Estimation of delay to diagnosis and incidence in HIV using indirect evidence of infection dates.
Estimation of delay to diagnosis and incidence in HIV using indirect evidence of infection dates.
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DOI：
10.1186/s12874-018-0522-x
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发表时间：
2018-06-27
影响因子：
4
通讯作者：
Dunn DT
中科院分区：
文献类型：
--
作者：
Stirrup OT;Dunn DT
最大限度地减少诊断延误对于实现艾滋病毒患者的最佳结果和限制进一步感染的可能性至关重要。然而，在大多数新诊断的患者中，无法确定确切的感染时间，因此必须从生物标志物数据中得出推断，这一事实阻碍了对诊断延迟的调查。我们开发了一个贝叶斯统计模型来评估感染日期未知的HIV患者的延迟诊断分布，该模型基于病毒序列遗传多样性和纵向病毒载量以及CD4计数数据。诊断延迟被视为每个患者的随机变量，并且他们的生物标记物数据相对于感染以来经过的真实时间被建模，这种相关性被用来获得诊断延迟的后验分布。来自已知感染日期在± 6个月内的全国血清转换者队列的数据，链接到病毒序列数据库，用于校准模型参数。实现了一个指数生存模型，该模型允许关于诊断延迟和跨患者组的信息汇集的一般推断。如果仅在给定的窗口期内观察到诊断，则还有必要将发病率建模为时间的函数；我们建议在处理来自已建立的流行病的数据时对该问题采取务实的方法。开发的模型用于调查2009-2013年期间在伦敦与感染日期未知的被诊断为艾滋病毒的男性发生性行为的男性中延迟诊断的分布。交叉验证和模拟分析表明，所开发的模型提供了关于感染时间的更准确的信息，而不是基于CD4计数的估计。在伦敦队列中估计了延迟诊断的分布，并根据种族观察到显著的差异。所有可用的生物标志物数据与诊断延迟分布的综合估计相结合，可以更准确地预测单个患者感染的真实时间，所开发的模型也提供了有用的人群水平信息。本文的在线版本(10.1186/s12874-0180522-x)包含向授权用户提供的补充材料。
Minimisation of the delay to diagnosis is critical to achieving optimal outcomes for HIV patients and to limiting the potential for further onward infections. However, investigation of diagnosis delay is hampered by the fact that in most newly diagnosed patients the exact timing of infection cannot be determined and so inferences must be drawn from biomarker data. We develop a Bayesian statistical model to evaluate delay-to-diagnosis distributions in HIV patients without known infection date, based on viral sequence genetic diversity and longitudinal viral load and CD4 count data. The delay to diagnosis is treated as a random variable for each patient and their biomarker data are modelled relative to the true time elapsed since infection, with this dependence used to obtain a posterior distribution for the delay to diagnosis. Data from a national seroconverter cohort with infection date known to within ± 6 months, linked to a database of viral sequences, are used to calibrate the model parameters. An exponential survival model is implemented that allows general inferences regarding diagnosis delay and pooling of information across groups of patients. If diagnoses are only observed within a given window period, then it is necessary to also model incidence as a function of time; we suggest a pragmatic approach to this problem when dealing with data from an established epidemic. The model developed is used to investigate delay-to-diagnosis distributions in men who have sex with men diagnosed with HIV in London in the period 2009–2013 with unknown date of infection. Cross-validation and simulation analyses indicate that the models developed provide more accurate information regarding the timing of infection than does CD4 count-based estimation. Delay-to-diagnosis distributions were estimated in the London cohort, and substantial differences were observed according to ethnicity. The combination of all available biomarker data with pooled estimation of the distribution of diagnosis-delays allows for more precise prediction of the true timing of infection in individual patients, and the models developed also provide useful population-level information. The online version of this article (10.1186/s12874-018-0522-x) contains supplementary material, which is available to authorized users.
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DOI：
10.1093/cid/ciq164
发表时间：
2011-02-15
期刊：
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
影响因子：
--
作者：
Kouyos RD;von Wyl V;Yerly S;Böni J;Rieder P;Joos B;Taffé P;Shah C;Bürgisser P;Klimkait T;Weber R;Hirschel B;Cavassini M;Rauch A;Battegay M;Vernazza PL;Bernasconi E;Ledergerber B;Bonhoeffer S;Günthard HF;Swiss HIV Cohort Study
通讯作者：
Swiss HIV Cohort Study
影响因子：
3.2
作者：
Andersson, Emmi;Shao, Wei;Jordan, Michael R.
通讯作者：
Jordan, Michael R.
影响因子：
105.7
作者：
Cane, P;Chrystie, I;Zuckerman, M
通讯作者：
Zuckerman, M
影响因子：
9.4
作者：
Meixenberger, Karolin;Hauser, Andrea;Kuecherer, Claudia
通讯作者：
Kuecherer, Claudia
DOI：
10.1111/j.1467-9876.2005.00491.x
发表时间：
2005-01-01
影响因子：
1.6
作者：
Pantazis, N;Touloumi, G
通讯作者：
Touloumi, G