Sofia Pazmino1, Anikó Lovik2, Annelies Boonen3, Diederik De Cock4, Veerle Stouten4, Johan Joly5, Delphine Bertrand4, Kristien Van der Elst5, Rene Westhovens6, Patrick Verschueren6. 1. S. Pazmino, MD, D. De Cock, PhD, V. Stouten, MSc, D. Bertrand, MSc, Department of Development and Regeneration, Skeletal Biology and Engineering Research Centre, KU Leuven, Leuven, Belgium; sofia.pazmino@kuleuven.be. 2. A. Lovik, PhD, I-BioStat Leuven Biostatistics and Statistical Bioinformatics Centre, KU Leuven, Leuven, Belgium. 3. A. Boonen, MD, PhD, Department of Internal Medicine, Division of Rheumatology, Maastricht University Medical Centre, and Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, the Netherlands. 4. S. Pazmino, MD, D. De Cock, PhD, V. Stouten, MSc, D. Bertrand, MSc, Department of Development and Regeneration, Skeletal Biology and Engineering Research Centre, KU Leuven, Leuven, Belgium. 5. J. Joly, MSc, K. Van der Elst, PhD, Department of Rheumatology, University Hospitals Leuven, Leuven, Belgium. 6. R. Westhovens, MD, PhD, P. Verschueren, MD, PhD, Department of Development and Regeneration, Skeletal Biology and Engineering Research Centre, KU Leuven, and Department of Rheumatology, University Hospitals Leuven, Leuven, Belgium.
Abstract
OBJECTIVE: To explore the possibility of integrating patient-important outcomes like pain, fatigue, and physical function into the evaluation of disease status in early rheumatoid arthritis (ERA) without compromising correct disease activity measurement. METHODS: Patients from the 2-year Care in Early Rheumatoid Arthritis (CareRA) trial were included. Pain and fatigue (visual analog scales), Health Assessment Questionnaire (HAQ), standard components of disease activity [swollen/tender joint counts (SJC/TJC), C-reactive protein (CRP) or erythrocyte sedimentation rate (ESR), physician (PhGH) and patient (PaGH) global health] were recorded at every visit (n = 10). Pearson correlation and exploratory factor analyses (EFA), using multiple imputation (15×) and outputation (1000×), were performed per timepoint and overall, on standard components of disease activity scores with and without pain, fatigue, and HAQ. Each of the 15,000 datasets was analyzed using EFA with principal component extraction and oblimin rotation to determine which variables belong together. RESULTS: We included 379 patients. EFA on standard composite score components extracted 2 factors with no substantial cross-loadings. Still, pain (0.83), fatigue (0.65), and HAQ (0.59) were strongly correlated with PaGH. When rerunning the EFA with the inclusion of pain, fatigue, and HAQ, the 2-factor model had substantial cross-loadings between factors. However, a 3-factor model was optimal, with Factor 1: patient assessment, Factor 2: clinical assessment (PhGH, SJC, and TJC), and Factor 3: laboratory assessment (ESR/CRP). CONCLUSION: PaGH, pain, fatigue, and physical function represent a separate aspect of the disease burden of patients with ERA, which could be further explored as a target for care apart from disease activity. [ClinicalTrials.gov: NCT01172639].
OBJECTIVE: To explore the possibility of integrating patient-important outcomes like pain, fatigue, and physical function into the evaluation of disease status in early rheumatoid arthritis (ERA) without compromising correct disease activity measurement. METHODS:Patients from the 2-year Care in Early Rheumatoid Arthritis (CareRA) trial were included. Pain and fatigue (visual analog scales), Health Assessment Questionnaire (HAQ), standard components of disease activity [swollen/tender joint counts (SJC/TJC), C-reactive protein (CRP) or erythrocyte sedimentation rate (ESR), physician (PhGH) and patient (PaGH) global health] were recorded at every visit (n = 10). Pearson correlation and exploratory factor analyses (EFA), using multiple imputation (15×) and outputation (1000×), were performed per timepoint and overall, on standard components of disease activity scores with and without pain, fatigue, and HAQ. Each of the 15,000 datasets was analyzed using EFA with principal component extraction and oblimin rotation to determine which variables belong together. RESULTS: We included 379 patients. EFA on standard composite score components extracted 2 factors with no substantial cross-loadings. Still, pain (0.83), fatigue (0.65), and HAQ (0.59) were strongly correlated with PaGH. When rerunning the EFA with the inclusion of pain, fatigue, and HAQ, the 2-factor model had substantial cross-loadings between factors. However, a 3-factor model was optimal, with Factor 1: patient assessment, Factor 2: clinical assessment (PhGH, SJC, and TJC), and Factor 3: laboratory assessment (ESR/CRP). CONCLUSION: PaGH, pain, fatigue, and physical function represent a separate aspect of the disease burden of patients with ERA, which could be further explored as a target for care apart from disease activity. [ClinicalTrials.gov: NCT01172639].
Authors: Peter C Taylor; Rieke Alten; Jose María Álvaro Gracia; Yuko Kaneko; Chad Walls; Amanda Quebe; Bochao Jia; Natalia Bello; Jorge Ross Terres; Roy Fleischmann Journal: RMD Open Date: 2022-03