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Information on Center Characteristics as Costs' Determinants in Multicenter Clinical Trials: Is Modeling Center Effect Worth the Effort?

机译:在多中心临床试验中作为费用决定因素的中心特征信息:中心效应建模值得吗?

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摘要

OBJECTIVES: \ud\udSeveral methodological problems arise when health outcomes and resource utilization are collected at different sites. To avoid misleading conclusions in multi-center economic evaluations the center effect needs to be taken into adequate consideration. The aim of this article is to compare several models, which make use of a different amount of information about the enrolling center.\ud\udMETHODS: \ud\udTo model the association of total medical costs with the levels of two sets of covariates, one at patient and one at center level, we considered four statistical models, based on the Gamma model in the class of the Generalized Linear Models with a log link, which use different amount of information on the enrolling centers. Models were applied to Cost of Strategies after Myocardial Infarction data, an international randomized trial on costs of uncomplicated acute myocardial infarction (AMI).\ud\udRESULTS: \ud\udThe simple center effect adjustment based on a single random effect results in a more conservative estimation of the parameters as compared with approaches which make use of deeper information on the centers characteristics.\ud\udCONCLUSIONS: \ud\udThis study shows, with reference to a real multicenter trial, that center information cannot be neglected and should be collected and inserted in the analysis, better in combination with one or more random effect, taking into account in this way also the heterogeneity among centers because of unobserved centers characteristics.
机译:目的:\ ud \ ud当在不同地点收集健康结果和资源利用时,会出现一些方法学问题。为了避免在多中心经济评估中产生误导性结论,需要充分考虑中心效应。本文的目的是比较几种模型,这些模型利用了有关注册中心的不同数量的信息。\ ud \ ud方法:\ ud \ ud要对总医疗费用与两组协变量水平的关联进行建模,一个在患者身上,一个在中心水平上,我们考虑了基于带有日志链接的广义线性模型类别中的Gamma模型的四个统计模型,它们在注册中心使用了不同数量的信息。将模型应用于发生心肌梗塞数据后的策略成本,这是一项国际单纯性急性心肌梗塞(AMI)成本的随机试验。\ ud \ ud结果:\ ud \ ud基于单个随机效应的简单中心效应调整会产生更多结果。与使用更深入的中心特征信息的方法相比,参数的保守估计。\ ud \ ud结论:\ ud \ ud这项研究表明,参照实际的多中心试验,中心信息不能忽略,应该收集并插入分析中,最好与一个或多个随机效应结合,同时考虑到中心之间的异质性(由于未观察到的中心特征)。

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