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

ABSTRACT:

Background

Traditional 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.

Methods

Data were derived from a National Cancer Institute-sponsored study examining the validity of a measurement system (PRO-CTCAE) for patient self-reportin

SUBMITTER: Atkinson TM 

PROVIDER: S-EPMC6279753 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature