与时间相关的泊松-伽马模型在实践中的应用:艾滋病试验中的招募预测

IF 2 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
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引用次数: 0

摘要

尽管多中心研究招募模型方面的文献越来越多,但在实践中,预测招募人数的统计模型却很少使用,即使使用,也往往依赖于不切实际的假设。与时间相关的泊松-伽马模型(tPG)是最近开发的一种灵活方法,分析人员可利用它预测正在进行的多中心试验的招募情况,其性能已在一项队列研究的数据中得到验证。在本文中,我们将在随机对照试验的招募数据上对 tPG 模型进行说明和进一步验证。此外,我们还在附录中提供了通过 tPG R 软件包实施该模型的实用易学指南。为了验证该模型,我们展示了所提出的方法在预测 HIV 疫苗试验网络在多个撒哈拉以南国家进行的两项 HIV 疫苗试验招募过程中的预测性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The time-dependent Poisson-gamma model in practice: Recruitment forecasting in HIV trials

Despite a growing body of literature in the area of recruitment modeling for multicenter studies, in practice, statistical models to predict enrollments are rarely used and when they are, they often rely on unrealistic assumptions. The time-dependent Poisson-Gamma model (tPG) is a recently developed flexible methodology which allows analysts to predict recruitments in an ongoing multicenter trial, and its performance has been validated on data from a cohort study. In this article, we illustrate and further validate the tPG model on recruitment data from randomized controlled trials. Additionally, in the appendix, we provide a practical and easy to follow guide to its implementation via the tPG R package. To validate the model, we show the predictive performance of the proposed methodology in forecasting the recruitment process of two HIV vaccine trials conducted by the HIV Vaccine Trials Network in multiple Sub-Saharan countries.

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来源期刊
CiteScore
3.70
自引率
4.50%
发文量
281
审稿时长
44 days
期刊介绍: Contemporary Clinical Trials is an international peer reviewed journal that publishes manuscripts pertaining to all aspects of clinical trials, including, but not limited to, design, conduct, analysis, regulation and ethics. Manuscripts submitted should appeal to a readership drawn from disciplines including medicine, biostatistics, epidemiology, computer science, management science, behavioural science, pharmaceutical science, and bioethics. Full-length papers and short communications not exceeding 1,500 words, as well as systemic reviews of clinical trials and methodologies will be published. Perspectives/commentaries on current issues and the impact of clinical trials on the practice of medicine and health policy are also welcome.
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