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Abstract Number: 1294

Patient Reported Outcome Measures for Rheumatoid Arthritis Disease Activity: Using Rasch Measurement Theory and Cognitive Interviewing to Achieve More Meaningful Measurement

Tim Pickles1, Mike Horton2, Karl Bang Christensen3, Rhiannon Phillips4, David Gillespie1, Neil Mo5 and Ernest Choy6, 1Cardiff University, Cardiff, United Kingdom, 2University of Leeds, Leeds, United Kingdom, 3University of Copenhagen, Copenhagen, Denmark, 4Cardiff Metropolitan University, Cardiff, United Kingdom, 5Swansea Bay University Health Board, Port Talbot, United Kingdom, 6Section of Rheumatology, Cardiff University, Cardiff, United Kingdom

Meeting: ACR Convergence 2023

Keywords: Disease Activity, Patient reported outcomes, Psychometrics, Qualitative Research, rheumatoid arthritis

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Session Information

Date: Monday, November 13, 2023

Title: (1264–1307) RA – Diagnosis, Manifestations, and Outcomes Poster II

Session Type: Poster Session B

Session Time: 9:00AM-11:00AM

Background/Purpose: Disease Activity (DA) monitoring is a standard of care in Rheumatoid Arthritis (RA). A systematic review of Patient Reported Outcome Measures (PROMs) for RA DA demonstrated a lack of sufficient evidence for content validity. The aim of this study was to use Rasch measurement theory (RMT) to develop a valid item pool for measurement of RA DA, and then explore patients’ views on the relevance, comprehensiveness and comprehensibility of these items.

Methods: Questionnaires were sent to people aged 18 or over with RA in 2020/21, which included items from identified PROMs from a systematic review – RADAI5, RADAI, RADAI-SF, PDAS2, GAS, PAS, PAS-II, RAPID3, RAPID4, PRO-CLARA, PROM-score, RADAR, RADAI-F5, FLARE-RA and RA-FQ – and others suggested by patient feedback. Items were grouped into core domains established by OMERACT and included in exploratory factor analyses (EFA). By domain, psychometric properties were assessed by RMT analyses, which provided results on targeting, model fit, internal consistency, local dependency, unidimensionality and item threshold ordering. Sampling used a maximal variation approach across various demographics from the questionnaire-returning participants. Individual cognitive interviews took place in 2022/23. The think aloud technique was used as participants answered items, who were then asked about relevance, comprehensiveness and comprehensibility.

Results: A test dataset of n=398 and a validation dataset of n=293 were available. EFA of the test dataset showed that 30 items across the tenderness and swelling, patient global, pain, fatigue, physical functioning and stiffness domains loaded together. RMT analyses in the test dataset indicated that the patient global domain comprised two domains: general health and disease activity. In assessing the now seven domains, 12 items were discarded. Subtest analyses in the validation dataset indicated that patient global general health and fatigue could not be used to measure RA DA but the remaining five domains, containing 12 items, could. 20 participants were interviewed using a questionnaire containing the 12 identified RA DA items, six additional RA DA items, and six general health and fatigue items, which were presented to elicit views on their potential for inclusion. No consistent concerns were identified with the 12 RA DA items with regards relevance, comprehensiveness and comprehensibility. Some participants would prefer longer timeframes ( > one week) for symptom reporting to fully capture their DA, a ‘don’t know’ option, and asking about symptoms at different times of day due to diurnal patterns in symptoms. One participant noted that ‘disease activity’ was a confusing term.

Conclusion: Patient global items relating to general health and disease activity were two separate domains. RA DA can be measured using tenderness and swelling, patient global disease activity, pain, physical functioning and stiffness items, but not with fatigue and patient global general health items. These results provide initial evidence of content validity of the item pool in terms of relevance, comprehensiveness and comprehensibility. The next step is to develop a computer adaptive test based on anchored locations calculated using these data.


Disclosures: T. Pickles: None; M. Horton: None; K. Bang Christensen: None; R. Phillips: None; D. Gillespie: None; N. Mo: AbbVie/Abbott, 5, Eli Lilly, 5, Novartis, 1, Pfizer, 6, Roche, 6, UCB, 5; E. Choy: AbbVie, 2, 6, Amgen, 2, 6, Bio-Cancer, 5, Biogen, 2, 5, Chugai Pharma, 2, 6, Eli Lilly, 2, 6, Fresenius Kabi, 2, 6, Galapagos, 2, 6, Gilead, 2, 6, Janssen, 2, Novartis, 5, Pfizer, 5, 6, R-Pharm, 2, Sanofi, 2, 5, 6, Sanofi-Genzyme, 2, UCB, 2.

To cite this abstract in AMA style:

Pickles T, Horton M, Bang Christensen K, Phillips R, Gillespie D, Mo N, Choy E. Patient Reported Outcome Measures for Rheumatoid Arthritis Disease Activity: Using Rasch Measurement Theory and Cognitive Interviewing to Achieve More Meaningful Measurement [abstract]. Arthritis Rheumatol. 2023; 75 (suppl 9). https://acrabstracts.org/abstract/patient-reported-outcome-measures-for-rheumatoid-arthritis-disease-activity-using-rasch-measurement-theory-and-cognitive-interviewing-to-achieve-more-meaningful-measurement/. Accessed .
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