Assessing the utility of methods for menopausal transition classification in a population-based cohort: The CARDIA Study

When designing studies, researchers should collect the data required to construct a prediction model for classifying perimenopause status that includes age, smoking status, vasomotor symptoms, and cycle irregularities as predictors. The inclusion of additional data regarding menstrual cycles can be used to construct a full prediction model which may offer improved validity. Valid classification methods that use readily available data are needed to improve the scientific accuracy of research regarding perimenopause, promote research on this topic, and inform clinical practices.