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Development and Validation of a Personalized Social Media Platform–Based HIV Incidence Risk Assessment Tool for Men Who Have Sex With Men in China
BACKGROUND: Personalized risk assessments can help medical providers determine targeted populations for counseling and risk reduction interventions. OBJECTIVE: The objective of this study was to develop a social media platform–based HIV risk prediction tool for men who have sex with men (MSM) in Chi...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6604506/ https://www.ncbi.nlm.nih.gov/pubmed/31215509 http://dx.doi.org/10.2196/13475 |
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author | Yun, Ke Xu, Junjie Leuba, Sequoia Zhu, Yunyu Zhang, Jing Chu, Zhenxing Geng, Wenqing Jiang, Yongjun Shang, Hong |
author_facet | Yun, Ke Xu, Junjie Leuba, Sequoia Zhu, Yunyu Zhang, Jing Chu, Zhenxing Geng, Wenqing Jiang, Yongjun Shang, Hong |
author_sort | Yun, Ke |
collection | PubMed |
description | BACKGROUND: Personalized risk assessments can help medical providers determine targeted populations for counseling and risk reduction interventions. OBJECTIVE: The objective of this study was to develop a social media platform–based HIV risk prediction tool for men who have sex with men (MSM) in China based on an independent MSM cohort to help medical providers determine target populations for counseling and risk reduction treatments. METHODS: A prospective cohort of MSM from Shenyang, China, followed from 2009 to 2016, was used to develop and validate the prediction model. The eligible MSM were randomly assigned to the training and validation dataset, and Cox proportional hazards regression modeling was conducted using predictors for HIV seroconversion selected by the training dataset. Discrimination and calibration were performed, and the related nomogram and social media platform–based HIV risk assessment tool were constructed. RESULTS: The characteristics of the sample between the training dataset and the validation dataset were similar. The risk prediction model identified the following predictors for HIV seroconversion: the main venue used to find male sexual partners, had condomless receptive or insertive anal intercourse, and used rush poppers. The model was well calibrated. The bootstrap C-index was 0.75 (95% CI 0.65-0.85) in the training dataset, and 0.60 (95% CI 0.45-0.74) in the validation dataset. The calibration plots showed good agreement between predicted risk and the actual proportion of no HIV infection in both the training and validation datasets. Nomogram and WeChat-based HIV incidence risk assessment tools for MSM were developed. CONCLUSIONS: This social media platform–based HIV infection risk prediction tool can be distributed easily, improve awareness of personal HIV infection risk, and stratify the MSM population based on HIV risk, thus informing targeted interventions for MSM at greatest risk for HIV infection. |
format | Online Article Text |
id | pubmed-6604506 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-66045062019-07-17 Development and Validation of a Personalized Social Media Platform–Based HIV Incidence Risk Assessment Tool for Men Who Have Sex With Men in China Yun, Ke Xu, Junjie Leuba, Sequoia Zhu, Yunyu Zhang, Jing Chu, Zhenxing Geng, Wenqing Jiang, Yongjun Shang, Hong J Med Internet Res Original Paper BACKGROUND: Personalized risk assessments can help medical providers determine targeted populations for counseling and risk reduction interventions. OBJECTIVE: The objective of this study was to develop a social media platform–based HIV risk prediction tool for men who have sex with men (MSM) in China based on an independent MSM cohort to help medical providers determine target populations for counseling and risk reduction treatments. METHODS: A prospective cohort of MSM from Shenyang, China, followed from 2009 to 2016, was used to develop and validate the prediction model. The eligible MSM were randomly assigned to the training and validation dataset, and Cox proportional hazards regression modeling was conducted using predictors for HIV seroconversion selected by the training dataset. Discrimination and calibration were performed, and the related nomogram and social media platform–based HIV risk assessment tool were constructed. RESULTS: The characteristics of the sample between the training dataset and the validation dataset were similar. The risk prediction model identified the following predictors for HIV seroconversion: the main venue used to find male sexual partners, had condomless receptive or insertive anal intercourse, and used rush poppers. The model was well calibrated. The bootstrap C-index was 0.75 (95% CI 0.65-0.85) in the training dataset, and 0.60 (95% CI 0.45-0.74) in the validation dataset. The calibration plots showed good agreement between predicted risk and the actual proportion of no HIV infection in both the training and validation datasets. Nomogram and WeChat-based HIV incidence risk assessment tools for MSM were developed. CONCLUSIONS: This social media platform–based HIV infection risk prediction tool can be distributed easily, improve awareness of personal HIV infection risk, and stratify the MSM population based on HIV risk, thus informing targeted interventions for MSM at greatest risk for HIV infection. JMIR Publications 2019-06-18 /pmc/articles/PMC6604506/ /pubmed/31215509 http://dx.doi.org/10.2196/13475 Text en ©Ke Yun, Junjie Xu, Sequoia Leuba, Yunyu Zhu, Jing Zhang, Zhenxing Chu, Wenqing Geng, Yongjun Jiang, Hong Shang. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 18.06.2019. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Yun, Ke Xu, Junjie Leuba, Sequoia Zhu, Yunyu Zhang, Jing Chu, Zhenxing Geng, Wenqing Jiang, Yongjun Shang, Hong Development and Validation of a Personalized Social Media Platform–Based HIV Incidence Risk Assessment Tool for Men Who Have Sex With Men in China |
title | Development and Validation of a Personalized Social Media Platform–Based HIV Incidence Risk Assessment Tool for Men Who Have Sex With Men in China |
title_full | Development and Validation of a Personalized Social Media Platform–Based HIV Incidence Risk Assessment Tool for Men Who Have Sex With Men in China |
title_fullStr | Development and Validation of a Personalized Social Media Platform–Based HIV Incidence Risk Assessment Tool for Men Who Have Sex With Men in China |
title_full_unstemmed | Development and Validation of a Personalized Social Media Platform–Based HIV Incidence Risk Assessment Tool for Men Who Have Sex With Men in China |
title_short | Development and Validation of a Personalized Social Media Platform–Based HIV Incidence Risk Assessment Tool for Men Who Have Sex With Men in China |
title_sort | development and validation of a personalized social media platform–based hiv incidence risk assessment tool for men who have sex with men in china |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6604506/ https://www.ncbi.nlm.nih.gov/pubmed/31215509 http://dx.doi.org/10.2196/13475 |
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