External validation of a prediction tool to estimate the risk of human immunodeficiency virus infection amongst men who have sex with men

Data mining and machine learning in HIV infection risk research: An overview and recommendations

In the contemporary era, the applications of data mining and machine learning have permeated extensively into medical research, significantly contributing to areas such as HIV studies. By reviewing 38 articles published in the past 15 years, the study presents a roadmap based on seven different aspects, utilizing various machine learning techniques for both novice researchers and experienced researchers seeking to comprehend the current state of the art in this area. While traditional regression modeling techniques have been commonly used, researchers are increasingly adopting more advanced fully supervised machine learning and deep learning techniques, which often outperform the traditional methods in predictive performance. Additionally, the study identifies nine new open research issues and outlines possible future research plans to enhance the outcomes of HIV infection risk research. This review is expected to be an insightful guide for researchers, illuminating current practices and suggesting advancements in the field.

Associations between perceived and actual risk of HIV infection and HIV prevention services uptake among men who have sex with men in Shandong province, China: a cross-sectional study

BACKGROUND

Associations between perceived and actual risk of HIV infection and HIV prevention services uptake are inconclusive. This study aimed to evaluate the discrepancy between the perceived and actual HIV risk, and quantify the associations between perceived and actual risk of HIV infection and three HIV prevention services utilization among men who have sex with men (MSM) in Shandong province, China.

METHODS

A cross-sectional study was conducted in Shandong province in June 2021. Participants were eligible if they were born biologically male, aged 18 years or older, had negative or unknown HIV status, and had sex with men in the past year. Participants were recruited online. The discrepancy between their perceived and actual risk of HIV infection was evaluated by calculating the Kappa value. Bayesian model averaging was used to assess the associations between perceived and actual risk of HIV infection and HIV prevention services uptake.

RESULTS

A total of 1136 MSM were recruited, most of them were 30 years old or younger (59.9%), single (79.5%), with at least college education level (74.7%). Most participants (97.4%) perceived that they had low risk of HIV infection, and 14.1% were assessed with high actual risk. The discrepancy between their perceived and actual risk of HIV infection was evaluated with a Kappa value of 0.076 (P < 0.001). HIV testing uptake had a weak association with perceived high HIV prevalence among social networks (aOR = 1.156, post probability = 0.547). The perceived high HIV prevalence among national MSM was positive related to willingness to use PrEP (aOR = 1.903, post probability = 0.943) and PEP (aOR = 1.737, post probability = 0.829). Perceived personal risk (aOR = 4.486, post probability = 0.994) and perceived HIV prevalence among social networks (aOR = 1.280, post probability = 0.572) were related to history of using PrEP. Perceived personal risk (aOR = 3.144, post probability = 0.952), actual risk (aOR = 1.890, post probability = 0.950), and perceived risk among social networks (aOR = 1.502, post probability = 0.786) were related to history of using PEP.

CONCLUSIONS

There is discordance between perceived and actual personal risk of HIV infection among MSM in China. HIV risk assessment and education on HIV prevalence among MSM should be strengthened to assist high-risk populations aware their risk accurately and hence access HIV prevention services proactively.

Using HIV Risk Self-Assessment Tools to Increase HIV Testing in Men Who Have Sex With Men in Beijing, China: App-Based Randomized Controlled Trial

BACKGROUND

Men who have sex with men (MSM) in China hold a low-risk perception of acquiring HIV. This has resulted in an inadequate HIV testing rate.

OBJECTIVE

This study aims to investigate whether administering HIV risk self-assessments with tailored feedback on a gay geosocial networking (GSN) app could improve HIV testing rates and reduce sexual risk behaviors in Chinese MSM.

METHODS

We recruited MSM from Beijing, China, who used the GSN platform Blued in October 2017 in this 12-month double-blinded randomized controlled trial. From October 2017 to September 2018, eligible participants were randomly assigned to use a self-reported HIV risk assessment tool that provided tailored feedback according to transmission risk (group 1), access to the same HIV risk assessment without feedback (group 2), or government-recommended HIV education materials (control). All interventions were remotely delivered through the mobile phone-based app Blued, and participants were followed up at 1, 3, 6, and 12 months from baseline. The number of HIV tests over the 12-month study was the primary outcome and was assessed using an intention-to-treat analysis with an incident rate ratio (IRR). Unprotected anal intercourse (UAI) over 6 months was assessed by a modified intention-to-treat analysis and was the secondary outcome. All statistical analyses were conducted in SAS 9.3 (SAS Institute, Inc.), and a P value <.05 was considered statistically significant.

