马拉维利隆圭性传播感染诊所检测急性 HIV 感染的最新风险评分算法。

IF 2.9 3区 医学 Q3 IMMUNOLOGY JAIDS Journal of Acquired Immune Deficiency Syndromes Pub Date : 2024-09-09 DOI:10.1097/qai.0000000000003519
Griffin J Bell,Jane S Chen,Courtney N Maierhofer,Mitch Matoga,Sarah E Rutstein,Kathryn E Lancaster,Maganizo B Chagomerana,Edward Jere,Pearson Mmodzi,Naomi Bonongwe,Esther Mathiya,Beatrice Ndalama,Mina C Hosseinipour,Michael Emch,Ann M Dennis,Myron S Cohen,Irving F Hoffman,William C Miller,Kimberly A Powers
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Risk score algorithms can improve the efficiency of AHI detection by identifying persons at highest risk of AHI for prioritized RNA/antigen testing, but prior algorithms have not considered geospatial information, potential differences by sex, or current antibody testing paradigms.\r\n\r\nMETHODS\r\nWe used elastic net models to develop sex-stratified risk score algorithms in a case-control study of persons (136 with AHI, 250 without HIV) attending a sexually transmitted infections (STI) clinic in Lilongwe, Malawi from 2015 to 2019. We designed algorithms for varying clinical contexts according to three levels of data availability: 1) routine demographic and clinical information, 2) behavioral and occupational data obtainable through patient interview, and 3) geospatial variables requiring external datasets or field data collection. 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引用次数: 0

摘要

背景急性(血清转换前)HIV 感染(AHI)是传播风险最高的阶段,其检测需要资源密集型的 RNA 或抗原检测方法,常规使用可能不可行。风险评分算法可以提高 AHI 检测的效率,识别出 AHI 风险最高的人群,优先进行 RNA/抗原检测,但之前的算法并未考虑地理空间信息、潜在的性别差异或当前的抗体检测范例。方法:2015 年至 2019 年期间,我们在马拉维利隆圭的性传播感染(STI)诊所就诊者(136 人感染 AHI,250 人未感染 HIV)的病例对照研究中使用弹性网模型开发了性别分层风险评分算法。我们根据三种数据可用性水平设计了适用于不同临床环境的算法:1)常规人口统计学和临床信息;2)可通过患者访谈获得的行为和职业数据;3)需要外部数据集或实地数据收集的地理空间变量。我们计算了灵敏度、特异性和接收者工作特征曲线下面积(AUC)来评估模型的性能,并开发了一个网络应用程序来支持模型的实施。结果对男性而言,性能最高的 AHI 风险评分算法(AUC=0.74)包含前两级数据可用性中的五个变量(安全套使用、身体疼痛、发烧、皮疹、生殖器疮/溃疡)。表现最好的女性算法(AUC=0.81)包含来自所有三个数据可用性级别的 15 个变量。0.26 的风险评分切点对男性的 AHI 检测灵敏度为 93%,特异性为 27%;0.15 的切点对女性的灵敏度为 97%,特异性为 44%。结论:风险评分算法有助于在性传播疾病诊所环境中有效检测 AHI,从而在传播风险升高的关键时期为艾滋病传播预防干预创造机会。
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Updated Risk Score Algorithms for Acute HIV Infection Detection at a Sexually Transmitted Infections Clinic in Lilongwe, Malawi.
BACKGROUND Detection of acute (pre-seroconversion) HIV infection (AHI), the phase of highest transmission risk, requires resource-intensive RNA- or antigen-based detection methods that can be infeasible for routine use. Risk score algorithms can improve the efficiency of AHI detection by identifying persons at highest risk of AHI for prioritized RNA/antigen testing, but prior algorithms have not considered geospatial information, potential differences by sex, or current antibody testing paradigms. METHODS We used elastic net models to develop sex-stratified risk score algorithms in a case-control study of persons (136 with AHI, 250 without HIV) attending a sexually transmitted infections (STI) clinic in Lilongwe, Malawi from 2015 to 2019. We designed algorithms for varying clinical contexts according to three levels of data availability: 1) routine demographic and clinical information, 2) behavioral and occupational data obtainable through patient interview, and 3) geospatial variables requiring external datasets or field data collection. We calculated sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) to assess model performance and developed a web application to support implementation. RESULTS The highest-performing AHI risk score algorithm for men (AUC=0.74) contained five variables (condom use, body aches, fever, rash, genital sores/ulcers) from the first two levels of data availability. The highest-performing algorithm for women (AUC=0.81) contained fifteen variables from all three levels of data availability. A risk score cut-point of 0.26 had an AHI detection sensitivity of 93% and specificity of 27% for males, and a cut-point of 0.15 had 97% sensitivity and 44% specificity for females. Additional models are available in the web application. CONCLUSION Risk score algorithms can facilitate efficient AHI detection in STI clinic settings, creating opportunities for HIV transmission prevention interventions during this critical period of elevated transmission risk.
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来源期刊
CiteScore
5.80
自引率
5.60%
发文量
490
审稿时长
3-6 weeks
期刊介绍: JAIDS: Journal of Acquired Immune Deficiency Syndromes​ seeks to end the HIV epidemic by presenting important new science across all disciplines that advance our understanding of the biology, treatment and prevention of HIV infection worldwide. JAIDS: Journal of Acquired Immune Deficiency Syndromes is the trusted, interdisciplinary resource for HIV- and AIDS-related information with a strong focus on basic and translational science, clinical science, and epidemiology and prevention. Co-edited by the foremost leaders in clinical virology, molecular biology, and epidemiology, JAIDS publishes vital information on the advances in diagnosis and treatment of HIV infections, as well as the latest research in the development of therapeutics and vaccine approaches. This ground-breaking journal brings together rigorously peer-reviewed articles, reviews of current research, results of clinical trials, and epidemiologic reports from around the world.
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