The PROPr can be measured using different PROMIS domain item sets.

HRQoL IRT PROMIS PROPr Pain Patient Reported Outcomes

Journal

Cancer epidemiology
ISSN: 1877-783X
Titre abrégé: Cancer Epidemiol
Pays: Netherlands
ID NLM: 101508793

Informations de publication

Date de publication:
10 Sep 2024
Historique:
received: 16 04 2024
revised: 05 08 2024
accepted: 27 08 2024
medline: 12 9 2024
pubmed: 12 9 2024
entrez: 11 9 2024
Statut: aheadofprint

Résumé

The Patient-Reported Outcomes Measurement Information System (PROMIS) Preference Score (PROPr) is estimated from descriptive health assessments within the PROMIS framework. The underlying item response theory (IRT) allows researchers to measure PROMIS health domains with any subset of items that are calibrated to this domain. Consequently, this should also be true for the PROPr. We aimed to test this assumption using both an empirical and a simulation approach. Empirically, we estimated 3 PROMIS Pain inference (PI) scores from 3 different item subsets in a sample of n=199 cancer patients: 4 PROMIS-29 items (estimate: θ θ Different item subsets can be used to estimate the PROMIS PI for calculation of the PROPr. Reduction to 2 items per domain rather than 4 does not significantly change the PROPr estimate on average. Agreements differ across the spectrum and in individual comparisons.

Sections du résumé

BACKGROUND BACKGROUND
The Patient-Reported Outcomes Measurement Information System (PROMIS) Preference Score (PROPr) is estimated from descriptive health assessments within the PROMIS framework. The underlying item response theory (IRT) allows researchers to measure PROMIS health domains with any subset of items that are calibrated to this domain. Consequently, this should also be true for the PROPr. We aimed to test this assumption using both an empirical and a simulation approach.
METHODS METHODS
Empirically, we estimated 3 PROMIS Pain inference (PI) scores from 3 different item subsets in a sample of n=199 cancer patients: 4 PROMIS-29 items (estimate: θ
RESULTS RESULTS
θ
CONCLUSION CONCLUSIONS
Different item subsets can be used to estimate the PROMIS PI for calculation of the PROPr. Reduction to 2 items per domain rather than 4 does not significantly change the PROPr estimate on average. Agreements differ across the spectrum and in individual comparisons.

Identifiants

pubmed: 39260316
pii: S1877-7821(24)00137-1
doi: 10.1016/j.canep.2024.102658
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

102658

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Christoph Paul Klapproth (CP)

Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Germany; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digital Clinician Scientist Program, Charitéplatz 1, Berlin 10117, Germany. Electronic address: christoph-paul.klapproth@charite.de.

Felix Fischer (F)

Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Germany.

Annika Doehmen (A)

Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Germany.

Milan Kock (M)

Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Germany.

Jens Rohde (J)

Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Germany.

Kathrin Rieger (K)

Department of Hematology, Oncology and Cancer Immunology, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Ullrich Keilholz (U)

Charité Comprehensive Cancer Center (CCCC), Department of Oncology, Charité - Universitätsmedizin Berlin, Germany.

Matthias Rose (M)

Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Germany.

Alexander Obbarius (A)

Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Germany; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digital Clinician Scientist Program, Charitéplatz 1, Berlin 10117, Germany; Dornsife Center for Self-report Science, University of Southern California, Los Angeles, CA, USA.

Classifications MeSH