to the timing of childbirth and options for contraception and considering early screening for women with family history in the first degree relative.

Insulin-like growth factor 1 gene polymorphism and breast cancer risk among arab omani women: a case-control study.

UNLABELLED: Breast cancer is the most common cancer worldwide with significant global burden. Insulin-like growth factor 1 (IGF1) is an important regulator of cellular growth, differentiation, and apoptosis and mitogenic and antiapoptotic activities. Some studies suggested an association between cytosine adenine (CA) repeats gene polymorphisms of IGF1 and the risk of developing breast cancer while other studies did not find such an association. This study aims investigate the role of IGF1 (CA) repeats gene polymorphisms in the risk of developing breast cancer among Omani women. METHODS: We analyzed (CA) repeats gene polymorphisms of IGF1 by extraction of genomic DNA from the peripheral blood of 147 patients with breast cancer and 134 control participants and performed genotyping using DNA sequencing. RESULTS: Approximately 46% of patients carried the IGF (CA)(19) repeat allele, with 31.3% carrying two copies of this allele and 50% of controls carried the IGF (CA)(19) repeat allele with 30.1% carrying two copies of this allele. The difference of the IGF CA repeat groups was significant between cases and controls with (P =0.02). In contrast, there was no difference in the distribution of (CA)(19) repeat allele, (CA)(18) repeat allele and (CA)(19) repeat allele between cases and controls. The difference of the CA groups was significant between cases and controls among postmenopausal women with (P =0.026), whereas no difference was observed among postmenopausal subjects (P =0.429). In both pre- and postmenopausal groups there was no difference in the distribution of (CA)(19) repeat allele, (CA)(18) repeat allele and (CA)(20) repeat allele between patients and control subjects. On further IGF1 genotypes classification, we found an association between progesterone receptor status and the genotypes group where the non carrier of (CA)(19) repeat group was compared to (CA)(19) repeat carrier group (OR =2.482; 95% CI =1.119-5.503; P value =0.023). CONCLUSION: Overall there was no association between the IGF (CA)(19) repeat and breast cancer in Omani females.