A model for predicting age at menopause in white women

To develop a model to predict the age at natural menopause and the risk for premenopausal hysterectomy. Cross-sectional study. Multicenter study. A total of 1,345 white women. Ten single nucleotide polymorphisms (SNPs) of seven estrogen (E)-metabolizing genes (i.e., catechol- O-methyltransferase, 17-β-hydroxysteroid dehydrogenase type 1, cytochrome P-450 [CYP] 17, CYP1A1, CYP1B1, CYP19, and E receptor [ER] α) were analyzed by sequencing-on-chip-technology. Patients’ reproductive and medical histories were ascertained and correlated to genotypes. The model incorporates the number of full term pregnancies, the body mass index (BMI), a history of breast surgery, and the presence of CYP17 and CYP1B1-4 polymorphisms as well as the BMI to predict age at natural menopause and the risk for undergoing premenopausal hysterectomy. We present the first model to date, which can predict age at natural menopause and the risk for undergoing premenopausal hysterectomy based on genotype information and personal history.