Application of a Bayesian graded response model to characterize areas of disagreement between clinician and patient grading of symptomatic adverse events Journal Article
| Authors: | Atkinson, T. M.; Reeve, B. B.; Dueck, A. C.; Bennett, A. V.; Mendoza, T. R.; Rogak, L. J.; Basch, E.; Li, Y. |
| Article Title: | 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-reporting of AEs in cancer patients receiving treatment (N = 940). AEs included 13 multiple attribute patient-reported symptoms that had corresponding unidimensional clinician AE grades. A Bayesian IRT Model was fitted to calculate the latent grading thresholds between raters. The posterior mean values of the model-fitted item responses were calculated to represent model-based AE grades obtained from patients and clinicians. Results: Model-based AE grades showed a general pattern of clinician underestimation relative to patient-graded AEs. However, the magnitude of clinician underestimation was associated with AE severity, such that clinicians’ underestimation was more pronounced for moderate/very severe model-estimated AEs, and less so with mild AEs. Conclusions: The Bayesian IRT approach reconciles multiple symptom attributes and elaborates on the patterns of clinician-patient non-concordance beyond that provided by traditional metrics. This IRT-based technique may be used as a supplemental tool to detect and characterize nuanced differences in patient-, clinician-, and proxy-based ratings of HRQOL and patient-centered outcomes. Trial registration: ClinicalTrials.gov NCT01031641. Registered 1 December 2009. © The Author(s). |
| Keywords: | neoplasms; patient-reported outcomes; item response theory; clinician-patient agreement |
| Journal Title: | Journal of Patient-Reported Outcomes |
| Volume: | 2 |
| ISSN: | 2509-8020 |
| Publisher: | SpringerOpen |
| Date Published: | 2018-01-01 |
| Start Page: | 56 |
| Language: | English |
| DOI: | 10.1186/s41687-018-0086-x |
| PROVIDER: | scopus |
| PMCID: | PMC6279753 |
| PUBMED: | 30515599 |
| DOI/URL: | |
| Notes: | Article -- Export Date: 1 May 2020 -- Source: Scopus |
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