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HIV 感染风险预测评分:来自中国男男性行为者的横断面数据的开发和内部验证。

Risk Prediction Score for HIV Infection: Development and Internal Validation with Cross-Sectional Data from Men Who Have Sex with Men in China.

机构信息

Medical Research & Biometrics Center, National Center for Cardiovascular Diseases, Beijing, China.

Vanderbilt Institute for Global Health, Vanderbilt University Medical Center, Nashville, TN, USA.

出版信息

AIDS Behav. 2018 Jul;22(7):2267-2276. doi: 10.1007/s10461-018-2129-y.

Abstract

Receptive anal intercourse, multiple partners, condomless sex, sexually transmitted infections (STIs), and drug/alcohol addiction are familiar factors that correlate with increased human immunodeficiency virus (HIV) risk among men who have sex with men (MSM). To improve estimation to HIV acquisition, we created a composite score using questions from routine survey of 3588 MSM in Beijing, China. The HIV prevalence was 13.4%. A risk scoring tool using penalized maximum likelihood multivariable logistic regression modeling was developed, deploying backward step-down variable selection to obtain a reduced-form model. The full penalized model included 19 sexual predictors, while the reduced-form model had 12 predictors. Both models calibrated well; bootstrap-corrected c-indices were 0.70 (full model) and 0.71 (reduced-form model). Non-Beijing residence, short-term living in Beijing, illegal drug use, multiple male sexual partners, receptive anal sex, inconsistent condom use, alcohol consumption before sex, and syphilis infection were the strongest predictors of HIV infection. Discriminating higher-risk MSM for targeted HIV prevention programming using a validated risk score could improve the efficiency of resource deployment for educational and risk reduction programs. A valid risk score can also identify higher risk persons into prevention and vaccine clinical trials, which would improve trial cost-efficiency.

摘要

接受肛交、多个性伴侣、无保护性行为、性传播感染(STIs)和药物/酒精成瘾是与男男性行为者(MSM)中人类免疫缺陷病毒(HIV)风险增加相关的熟悉因素。为了提高对 HIV 感染的估计,我们使用来自中国北京 3588 名 MSM 常规调查的问题创建了一个综合评分。HIV 感染率为 13.4%。使用惩罚最大似然多变量逻辑回归建模开发了一种风险评分工具,采用逐步向后变量选择来获得简化模型。全惩罚模型包括 19 个性预测因素,而简化模型有 12 个预测因素。两个模型都校准得很好;自举校正的 c 指数分别为 0.70(全模型)和 0.71(简化模型)。非北京居住、短期在北京居住、吸毒、多个男性性伴侣、接受肛交、避孕套使用不一致、性行为前饮酒和梅毒感染是非 HIV 感染的最强预测因素。使用经过验证的风险评分对高危 MSM 进行有针对性的 HIV 预防规划可以提高教育和减少风险计划的资源部署效率。有效的风险评分还可以将高危人群纳入预防和疫苗临床试验,从而提高试验的成本效益。

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