Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

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

Performance of HIV Infection Prediction Models in Men Who Have Sex with Men: A Systematic Review... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archives of Sexual Behavior Springer Journals

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

Download PDF
13 pages

Loading next page...
 
/lp/springer-journals/performance-of-hiv-infection-prediction-models-in-men-who-have-sex-rAXTl07lYZ
Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
ISSN
0004-0002
eISSN
1573-2800
DOI
10.1007/s10508-023-02574-x
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Archives of Sexual Behavior – Springer Journals

Published: Mar 8, 2023

Keywords: HIV; Men who have sex with men; Screening models; Discrimination; Meta-analysis; Sexual orientation

References

  • Cardiovascular disease risk profiles
    Anderson, KM; Odell, PM; Wilson, PW; Kannel, WB
  • Sexual risk behavior trajectories among MSM at risk for HIV in Amsterdam, the Netherlands
    Basten, M; Heijne, JCM; Geskus, R; Den Daas, C; Kretzschmar, M; Matser, A
  • Are Centers for Disease Control and Prevention guidelines for preexposure prophylaxis specific enough? Formulation of a personalized HIV risk score for pre-exposure prophylaxis initiation
    Beymer, MR; Weiss, RE; Sugar, CA; Bourque, LB; Gee, GC; Morisky, DE; Bolan, RK
  • Global epidemiology of HIV infection in men who have sex with men
    Beyrer, C; Baral, SD; van Griensven, F; Goodreau, SM; Chariyalertsak, S; Wirtz, AL; Brookmeyer, R
  • Predictive ability of risk assessment tool regarding HIV infection for men who have sex with men
    Chen, XX; Li, LL; Wang, SL; Xu, YY; Li, Y; Chen, J; Lin, HJ
  • Human immunodeficiency virus prevalence is increasing among men who have sex with men in China: Findings from a review and meta-analysis
    Chow, EP; Wilson, DP; Zhang, J; Jing, J; Zhang, L
  • Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD Statement
    Collins, GS; Reitsma, JB; Altman, DG; Moons, KG
  • A guide to systematic review and meta-analysis of prediction model performance
    Debray, TP; Damen, JA; Snell, KI; Ensor, J; Hooft, L; Reitsma, JB; Riley, RD; Moons, KG
  • Development and validation of a risk score to assist screening for acute HIV-1 infection among men who have sex with men
    Dijkstra, M; de Bree, GJ; Stolte, IG; Davidovich, U; Sanders, EJ; Prins, M; Schim van der Loeff, MF
  • Validation of the san diego early test score for early human immunodeficiency virus infection among amsterdam men who have sex with men
    Dijkstra, M; Lin, TC; de Bree, GJ; Hoenigl, M; Schim van der Loeff, MF
  • Prediction model for the risk of HIV infection among MSM in China: Validation and stability
    Dong, Y; Liu, S; Xia, D; Xu, C; Yu, X; Chen, H; Wang, Y
  • Search filters for finding prognostic and diagnostic prediction studies in Medline to enhance systematic reviews
    Geersing, GJ; Bouwmeester, W; Zuithoff, P; Spijker, R; Leeflang, M; Moons, KG
  • Using HIV risk prediction tools to identify candidates for pre-exposure prophylaxis: Perspectives from patients and primary care providers
    Gilkey, MB; Marcus, JL; Garrell, JM; Powell, VE; Maloney, KM; Krakower, DS
  • Validation of a quantitative HIV risk prediction tool using a national HIV testing cohort
    Haukoos, JS; Hopkins, E; Bucossi, MM; Lyons, MS; Rothman, RE; White, DA; Thrun, MW
  • Derivation and validation of the Denver human Immunodeficiency virus (HIV) risk score for targeted HIV screening
    Haukoos, JS; Lyons, MS; Lindsell, CJ; Hopkins, E; Bender, B; Rothman, RE; Byyny, RL
  • Development and validation of the San Diego early test score to predict acute and early HIV infection risk in men who have sex with men
    Hoenigl, M; Weibel, N; Mehta, SR; Anderson, CM; Jenks, J; Green, N; Little, SJ
  • Post-exposure prophylaxis: An underutilized biomedical HIV prevention method among gay, bisexual and other men who have sex with men in China
    Hou, J; Wu, Y; Xie, L; Meng, S; Fu, R; Zheng, H; Meyers, K
  • Study on the infectious risk model of AIDS among men who have sex with men in Guangzhou
    Hu, P; Zhong, F; Cheng, WB; Xu, HF; Ling, L
  • The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard Dersimonian-Laird method
    IntHout, J; Ioannidis, JP; Borm, GF
  • Assessing the performance of 3 human immunodeficiency virus incidence risk scores in a cohort of black and white men who have sex with men in the South
    Jones, J; Hoenigl, M; Siegler, AJ; Sullivan, PS; Little, S; Rosenberg, E
  • Development and validation of an automated HIV prediction algorithm to identify candidates for pre-exposure prophylaxis: A modelling study
    Krakower, DS; Gruber, S; Hsu, K; Menchaca, JT; Maro, JC; Kruskal, BA; Klompas, M
  • Preexposure prophylaxis guidelines have low sensitivity for identifying seroconverters in a sample of young Black MSM in Chicago
    Lancki, N; Almirol, E; Alon, L; McNulty, M; Schneider, JA
  • Development of HIV infection risk assessment tool for men who have sex with men based on Delphi method
    Li, LL; Jiang, Z; Song, WL; Ding, YY; Xu, J; He, N
