PMID- 30515599
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20201001
IS  - 2509-8020 (Electronic)
IS  - 2509-8020 (Linking)
VI  - 2
IP  - 1
DP  - 2018 Dec 4
TI  - Application of a Bayesian graded response model to characterize areas of 
      disagreement between clinician and patient grading of symptomatic adverse events.
PG  - 56
LID - 10.1186/s41687-018-0086-x [doi]
LID - 56
AB  - 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.
FAU - Atkinson, Thomas M
AU  - Atkinson TM
AUID- ORCID: 0000-0002-4965-3913
AD  - Department of Psychiatry & Behavioral Sciences, Memorial Sloan Kettering Cancer 
      Center, 641 Lexington Ave., 7th Floor, New York, NY, 10022, USA. 
      atkinsot@mskcc.org.
FAU - Reeve, Bryce B
AU  - Reeve BB
AD  - Duke University Medical Center, Durham, NC, USA.
FAU - Dueck, Amylou C
AU  - Dueck AC
AD  - Mayo Clinic, Scottsdale, AZ, USA.
FAU - Bennett, Antonia V
AU  - Bennett AV
AD  - University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
FAU - Mendoza, Tito R
AU  - Mendoza TR
AD  - University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.
FAU - Rogak, Lauren J
AU  - Rogak LJ
AD  - Department of Psychiatry & Behavioral Sciences, Memorial Sloan Kettering Cancer 
      Center, 641 Lexington Ave., 7th Floor, New York, NY, 10022, USA.
FAU - Basch, Ethan
AU  - Basch E
AD  - Department of Psychiatry & Behavioral Sciences, Memorial Sloan Kettering Cancer 
      Center, 641 Lexington Ave., 7th Floor, New York, NY, 10022, USA.
AD  - University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
FAU - Li, Yuelin
AU  - Li Y
AD  - Department of Psychiatry & Behavioral Sciences, Memorial Sloan Kettering Cancer 
      Center, 641 Lexington Ave., 7th Floor, New York, NY, 10022, USA.
LA  - eng
SI  - ClinicalTrials.gov/NCT01031641
GR  - P30 CA8748-50/National Institutes of Health/
GR  - P30 CA008748/CA/NCI NIH HHS/United States
GR  - HHSN261200800043C/CA/NCI NIH HHS/United States
GR  - HHSN261201000063C/CA/NCI NIH HHS/United States
GR  - HHSN261200800001E/National Cancer Institute/
GR  - HHSN261201000063C/National Cancer Institute/
GR  - HHSN261200800001C/RC/CCR NIH HHS/United States
GR  - HHSN261200800043C/National Cancer Institute/
GR  - HHSN261200800001E/CA/NCI NIH HHS/United States
PT  - Journal Article
DEP - 20181204
PL  - Germany
TA  - J Patient Rep Outcomes
JT  - Journal of patient-reported outcomes
JID - 101722688
PMC - PMC6279753
OTO - NOTNLM
OT  - Clinician-patient agreement
OT  - Item response theory
OT  - Neoplasms
OT  - Patient-reported outcomes
COIS- ETHICS APPROVAL AND CONSENT TO PARTICIPATE: The study was approved by the 
      institutional review boards at the National Cancer Institute and all 
      participating sites. All study participants provided written informed consent. 
      CONSENT FOR PUBLICATION: Not applicable. COMPETING INTERESTS: The authors declare 
      that they have no competing interests. PUBLISHER'S NOTE: Springer Nature remains 
      neutral with regard to jurisdictional claims in published maps and institutional 
      affiliations.
EDAT- 2018/12/06 06:00
MHDA- 2018/12/06 06:01
PMCR- 2018/12/04
CRDT- 2018/12/06 06:00
PHST- 2018/03/23 00:00 [received]
PHST- 2018/11/18 00:00 [accepted]
PHST- 2018/12/06 06:00 [entrez]
PHST- 2018/12/06 06:00 [pubmed]
PHST- 2018/12/06 06:01 [medline]
PHST- 2018/12/04 00:00 [pmc-release]
AID - 10.1186/s41687-018-0086-x [pii]
AID - 86 [pii]
AID - 10.1186/s41687-018-0086-x [doi]
PST - epublish
SO  - J Patient Rep Outcomes. 2018 Dec 4;2(1):56. doi: 10.1186/s41687-018-0086-x.