Developing a prediction model for the self-evaluation of erectile dysfunction in an adult male population

The purpose of this study was to develop an erectile dysfunction (ED) risk assessment tool suitable for the general population. Based on an ED network survey of the general adult male population in China from October to November 2019, a total of 612 cases with a mean age of 31 years (interquartile range: 28-37) with valid data were collected: 357 cases were assigned to the training set and 255 to the validation set. The ED risk prediction model was established by multifactor logistic regression analysis, and nomograms were constructed for visualisation. In the validation set, a receiver operating characteristic curve, calibration curve analysis and decision curve analysis were used to evaluate the discrimination, calibration and clinical usefulness of the ED risk prediction model. Based on multivariate logistic regression, education, smoking, chronic diseases, feelings about one's spouse, frequency of sexual intercourse, masturbation and self-reported sexual satisfaction were selected as predictors to develop the ED prediction model. The model had good discrimination, calibration and clinical applicability. The ED risk prediction model developed in this study can effectively predict ED risk in the general population.