METHODS: Forty-two female Sprage-Dawley rats were randomized into 7 groups (6 in each group). The ovariectomized (OVX) and OVX + 6%, 3%, and 1.5% EBN and OVX +estrogen groups were given standard rat chow alone, standard rat chow +6%, 3%, and 1.5% EBN, or standard rat chow +estrogen therapy (0.2mg/kg per day), respectively. The sham-operation group was surgically opened without removing the ovaries. The control group did not have any surgical intervention. After 12 weeks of intervention, blood samples were taken for serum estrogen, osteocalcin, and osteoprotegerin, as well as the measurement of magnesium, calcium abd zinc concentrations. While femurs were removed from the surrounding muscles to measure bone mass density using the X-ray edge detection technique, then collected for histology and estrogen receptor (ER) immunohistochemistry.
RESULTS: Ovariectomy altered serum estrogen levels resulting in increased food intake and weight gain, while estrogen and EBN supplementation attenuated these changes. Ovariectomy also reduced bone ER expression and density, and the production of osteopcalcin and osteorotegerin, which are important pro-osteoplastic hormones that promote bone mineraliztion and density. Conversely, estrogen and EBN increased serum estrogen levels leading to increased bone ER expression, pro-osteoplastic hormone production and bone density (all P<0.05).
CONCLUSION: EBN could be used as a safe alternative to hormone replacement therapys for managing menopausal complications like bone degeneration.
METHODS: We built two models, for ER+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks) were assessed both internally and externally in 82,319 postmenopausal women from the Women's Health Initiative study. We performed decision curve analysis to compare ModelER+ and the Gail model (ModelGail) regarding their applicability in risk assessment for chemoprevention.
RESULTS: Parity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for ModelER+ and 0.59 for ModelER-. External validation reduced the C-statistic of ModelER+ (0.59) and ModelGail (0.57). In external evaluation of calibration, ModelER+ outperformed the ModelGail: the former led to a 9% overestimation of the risk of ER+ tumors, while the latter yielded a 22% underestimation of the overall BC risk. Compared with the treat-all strategy, ModelER+ produced equal or higher net benefits irrespective of the benefit-to-harm ratio of chemoprevention, while ModelGail did not produce higher net benefits unless the benefit-to-harm ratio was below 50. The clinical applicability, i.e. the area defined by the net benefit curve and the treat-all and treat-none strategies, was 12.7 × 10- 6 for ModelER+ and 3.0 × 10- 6 for ModelGail.
CONCLUSIONS: Modeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.