Department of Urology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
St. George's University School of Medicine, West Indies, Grenada.
Andrology. 2021 May;9(3):886-893. doi: 10.1111/andr.12956. Epub 2020 Dec 26.
A predictive model for acquired premature ejaculation (APE) in PE patients has not yet been established.
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.
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.
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.
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.
目前尚未建立预测获得性早泄(APE)的模型。
本研究旨在确定哪些因素与预测 PE 患者发生 APE 的可能性独立相关,以及是否可以为预测 PE 患者个体发生 APE 的可能性制定有效的治疗前预测列线图。
我们分析了 2019 年 5 月至 2020 年 5 月期间在西京医院(西安,中国)和西北妇女儿童医院(西安,中国)诊断为 PE 的 915 例患者的病历。使用多元逻辑回归模型,通过整合单变量分析确定的有意义的变量来开发诊断列线图。通过比较列线图预测的概率与实际 APE 发生率,使用受试者工作特征曲线评估列线图及其构成变量的预测准确性,并进行校准。
确定的 APE 独立预测因子包括年龄、阴道内射精潜伏期(IELT)、性欲频率(FSD)和艾森克人格问卷修订简式量表中国版(精神质)[EPQ-RSC(P)]评分。该列线图的预测准确性为 0.782(95%CI:0.723-0.841)。此外,列线图预测的概率与 APE 的实际发生率之间表现出极好的一致性。
我们确定了 4 个 APE 的独立预测因子,并证明了轻度早泄(LPE)和 APE 患者之间在精神质方面存在显著差异。这是第一个进行内部验证的预测 APE 的列线图,具有良好的区分度和校准度,在临床实践中具有广阔的应用前景。需要进一步的研究来验证其普遍适用性。