Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China.
Dermatology Hospital, Southern Medical University, Guangzhou, China.
BMC Infect Dis. 2021 Nov 29;21(1):1199. doi: 10.1186/s12879-021-06912-z.
The purpose of this study was to develop and validate a simple-to-use nomogram for the prediction of syphilis infection among men who have sex with men (MSM) in Guangdong Province.
A serial cross-sectional data of 2184 MSM from 2017 to 2019 was used to develop and validate the nomogram risk assessment model. The eligible MSM were randomly assigned to the training and validation dataset. Factors included in the nomogram were determined by multivariate logistic regression analysis based on the training dataset. The receiver operating characteristic (ROC) curves was used to assess its predictive accuracy and discriminative ability.
A total of 2184 MSM were recruited in this study. The prevalence of syphilis was 18.1% (396/2184). Multivariate logistic analysis found that age, the main venue used to find sexual partners, condom use in the past 6 months, commercial sex in the past 6 months, infection with sexually transmitted diseases (STD) in the past year were associated with syphilis infection using the training dataset. All these factors were included in the nomogram model that was well calibrated. The C-index was 0.80 (95% CI 0.76-0.84) in the training dataset, and 0.79 (95% CI 0.75-0.84) in the validation dataset.
A simple-to-use nomogram for predicting the risk of syphilis has been developed and validated among MSM in Guangdong Province. The proposed nomogram shows good assessment performance.
本研究旨在开发和验证一种简单易用的列线图,用于预测广东省男男性行为者(MSM)中的梅毒感染。
使用 2017 年至 2019 年 2184 名 MSM 的系列横断面数据来开发和验证列线图风险评估模型。合格的 MSM 被随机分配到训练和验证数据集。基于训练数据集的多变量逻辑回归分析确定列线图中包含的因素。使用接收者操作特征(ROC)曲线评估其预测准确性和区分能力。
本研究共招募了 2184 名 MSM。梅毒的患病率为 18.1%(396/2184)。多变量逻辑分析发现,年龄、寻找性伴侣的主要场所、过去 6 个月的 condom 使用情况、过去 6 个月的商业性性行为、过去一年的性传播疾病(STD)感染与使用训练数据集的梅毒感染相关。所有这些因素都包含在列线图模型中,该模型具有良好的校准度。训练数据集中的 C 指数为 0.80(95%置信区间 0.76-0.84),验证数据集中的 C 指数为 0.79(95%置信区间 0.75-0.84)。
已开发并验证了一种用于预测广东省 MSM 梅毒感染风险的简单易用的列线图。所提出的列线图显示出良好的评估性能。