A model for predicting age at menopause in white women

<bold>Objective: </bold>To develop a model to predict the age at natural menopause and the risk for premenopausal hysterectomy.<bold>Design: </bold>Cross-sectional study.<bold>Setting: </bold>Multicenter study.<bold>Patient(s): </bold>A total of 1,345 white women.<bold>Intervention(s): </bold>Ten single nucleotide polymorphisms (SNPs) of seven estrogen (E)-metabolizing genes (i.e., catechol-O-methyltransferase, 17-beta-hydroxysteroid dehydrogenase type 1, cytochrome P-450 [CYP] 17, CYP1A1, CYP1B1, CYP19, and E receptor [ER] alpha) were analyzed by sequencing-on-chip-technology.<bold>Main Outcome Measure(s): </bold>Patients' reproductive and medical histories were ascertained and correlated to genotypes.<bold>Result(s): </bold>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.<bold>Conclusion(s): </bold>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. [ABSTRACT FROM AUTHOR]