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Application of a Bayesian graded response model to characterize areas of disagreement between clinician and patient grading of symptomatic adverse events

机译:贝叶斯分级反应模型在表征临床和患者对症状不良事件分级之间的分歧区域中的应用

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摘要

BackgroundTraditional concordance metrics have shortcomings based on dataset characteristics (e.g., multiple attributes rated, missing data); therefore it is necessary to explore supplemental approaches to quantifying agreement between independent assessments. The purpose of this methodological paper is to apply an Item Response Theory (IRT) -based framework to an existing dataset that included unidimensional clinician and multiple attribute patient ratings of symptomatic adverse events (AEs), and explore the utility of this method in patient-reported outcome (PRO) and health-related quality of life (HRQOL) research.
机译:背景传统的一致性指标存在基于数据集特征的缺点(例如,多个属性已评级,数据丢失);因此,有必要探索补充方法来量化独立评估之间的一致性。该方法论论文的目的是将基于项目响应理论(IRT)的框架应用于现有数据集,该数据集包括一维临床医生和症状不良事件(AE)的多属性患者评级,并探讨该方法在患者中的实用性-报告了结局(PRO)和与健康相关的生活质量(HRQOL)研究。

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