当前位置: X-MOL 学术Arch. Sex. Behav. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Performance of HIV Infection Prediction Models in Men Who Have Sex with Men: A Systematic Review and Meta-Analysis
Archives of Sexual Behavior ( IF 2.9 ) Pub Date : 2023-03-08 , DOI: 10.1007/s10508-023-02574-x
Qianqian Luo 1 , Yongchuan Luo 2 , Tianyu Cui 1 , Tianying Li 1
Affiliation  

Effective ways to identify and predict men who have sex with men (MSM) at substantial risk for HIV is a global priority. HIV risk assessment tools can improve individual risk awareness and subsequent health-seeking actions. We sought to identify and characterize the performance of HIV infection risk prediction models in MSM through systematic review and meta-analysis. PubMed, Embase, and The Cochrane Library were searched. Eighteen HIV infection risk assessment models with a total of 151,422 participants and 3643 HIV cases were identified, eight of which have been externally validated by at least one study (HIRI-MSM, Menza Score, SDET Score, Li Model, DHRS, Amsterdam Score, SexPro model, and UMRSS). The number of predictor variables in each model ranged from three to 12, age, the number of male sexual partners, unprotected receptive anal intercourse, recreational drug usage (amphetamines, poppers), and sexually transmitted infections were critical scoring variables. All eight externally validated models performed well in terms of discrimination, with the pooled area under the receiver operating characteristic curve (AUC) ranging from 0.62 (95%CI: 0.51 to 0.73, SDET Score) to 0.83 (95%CI: 0.48 to 0.99, Amsterdam Score). Calibration performance was only reported in 10 studies (35.7%, 10/28). The HIV infection risk prediction models showed moderate-to-good discrimination performance. Validation of prediction models across different geographic and ethnic environments is needed to ensure their real-world application.



中文翻译:

男男性行为者艾滋病毒感染预测模型的表现:系统回顾和荟萃分析

有效地识别和预测存在艾滋病毒高风险的男男性行为者 (MSM) 是全球优先考虑的事项。艾滋病毒风险评估工具可以提高个人风险意识和随后的健康寻求行动。我们试图通过系统回顾和荟萃分析来确定和描述 MSM 中 HIV 感染风险预测模型的表现。检索了 PubMed、Embase 和 Cochrane 图书馆。确定了 18 个 HIV 感染风险评估模型,共有 151,422 名参与者和 3643 个 HIV 病例,其中 8 个已通过至少一项研究进行外部验证(HIRI-MSM、Menza 评分、SDET 评分、Li 模型、DHRS、Amsterdam 评分、 SexPro 模型和 UMRSS)。每个模型中的预测变量数量从 3 到 12 个不等,包括年龄、男性性伴侣的数量、无保护的肛交、娱乐性药物(安非他明、poppers)的使用和性传播感染是关键的评分变量。所有八个外部验证模型在区分度方面均表现良好,受试者工作特征曲线 (AUC) 下的合并面积范围为 0.62(95%CI:0.51 至 0.73,SDET 评分)至 0.83(95%CI:0.48 至 0.99) ,阿姆斯特丹分数)。仅 10 项研究报告了校准性能 (35.7%, 10/28)。HIV感染风险预测模型显示出中等至良好的区分性能。需要在不同地理和种族环境中验证预测模型,以确保其在现实世界中的应用。所有八个外部验证模型在区分度方面均表现良好,受试者工作特征曲线 (AUC) 下的合并面积范围为 0.62(95%CI:0.51 至 0.73,SDET 评分)至 0.83(95%CI:0.48 至 0.99) ,阿姆斯特丹分数)。仅 10 项研究报告了校准性能 (35.7%, 10/28)。HIV感染风险预测模型显示出中等至良好的区分性能。需要在不同地理和种族环境中验证预测模型,以确保其在现实世界中的应用。所有八个外部验证模型在区分度方面均表现良好,受试者工作特征曲线 (AUC) 下的合并面积范围为 0.62(95%CI:0.51 至 0.73,SDET 评分)至 0.83(95%CI:0.48 至 0.99) ,阿姆斯特丹分数)。仅 10 项研究报告了校准性能 (35.7%, 10/28)。HIV感染风险预测模型显示出中等至良好的区分性能。需要在不同地理和种族环境中验证预测模型,以确保其在现实世界中的应用。10/28)。HIV感染风险预测模型显示出中等至良好的区分性能。需要在不同地理和种族环境中验证预测模型,以确保其在现实世界中的应用。10/28)。HIV感染风险预测模型显示出中等至良好的区分性能。需要在不同地理和种族环境中验证预测模型,以确保其在现实世界中的应用。

更新日期:2023-03-09
down
wechat
bug