RESULTS

In total, 9280 MSM were recruited from baseline and were randomly assigned to group 1 (n=3028), group 2 (n=3065), or controls (n=3187). After follow-up, 1034 (34.1%), 993 (32.4%), and 1103 (34.6%) remained in each group, respectively. Over 12 months, group 1 took 391 tests (mean of 2.51 tests per person), group 2 took 352 tests (mean of 2.01 tests per person), and controls took 295 tests (mean of 1.72 tests per person). Group 1 had significantly more HIV testing than the control group (IRR 1.32, 95% CI 1.09-4.58; P=.01), while group 2 did not differ significantly from the controls (IRR 1.06, 95% CI 0.86-1.30; P=.60). The proportion of UAI was not statistically different among different groups, but all 3 groups had UAI, which declined from baseline.

CONCLUSIONS

Repeated HIV risk assessments coupled with tailored feedback through GSN apps improved HIV testing. Such interventions should be considered a simple way of improving HIV testing among MSM in China and increasing awareness of HIV status.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03320239; https://clinicaltrials.gov/study/NCT03320239.

Performance of HIV Infection Prediction Models in Men Who Have Sex with Men: A Systematic Review and Meta-Analysis

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.

An integrated online-to-offline model for HIV post-exposure prophylaxis (O2O-PEP) scale-up among men who have sex with men (MSM): Protocol for developing a pilot randomized controlled trial

Background

HIV post-exposure prophylaxis (PEP) is an evidence-based biomedical HIV prevention strategy consisting of a 28-day course of highly active antiretroviral therapy after recent potential exposure to HIV. However, awareness and uptake of PEP among men who have sex with men (MSM) are very low. Innovative and effective methods are needed to support PEP implementation among MSM. This work reports a protocol to design and evaluate an online-to-offline-based delivery model for HIV PEP uptake (O2O-PEP) in Chinese MSM.

Methods and analysis

This will be a two-phase study. In phase 1, we will develop an O2O-PEP model delivered through the WeChat mini-app (an app built into the WeChat platform). The O2O-PEP model initially includes four core components: a gamification-based education package for PEP, an online HIV risk assessment tool, a free online booking system for PEP initiation, and offline PEP prescription in the study hospitals. In phase 2, a two-arm pilot stratified randomized controlled trial comparing the O2O-PEP group with the standard care group will be designed to assess the feasibility, usability, and preliminary evidence of the efficacy of the O2O-PEP model in increasing PEP uptake among Chinese MSM. Model feasibility and usability will be further explored for broader model implementation.

Discussion

The O2O-PEP model is one of the first interventions in China aiming to promote PEP initiation in Chinese MSM. Components in the O2O-PEP model could assist MSM in better understanding their HIV infection risk and increasing accessibility of PEP. Moreover, coupled with online and offline recruitment, the O2O-PEP model has great potential to reach and engage MSM who are not involved in care by traditional methods.

Clinical trial registration

No. ChiCTR2200062538.

Risk assessment and identification of HIV infection among men who have sex with men: a cross-sectional study in Southwest China

OBJECTIVES

The HIV epidemic is around 7%-20% among men who have sex with men (MSM) in Southwest China. The low HIV-testing rate highlights the need for tools to identify high-risk MSM in resource-limited regions. Our aim was, therefore, to evaluate the HIV RISK Assessment Tool for HIV prediction and to characterise the primary infection among MSM in Southwest China.

DESIGN

A cross-sectional survey was conducted in Guizhou province between January and December 2018. Participants were recruited from gay communities, among whom the HIV RISK Assessment Tool was evaluated. Logistic regression was used to analyse items associated with HIV and the area under the curve (AUC) of the receiver operating curve was calculated to quantify discrimination performance.

PARTICIPANTS

1330 MSM participants, of which 83 (6.2%) tested as HIV positive.

RESULTS

A higher composite score of the tool (adjusted OR (aOR) 9.33, 95% CI 4.57 to 19.05) was independently associated with HIV infection. Items positively associated with HIV infection included having 2-5 same sex partners (aOR 2.43, 95% CI 1.28 to 4.64), always (aOR 5.93, 95% CI 1.59 to 22.13) or sometimes (aOR 4.25, 95% CI 2.09 to 8.64) having unprotected anal intercourse, taking both insertive and receptive sex roles (aOR 4.95, 95% CI 2.57 to 9.53) or only the receptive sex role (aOR 2.26, 95% CI 1.21 to 4.24). The tool showed an optimal discrimination ability (AUC=0.827), with a specificity of 0.747 and sensitivity of 0.785. Five MSM were identified with primary infection and had similar sexual risk behaviors as HIV-positive participants.

CONCLUSIONS

The HIV RISK Assessment Tool showed an overall good performance in predicting HIV risk among MSM in Guizhou province where the prevalence is still severe. This tool also demonstrated a potential to identify primary infection and is worth being promoted in resource-limited regions.