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

Luo, Qianqian; Luo, Yongchuan; Cui, Tianyu; Li, Tianying

doi:10.1007/s10508-023-02574-x

Cited by 4 publications

(5 citation statements)

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“…Of the respondents, 96.3% identified as male, 3.2% as female, and 0.5% as transgender individuals. The higher proportion of male respondents is closely associated with the Men who have Sex with Men (MSM) population [ 18 ], where anal sex is a sexual practice that can increase the risk of HIV transmission [ 19 ]. Regarding age distribution, the majority of the participants in the survey fell within the young and middle-aged groups, with 41.3% of respondents aged 31–40, followed by 36.5% aged 21–30, 16.6% aged 41–50, and 5.5% aged 51–60.…”

Section: Resultsmentioning

confidence: 99%

“…Currently, Chinese law simply lists sexual partners and spouses, without further distinguishing between the two. 18 Real-life situations can be far more complex than what the law dictates, however. The blurred definitions of "spouse" and "sexual partner" undeniably pose a challenge to applying the law [28], which may require further judicial, if not legislative distinction between the two.…”

Section: Challenges Of the Legal Obligation: When And Whether To Disc...mentioning

confidence: 99%

“… Article 38 of the "Regulations on the Prevention and Control of HIV/ AIDS" in China states: (2) PLHIV shall promptly inform individuals with whom they have sexual relations of their infection or illness 17. Article 1053 of 2021 Civil Code: If one of the parties suffers from a serious disease, he shall truthfully inform the other party of such disease prior to marriage registration; where such information is not truthfully provided, the other party may apply to the people's court to annul the marriage 18. In the "Regulations on the Prevention and Control of HIV/AIDS in Yunnan Province, " Article 20 specifies, "PLHIV/AIDS shall promptly inform their spouses or sexual partners of their HIV infection.…”

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Balancing public health and privacy rights: a mixed-methods study on disclosure obligations of people living with HIV to their partners in China

Xie,

Duan

2024

Harm Reduct J

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Background In 2021, a Chinese court, based on the newly enacted Civil Code, first revoked a marriage license due to the spouse’s failure to disclose their HIV infection before the marriage. This landmark case ignited a fresh debate on whether people living with HIV (PLHIV) have a legal duty to inform their spouses and sexual partners. Advances in medicine have partially isolated HIV transmission from sexual contact, extending the legal basis for the obligation to disclose beyond disease prevention. This study investigates some possibly unforeseen challenges for PLHIV in China to fulfill this duty, and the outcomes of their decisions in light of the government’s goal to promote health. Methods This study aims to provide a detailed examination of the legal provisions and practices concerning partner notification among PLHIV in China. A mixed-methods research approach was employed between 2019 and 2020, combining questionnaire surveys, in-depth interviews, and participatory observations. A total of 433 valid responses were obtained through a questionnaire posted on a Chinese online platform for PLHIV. Following the collection and random coding of the questionnaire data, 40 individuals living with HIV were selected for in-depth interviews. Subsequently, a six-month field investigation was conducted in Guan ai jia yuan (Caring Home) in Jinhua City to further explore this issue. Results A considerable proportion of PLHIV exhibit a high rate of disclosure to their spouses (nearly 80%). In the context of sexual partners, 56% of PLHIV stated that their sexual partners were aware of their HIV infection. Whether married PLHIV disclosing to their spouses or unmarried/divorced PLHIV disclosing to sexual partners, however, a substantial majority expressed apprehension about the potential disruption to their relationships that the disclosure might cause. The sole exception was observed among married PLHIV in extramarital relationships who demonstrated a slightly diminished level of concern in this context. Reasons for non-disclosure predominantly included undetectable viral load and the adoption of protective measures. Discussion This study reveals that a prevailing “HIV stigma” hinders PLHIV from voluntarily fulfilling the disclosure duties bestowed by Article 38 of the Regulations on the Prevention and Control of HIV/AIDS, and the unclear legal provisions of the new Civil Code play a significant role in this regard. Addressing this issue necessitates not only increasing societal tolerance toward PLHIV and reducing instances of social exclusion but also shifting the legal basis of disclosure duties from disease prevention to rights and obligations within the legal relationships of the parties involved. When it comes to the recipients of disclosure, for instance, it is crucial to differentiate between spouses and sexual partners. As for PLHIV failing to fulfill their disclosure duties, apart from interventions involving indirect notifications, the addition of further legal responsibilities may not be advisable. Intentional transmission actions, on the other hand, should still be subject to severe penalties. Clinical trial number: Not applicable.

