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BMJ Publishing Group, Annals of the Rheumatic Diseases, Suppl 1(80), p. 1083.1-1083, 2021

DOI: 10.1136/annrheumdis-2021-eular.915

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Ab0109 Validation of Separate Patient-Reported, Clinical and Laboratory Factor Scores as Representation of Disease Burden in a Population With Established Rheumatoid Arthritis

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

Background:Rheumatoid arthritis (RA) can cause important bio-psychosocial burden. When exploring disease burden evolution in the 2-year Care in early RA (CareRA) trial, 3 factor scores were extracted via exploratory factor analysis (EFA).1 EFA uncovers the fact that multiple observed variables have similar patterns of responses because they are all associated with a latent, not directly observable, variable.Objectives:To validate in a population with established RA, the 3 factors scores and their individual components originally extracted in CareRA.Methods:Patients with established RA in sustained remission under treatment with etanercept (≥1 year) were enrolled in the TapERA (Tapering Etanercept in RA) trial between 2012 and 2014. Patients completed the Flare Assessment in RA (FLARE-RA) questionnaire.2Components of disease activity scores (swollen/tender joint count, physician and patient global health assessment, CRP and ESR), as well as pain (question 2) and fatigue evaluation (question 8), from the FLARE-RA questionnaire, and HAQ were recorded at every visit (v=5).Missingness on previously mentioned variables was handled with multiple imputation (100 imputations). Pain and fatigue were re-scaled from their original Likert scale of 1-6 to 0-100 to match CareRA data. Next, timepoint clustering was removed with multiple outputation (1000x) and each of the 100 000 datasets was analyzed by EFA with principal component extraction and oblimin rotation. The analyses were combined after re-ordering the factors by maximizing factor congruence.Results:Sixty-six patients with a mean disease duration of 14.8 years (SD 9.03), mean age of 55.21 years (SD12.87), 96% (63/66) positive to RF or ACPA, 77% (51/66) with erosions and 68% (45/66) female were included in this analysis.Table 1 provides the results of the EFAs from CareRA and TapERA. The factor structure and factor components remained the same in both datasets. The factor loadings, indicating how strongly a variable relates to its factor (correlation between observed and latent score), were also comparable. The HAQ, however; did have a stronger factor loading in TapERA (0.57 vs 0.92).Table 1.Results from the exploratory factor analyses in CareRA and TapERAVariableCareRATapERAPRFCFLFPRFCFLFFatigue0.900.80PaGH0.870.81Pain0.860.75HAQ0.570.92SJC280.920.82TJC280.890.84PhGH0.760.60CRP0.870.85ESR0.780.82Factor loadings presented (correlation between the observed score and the latent factor). Cross-loadings were negligible (<0.3) -not presented. The factor order is by % of variance explained.PRF: patient-reported factor, CF: clinical factor, LF: laboratory factor, PaGH: patient’s global health assessment, HAQ: health assessment questionnaire, SJC28: 28 swollen joint count, TJC28: 28 tender joint count, PhGH: physician’s global health assessment, CRP: C-reactive protein, ESR: erythrocyte sedimentation rateConclusion:The latent factor structure for disease burden originally found in CareRA was successfully validated in the TapERA dataset, underlining the robustness of the PRF, CF and LF scores. HAQ seems to take “greater importance” on established RA. However, deviations in factor loadings (e.g., HAQ) could be attributed to differences between study populations (e.g., early vs. established RA, sample size). Apart from traditional clinical and laboratory factors, patient-reported pain, fatigue, functionality and overall well-being determine disease burden, both in early and established RA. Using these factor scores could facilitate detection and management of patient’s unmet needs.References:[1]Pazmino, et al. Does Including Pain, Fatigue, and Physical Function When Assessing Patients with Early Rheumatoid Arthritis Provide a Comprehensive Picture of Disease Burden? J Rheumatology 2020 Nov.[2]Berthelot JM, et al. A tool to identify recent or present rheumatoid arthritis flare from both patient and physician perspectives: the ‘FLARE’ instrument. Annals Rheumatic Diseases. 2012.Disclosure of Interests:None declared