  • The Amsterdam symptom and risk-based score predicts for acute hiv infection in men who have sex with men in san diego
    Lin, TC; Dijkstra, M; De Bree, GJ; Schim van der Loeff, MF; Hoenigl, M
  • A simple symptom score for acute human immunodeficiency virus infection in a San Diego community-based screening program
    Lin, TC; Gianella, S; Tenenbaum, T; Little, SJ; Hoenigl, M
  • External validation of a prediction tool to estimate the risk of human immunodeficiency virus infection amongst men who have sex with men
    Luo, Q; Huang, X; Li, L; Ding, Y; Mi, G; Scott, SR; Wu, Z
  • Use of electronic health record data and machine learning to identify candidates for HIV pre-exposure prophylaxis: A modelling study
    Marcus, JL; Hurley, LB; Krakower, DS; Alexeeff, S; Silverberg, MJ; Volk, JE
  • Prescription of postexposure prophylaxis for HIV-1 in the emergency room: Correct transmission risk assessment remains challenging
    Marzel, A; Heinrich, H; Schilliger, L; Fehr, JS; Günthard, HF; Kouyos, R; Rampini, SK
  • Prediction of HIV acquisition among men who have sex with men
    Menza, TW; Hughes, JP; Celum, CL; Golden, MR
  • Critical appraisal and data extraction for systematic reviews of prediction modelling studies: The CHARMS Checklist
    Moons, KG; de Groot, JA; Bouwmeester, W; Vergouwe, Y; Mallett, S; Altman, DG; Collins, GS
  • Development and validation of a sociodemographic and behavioral characteristics-based risk-score algorithm for targeting HIV testing among adults in Kenya
    Muttai, H; Guyah, B; Musingila, P; Achia, T; Miruka, F; Wanjohi, S; Zielinski-Gutierrez, E
  • European System for Cardiac Operative Risk Evaluation (EuroSCORE)
    Nashef, SA; Roques, F; Michel, P; Gauducheau, E; Lemeshow, S; Salamon, R
  • Risk-based screening tools to optimise HIV testing services: A systematic review
    Ong, JJ; Coulthard, K; Quinn, C; Tang, MJ; Huynh, T; Jamil, MS; Johnson, C
  • PrEP awareness, familiarity, comfort, and prescribing experience among US primary care providers and HIV specialists
    Petroll, AE; Walsh, JL; Owczarzak, JL; McAuliffe, TL; Bogart, LM; Kelly, JA
  • Vital signs: HIV infection, diagnosis, treatment, and prevention among gay, bisexual, and other men who have sex with men-United States, 2010–2019
    Pitasi, MA; Beer, L; Cha, S; Lyons, SJ; Hernandez, AL; Prejean, J; Hall, HI
  • Improved detection of acute HIV-1 infection in sub-Saharan Africa: Development of a risk score algorithm
    Powers, KA; Miller, WC; Pilcher, CD; Mapanje, C; Martinson, FE; Fiscus, SA; Cohen, MS
  • Analysis on prediction power of HIV infection risk assessment tool in men who have sex with men in Guizhou province
    Qian, XH; Zheng, M; Zheng, YQ; He, JY; Yao, YM; Tao, R; Yuan, Z
  • Development and validation of the Personalized Sexual Health Promotion (SexPro) HIV risk prediction model for men who have sex with men in the United States
    Scott, H; Vittinghoff, E; Irvin, R; Liu, A; Nelson, L; Del Rio, C; Buchbinder, S
  • PrEP awareness and attitudes in a national survey of primary care clinicians in the United States, 2009–2015
    Smith, DK; Mendoza, MC; Stryker, JE; Rose, CE
  • Development of a clinical screening index predictive of incident HIV infection among men who have sex with men in the United States
    Smith, DK; Pals, SL; Herbst, JH; Shinde, S; Carey, JW
  • A study to develop clinical decision rules for the use of radiography in acute ankle injuries
    Stiell, IG; Greenberg, GH; McKnight, RD; Nair, RC; McDowell, I; Worthington, JR
  • HIV epidemiology and responses among men who have sex with men and transgender individuals in China: A scoping review
    Tang, S; Tang, W; Meyers, K; Chan, P; Chen, Z; Tucker, JD
  • Derivation and validation of an HIV risk prediction score among gay, bisexual, and other men who have sex with men to inform PrEP initiation in an STD clinic setting
    Tordoff, DM; Barbee, LA; Khosropour, CM; Hughes, JP; Golden, MR
  • Primary care providers' perspectives on using automated HIV risk prediction models to identify potential candidates for pre-exposure prophylaxis
    van den Berg, P; Powell, VE; Wilson, IB; Klompas, M; Mayer, K; Krakower, DS
  • Evaluation of an empiric risk screening score to identify acute and early HIV-1 infection among MSM in coastal Kenya
    Wahome, E; Fegan, G; Okuku, HS; Mugo, P; Price, MA; Mwashigadi, G; Sanders, EJ
  • An empiric risk score to guide PrEP targeting among MSM in coastal Kenya
    Wahome, E; Thiong'o, AN; Mwashigadi, G; Chirro, O; Mohamed, K; Gichuru, E; Sanders, EJ
  • PROBAST: A tool to assess the risk of bias and applicability of prediction model studies
    Wolff, RF; Moons, KGM; Riley, RD; Whiting, PF; Westwood, M; Collins, GS; Mallett, S
  • Risk prediction score for HIV infection: Development and internal validation with cross-sectional data from men who have sex with men in China
    Yin, L; Zhao, Y; Peratikos, MB; Song, L; Zhang, X; Xin, R; Qian, HZ
  • 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, K; Xu, J; Leuba, S; Zhu, Y; Zhang, J; Chu, Z; Shang, H
  • Risk assessment and identification of HIV infection among men who have sex with men: A cross-sectional study in Southwest China
    Zheng, M; He, J; Yuan, Z; Zhang, X; Yao, Y; Fang, X; Zhang, Y