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Section: Resultsmentioning

confidence: 99%

Section: Challenges Of the Legal Obligation: When And Whether To Disc...mentioning

confidence: 99%

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confidence: 99%

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Balancing public health and privacy rights: a mixed-methods study on disclosure obligations of people living with HIV to their partners in China

Xie,

Duan

2024

Harm Reduct J

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“…They employed Bayesian generalized linear mixed-effect models and meta-regression analysis to scrutinize trends in HIV testing, treatment cascade, and HIV incidence among MSM in Africa [ 54 ]. Another study synthesized 18 evaluation models, revealing that machine learning models exhibit fair to good discriminatory performance in predicting HIV infection risk (AUC 0.62, 95% CI: 0.51 to 0.73) [ 55 ]. Machine learning also demonstrates promising predictive and evaluative effects in clinical antiretroviral treatment (ART) [ 56 ] and pre-exposure prophylaxis (PrEP).…”

Section: Discussionmentioning

confidence: 99%

The predictive accuracy of machine learning for the risk of death in HIV patients: a systematic review and meta-analysis

Li,

Feng,

et al. 2024

BMC Infect Dis

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Background Early prediction of mortality in individuals with HIV (PWH) has perpetually posed a formidable challenge. With the widespread integration of machine learning into clinical practice, some researchers endeavor to formulate models predicting the mortality risk for PWH. Nevertheless, the diverse timeframes of mortality among PWH and the potential multitude of modeling variables have cast doubt on the efficacy of the current predictive model for HIV-related deaths. To address this, we undertook a systematic review and meta-analysis, aiming to comprehensively assess the utilization of machine learning in the early prediction of HIV-related deaths and furnish evidence-based support for the advancement of artificial intelligence in this domain. Methods We systematically combed through the PubMed, Cochrane, Embase, and Web of Science databases on November 25, 2023. To evaluate the bias risk in the original studies included, we employed the Predictive Model Bias Risk Assessment Tool (PROBAST). During the meta-analysis, we conducted subgroup analysis based on survival and non-survival models. Additionally, we utilized meta-regression to explore the influence of death time on the predictive value of the model for HIV-related deaths. Results After our comprehensive review, we analyzed a total of 24 pieces of literature, encompassing data from 401,389 individuals diagnosed with HIV. Within this dataset, 23 articles specifically delved into deaths during long-term follow-ups outside hospital settings. The machine learning models applied for predicting these deaths comprised survival models (COX regression) and other non-survival models. The outcomes of the meta-analysis unveiled that within the training set, the c-index for predicting deaths among people with HIV (PWH) using predictive models stands at 0.83 (95% CI: 0.75–0.91). In the validation set, the c-index is slightly lower at 0.81 (95% CI: 0.78–0.85). Notably, the meta-regression analysis demonstrated that neither follow-up time nor the occurrence of death events significantly impacted the performance of the machine learning models. Conclusions The study suggests that machine learning is a viable approach for developing non-time-based predictions regarding HIV deaths. Nevertheless, the limited inclusion of original studies necessitates additional multicenter studies for thorough validation.

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“…The Denver Risk Score tool is an evidence-supported tool used to collect and assign potential HIV risk using information, such as sexual partners, practices, and injection drug use behaviors. Utilization of a screening tool is the first step in disrupting the continued transmission of HIV through the identification of those at risk (Luo et al, 2023). In the systematic review and meta-analysis from Luo et al (2023), the implementation of HIV risk prediction modules such as the Denver HIV Risk Score tool showed moderate-to-good discrimination performance within the MSM population who are known to be at substantial risk.…”

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confidence: 99%

Unlocking HIV Prevention in Primary Care: Implementation of the Denver HIV Risk Score Tool in an Urban Michigan Primary Care Setting

Knight

2024

J Assoc Nurses AIDS Care

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The Unlocking HIV Prevention Project was designed and implemented to address missed opportunities to address HIV risks. The project's site noted a gap in the use of an HIV risk assessment tool during primary care visits. The purpose of this quality-improvement project was to determine whether the translation of the Denver HIV Risk Score tool into primary care visits would affect the number of individuals identified as at risk for HIV and increase preexposure prophylaxis (PrEP) prescription rates among adults seeking care at an urban Michigan primary care clinic. Data on PrEP prescriptions were collected from the electronic health record before and after implementation of the HIV risk assessment tool. Before implementing this screening tool, no patients were identified as at risk and no prescriptions for PrEP were written. After implementation, 16 patients were identified as at risk with seven prescriptions written. These data suggest that this tool has the potential to improve the identification of patients at risk for HIV who are candidates for PrEP prescribing in primary care.

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

Cited by 4 publications

References 52 publications

Balancing public health and privacy rights: a mixed-methods study on disclosure obligations of people living with HIV to their partners in China

Balancing public health and privacy rights: a mixed-methods study on disclosure obligations of people living with HIV to their partners in China

The predictive accuracy of machine learning for the risk of death in HIV patients: a systematic review and meta-analysis

Unlocking HIV Prevention in Primary Care: Implementation of the Denver HIV Risk Score Tool in an Urban Michigan Primary Care Setting

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