OP0077 DETERMINANTS OF THE PHYSICIAN’S GLOBAL ASSESSMENT AND INFLUENCE OF CONTEXTUAL FACTORS IN EARLY AXIAL SPONDYLOARTHRITIS
Authors: F. Hirano, R. B. M. Landewé, F. A. Van Gaalen, D. Van der Heijde, C. Gaujoux-Viala, S. Ramiro
Journal: Annals of the Rheumatic Diseases (2020)

Background: In RMDs, the physician’s global assessment (PhGA) is a major factor of treatment decision. It is not well-known which disease manifestations contribute to PhGA in early axSpA and if contextual factors have an impact. Objectives: To investigate determinants of PhGA and the influence of contextual factors on this relationship in patients with early axSpA. Methods: Five-year data from DESIR, a cohort of early axSpA, were analysed. Clinical data were collected every 6 months up to 2 years and annually thereafter. The primary analysis included all patients, and the subgroup analysis patients with follow-up MRI at 2 and/or 5 years. PhGA over 5 years was the outcome of interest. Univariable generalized estimating equation (GEE) models were used to investigate relationships between potential determinants and PhGA. Longitudinal relationships were investigated in autoregressive models. Effect modification by contextual factors (educational level, gender and age) was tested and, if significant, models were stratified. Univariable analyses were chosen to better assess the contributory explanatory effects of each of the determinants in each of the strata. Results: A total of 708 patients were included, mean age 33.7 (SD 8.6) years, 46% male, 41% lower educated. The subgroup consisted of 220 patients with similar characteristics. Higher BASDAI questions 1-6, SJC28, TJC53, Maastricht Ankylosing Spondylitis Enthesitis Score (MASES), CRP and BASMI were associated with a higher PhGA (Table 1). Gender and age were effect modifiers of SJC28; the effect was largest in the younger male stratum (β [95% CI]; 1.07 [0.71, 1.43]), and smallest in the older female stratum (0.13 [0.04, 0.22]) (Figure 1). Autoregressive GEE models revealed the same determinants of PhGA and the same pattern of effect modification by gender and age. Table 1. Factors associated with PhGA over time in gender/age-stratified groups in univariable analysis Female/Older (n=200) Female/Younger (n=181) Male/Older (n=154) Male/Younger (n=173) Coefficient (95% CI) BASDAI Q1 (fatigue, 0-10) 0.39 (0.34, 0.44) 0.39 (0.34, 0.44) 0.41 (0.35, 0.46) 0.46 (0.41, 0.51) BASDAI Q2 (back pain, 0-10) 0.49 (0.45, 0.54) 0.53 (0.49, 0.57) 0.48 (0.43, 0.53) 0.58 (0.54, 0.63) BASDAI Q3 (peripheral joint pain, 0-10) 0.31 (0.27, 0.36) 0.36 (0.31, 0.41) 0.32 (0.27, 0.37) 0.43 (0.37, 0.48) BASDAI Q4 (enthesitis, 0-10) 0.37 (0.33, 0.41) 0.42 (0.37, 0.46) 0.36 (0.31, 0.41) 0.52 (0.47, 0.56) BASDAI Q5 (severity of morning stiffness, 0-10) 0.42 (0.37, 0.46) 0.45 (0.40, 0.49) 0.44 (0.40, 0.49) 0.58 (0.54, 0.63) BASDAI Q6 (duration of morning stiffness, 0-10) 0.30 (0.25, 0.35) 0.35 (0.30, 0.39) 0.36 (0.31, 0.41) 0.50 (0.45, 0.56) BASMI linear (0-10) 0.61 (0.45, 0.78) 0.67 (0.48, 0.86) 0.49 (0.30, 0.68) 0.95 (0.75, 1.15) SJC28 (0-28) 0.13 (0.04, 0.22 ) 0.52 (0.31, 0.73 ) 0.58 (0.40, 0.76 ) 1.07 (0.71, 1.43 ) TJC53 (0-159) ¶ 0.05 (0.04, 0.06) 0.13 (0.11, 0.16) 0.13 (0.11, 0.16) 0.15 (0.13, 0.18) MASES (0-39) 0.10 (0.08, 0.12) 0.15 (0.12, 0.17) 0.18 (0.14, 0.23) 0.30 (0.25, 0.35) CRP (mg/L) 0.02 (0.01, 0.04) 0.03 (0.01, 0.05) 0.06 (0.04, 0.07) 0.04 (0.03, 0.05) Any EAM (presence vs absence) -0.13 (-0.49, 0.23) -0.20 (-0.58, 0.19) -0.26 (-0.68, 0.17) -0.28 (-0.69, 0.14) SPARCC-spine (0-414) § 0.06 (-0.11, 0.22) 0.05 (-0.11, 0.20) 0.02 (-0.03, 0.06) 0.05 (-0.04, 0.14) SPARCC-SIJ (0-72) § -0.02 (-0.13, 0.09) 0.01 (-0.08, 0.10) 0.05 (-0.01, 0.11) 0.01 (-0.04, 0.06) ¶ Each joint graded 0-3 § Coefficients were estimated in the subgroup Conclusion: Patient’s subjective symptoms, peripheral arthritis, enthesitis, higher CRP and impaired spinal mobility contribute to explain PhGA in patients with early axSpA irrespective of gender and age. But physicians consider the presence of swollen joints as more important in males than in females. Disclosure of Interests: Fumio Hirano Paid instructor for: Ono pharmaceuticals, Astellas Pharma Inc, Sumitomo Dainippon Pharma, Chugai Pharmaceutical Co., Ltd., Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly &amp; Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Floris A. van Gaalen: None declared, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Cecile Gaujoux-Viala: None declared, Sofia Ramiro Grant/research support from: MSD, Consultant of: Abbvie, Lilly, Novartis, Sanofi Genzyme, Speakers bureau: Lilly, MSD, Novartis