ArticleInternational journal of environmental research and public health2022
Prediction Model for the Risk of HIV Infection among MSM in China: Validation and Stability.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 4 of them syntheses that pooled it.
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Who cites it
18 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Risk prediction models for targeted testing of HIV, hepatitis B and hepatitis C: a systematic review and meta-analysis.BMC infectious diseases · 2025Pooled it
- Machine learning for personalized risk assessment of HIV, syphilis, gonorrhoea and chlamydia: A systematic review and meta-analysis.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2025Pooled it
- Performance of HIV Infection Prediction Models in Men Who Have Sex with Men: A Systematic Review and Meta-Analysis.Archives of sexual behavior · 2023Pooled it
- Prevalence of sexualized drug use and risk of HIV among sexually active MSM in East and South Asian countries: systematic review and meta-analysis.Journal of the International AIDS Society · 2023Pooled it
- Integrating artificial intelligence and machine learning in HIV testing interventions in Gauteng Province, South Africa: Opportunities, challenges, and implementation strategies.Southern African journal of HIV medicine · 2026Article
- Environmental, socioeconomic, and sociocultural drivers of monkeypox transmission in the Democratic Republic of the Congo: a One Health perspective.Infectious diseases of poverty · 2025Article
- Genotypic Diversity and Pre-Treatment Resistance Characteristic Analysis Among Newly Diagnosed HIV-1-Positive MSM from 2020-2022 in Jiaxing City, China.Current HIV research · 2025Article
- The status of machine learning in HIV testing in South Africa: a qualitative inquiry with stakeholders in Gauteng province.Frontiers in digital health · 2025Article
- Machine learning-based prediction of mortality risk in AIDS patients with comorbid common AIDS-related diseases or symptoms.Frontiers in public health · 2025Article
- Examining the Effects of PrEP Use on Sexual Behaviors and Sexually Transmitted Infections Among Chinese Men who have Sex with Men: A Cross-Sectional Study.AIDS and behavior · 2024Article
- STI/HIV risk prediction model development-A novel use of public data to forecast STIs/HIV risk for men who have sex with men.Frontiers in public health · 2024Article
- Predicting the individualized risk of human immunodeficiency virus infection among sexually active women in Ethiopia using a nomogram: prediction model development and validation.Frontiers in public health · 2024Article
- Article
- Risk and Protective Profile of Men Who Have Sex With Men Using Mobile Voluntary HIV Counseling and Testing: Latent Class Analysis.JMIR public health and surveillance · 2023Article
- Exploring and Predicting the Drivers of Ongoing HIV-1 Transmission in Guangyuan, Sichuan.Infection and drug resistance · 2023Article
- Web-Based Risk Prediction Tool for an Individual's Risk of HIV and Sexually Transmitted Infections Using Machine Learning Algorithms: Development and External Validation Study.Journal of medical Internet research · 2022Article
- Predicting the risk of HIV infection among internal migrant MSM in China: An optimal model based on three variable selection methods.Frontiers in public health · 2022Article
- Internalized homophobia and sexual risk behavior in men who have sex with men: The mediational role of sexual self-concept.Frontiers in psychology · 2022Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The impact of psychosocial factors on increasing the risk of HIV infection among men who have sex with men (MSM) has attracted increasing attention. We aimed to develop and validate an integrated prediction model, especially incorporating emerging psychosocial variables, for predicting the risk of HIV infection among MSM. We surveyed and collected sociodemographic, psychosocial, and behavioral information from 547 MSM in China. The participants were split into a training set and a testing set in a 3:1 theoretical ratio. The prediction model was constructed by introducing the important variables selected with the least absolute shrinkage and selection operator (LASSO) regression, applying multivariate logistic regression, and visually assessing the risk of HIV infection through the nomogram. Receiver operating characteristic curves (ROC), Kolmogorov-Smirnov test, calibration plots, Hosmer-Lemeshow test and population stability index (PSI) were performed to test validity and stability of the model. Four of the 15 selected variables-unprotected anal intercourse, multiple sexual partners, involuntary subordination and drug use before sex-were included in the prediction model. The results indicated that the comprehensive prediction model we developed had relatively good predictive performance and stability in identifying MSM at high-risk for HIV infection, thus providing targeted interventions for high-risk MSM.
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