Construction and internal validation of a prediction nomogram for acquired premature ejaculation (APE) in PE patients.

ABSTRACT:

Background

A predictive model for acquired premature ejaculation (APE) in PE patients has not yet been established.

Objectives

This study was aimed at determining which factors were independently associated with the possibility of predicting APE in PE patients, and whether an effective pre-treatment nomogram for predicting their individual chances of being APE in PE patients can be developed.

Materials and methods

We analyzed the medical histories of 915 PE patients diagnosed at Xijing Hospital (Xi'an, China) and Northwest Women's and Children's Hospital (Xi'an, China) between May 2019 and May 2020. The diagnostic nomogram was developed using a multivariate logistic regression model by integrating selected significant variables determined through univariate analysis. Receiver operating characteristic curves were used to measure the predictive accuracy of the nomogram and its constituted variables, and calibrations were performed by making a comparison of nomogram-predicted probability with actual rate of APE.

Results

The independent predictors for APE that were identified include Age, Intra-vaginal Ejaculation Latency Time (IELT), Frequency of sexual desire (FSD), and Eysenck Personality Questionnaire-Revised Short Scale for Chinese (psychoticism) [EPQ-RSC(P)] scores. The predictive accuracy of the nomogram was 0.782 (95% CI: 0.723-0.841). Also, excellent agreement was demonstrated between the nomogram-predicted probability and the actual rate of APE.

Discussion and conclusion

We identified 4 independent predictors for APE and demonstrated the potential significant differences in psychoticism between LPE and APE patients. This was the first internally validated predictive APE nomogram where good discrimination and calibration were applied, and it offers a promising role in clinical practice. More studies are necessary for verification of its universal applicability.

SUBMITTER: Zhang L 

PROVIDER: S-EPMC8247358 | biostudies-literature |

REPOSITORIES: biostudies-literature