Development and External Validation of a Home-based Risk Prediction Model of Natural Onset of Menopause—Teuta

Abstract

Abstract Objective To develop and externally validate a 10-year risk prediction model of natural onset of menopause using ready-to-use predictors. Design Population-based prospective cohort study. Participants Community-dwelling, premenopausal women aged 28 years and older enrolled in the Swiss (CoLaus) and Dutch (PREVEND) study. Main outcome measure Incidence of self-reported natural menopause. Model development Based on existing literature, 11 predictors were tested in this study. The CoLaus cohort was used to develop the model by applying the backward-elimination approach and Bayesian Model Averaging. Internal validation was performed by bootstrapping. External validation was performed using data from the PREVEND cohort and recalibrating the baseline survival estimate. C-statistics, calibration slopes, and expected/observed probabilities were calculated as measures of model internal and/or external performances. Results The final analysis included 750 and 1032 premenopausal women from the CoLaus and the PREVEND cohorts, respectively. Among them, 445 (59%) from CoLaus and 387 (38%) from PREVEND experienced menopause over a median follow-up of 10.7 and 9 years, respectively. The final model included age, alcohol consumption, smoking status, education level, and systolic blood pressure. Upon external calibration in the PREVEND cohort, the model exhibited good discrimination, with a C-statistic of 0.888 and an expected/observed probability of 0.82. Conclusion We present the first internally and externally validated prediction model of natural menopause onset using readily available predictors. Validation of our model to other populations is needed.