Serum estradiol: oocyte ratio as a predictor of reproductive outcome: an analysis of data from >9000 IVF cycles in the Republic of Ireland

Purpose The purpose of this study was to evaluate the serum estradiol (E2) per oocyte ratio (EOR) as a function of selected embryology events and reproductive outcomes with IVF. Methods This retrospective analysis included all IVF cycles where oocyte collection and fresh transfer occurred between January 2001 and November 2012 at a single institution. Patients were divided by three age groups (<35, 35–39, and ≥40 years) and further stratified into nine groups based on EOR (measured in pmol/L/oocyte). Terminal serum E2 (pmol/mL) was recorded on day of hCG trigger administration, and fertilization rate, cleavage rate, number of good quality embryos, and reproductive outcomes were recorded for each IVF cycle. Results During the study interval, 9109 oocyte retrievals were performed for 5499 IVF patients (mean = 1.7 cycles/patient). A total of 63.4 % of transfers were performed on day 3 (n = 4926), while 36.6 % were carried out on day 5 (n = 2843). Clinical pregnancy rates were highest in patients with EOR of 250–750 and declined as this ratio increased, independent of patient age. While the odds ratio (OR) for clinical pregnancy where EOR = 250–750 vs. EOR > 1500 was 3.4 (p < 0.001; 95 % CI 2.67–4.34), no statistically significant correlation was seen in fertilization, cleavage rates or number of good quality embryos as a function of EOR. Conclusions Predicting reproductive outcomes with IVF has great utility both for patients and providers. The former have the opportunity to build realistic expectations, and the latter are better able to counsel according to measured clinical parameters. A better understanding of follicular dynamics and ovarian response to gonadotropin stimulation could optimize IVF treatments going forward.

Prediction of breast cancer risk based on profiling with common genetic variants

BACKGROUND: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. METHODS: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. RESULTS: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. CONCLUSIONS: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.