代谢综合征后前列腺增生风险预测列线图模型的建立

Establishment of nomogram prediction model for BPH in metabolic syndrome

目的:建立代谢综合征患者发生前列腺增生的列线图预测模型。方法:收集2019年1月至4月在我院进行健康体检的男性体检者1000例的临床资料,随访1.5年,最终将690例研究对象纳入分析,其中185例发生代谢综合征,根据是否发生良性前列腺增生(BPH),将其分为BPH亚组(45例)和非BPH亚组(140例)。比较两组患者的代谢指标,通过多因素Logistic回归分析筛选出BPH的独立危险因素,构建预测模型,并绘制列线图。结果:多因素Logistic回归分析结果显示,BMI、血糖、甘油三酯及低密度脂蛋白是BPH的独立危险因素,其OR分别为1.455(95%CI:1.296-1.633)、1.516(95%CI:1.258-1.828)、1.400(95%CI:1.095-1.791)、1.463(95%CI:1.156-1.851)。用于预测BPH风险的列线图显示出良好的一致系数,Cindex为0.857。结论:不同代谢指标可影响BPH的发生发展,利用绘制的列线图进行风险预测,有助于医师与患者的交流更直观及量化。

Objective:To establish a nomographic prediction model of prostatic hyperplasia in metabolic syndrome.Methods:The data of 1000 male physical examiners who underwent physical examination in our hospital from January to April 2019 were collected and followed up for 1.5 years.Finally,690 subjects were included in the analysis,of which 185 cases developed metabolic syndrome.According to whether BPH occurred,they were divided into 45 cases in BPH group and 140 cases in non BPH group.The two groups of metabolic indexes were compared,the independent risk factors were selected by multivariate logistic regression analysis,the prediction model was constructed,and the nomogram was drawn.Results:Multivariate logistic regression analysis showed that BMI,blood glucose,triglyceride and low density lipoprotein were independent risk factors for BPH,and their oR were 1.455(95%CI:1.296-1.633),1.516(95%CI:1.258-1.828),1.400(95%CI:1.095-1.791)and 1.463(95%CI:1.156-1.851)respectively.The nomogram used to predict BPH risk showed a good consistency coefficient,with a c-index of 0.857.Conclusion:Different metabolic indexes can affect the occurrence and development of BPH.Using the nomogram to predict the risk is helpful to make the communication between doctors and patients more intuitive and quantitative.