Concomitant Sjögren’s disease in patients with NMOSD: impacts on neurologic disease severity and recurrence - Wanqing Wu; Wenbo Yang; Bo Deng; Helian Li; Xiaoni Liu; Hai Yu; Xiang Zhang; Minrui Liang; Xiangjun Chen (Arthritis Research & Therapy)
Abstract Background We aimed to characterize the phenotype of neuromyelitis optica spectrum disorder (NMOSD) in the presence and absence of Sjogren's disease (SjD) and to develop a predictive nomogram to evaluate the risk of coexisting SjD within a single tertiary-center cohort of NMOSD patients. Methods Paraclinical and clinical features of patients with SjD were compared between NMOSD patients with SjD and those without SjD. Zstats v1.0 was utilized to randomly allocate participants into a derivation group (108 patients) and a validation group (47 patients) at a ratio of 7:3. Logistic regression analysis was used to assess the effectiveness of our predictive model, and a nomogram was created to illustrate the findings. Results A total of 155 NMOSD patients who were serologically positive for AQP4-IgG were cross-sectionally recruited (70 NMOSD patients with SjD [45.16%] and 85 NMOSD patients without SjD [54.84%]). Independent predictors of coexisting SjD were age upon recruitment (P = 0.002); Expanded Disability Status Scale (EDSS) score (P = 0.023); blood white blood cell (WBC) count (P = 0.049); and rheumatoid factor (RF) (P = 0.049), anti-SSA (Ro), and anti-SSB (La) antibody positivity (P < 0.001; P = 0.012). The nomogram had an area under the receiver operating characteristic (ROC) curve (AUC) (95% confidence interval [CI]) of 0.95 (0.89, 1.00) in the derivation cohort and 0.91 (0.79, 1.00) in the validation cohort. Survival curve analysis revealed that the EDSS score in the NMOSD patients with SjD was associated with clinical relapse, and these patients reached an EDSS score of 4.0 earlier than those without SjD. Conclusion NMOSD patients with SjD manifested more severe disease at attack and relapsed earlier than those without SjD. The nomogram established by combining age upon recruitment; EDSS score; blood WBC count; and RF, anti-SSA (Ro), and anti-SSB (La) antibody levels can significantly predict the risk of NMOSD combined with SjD.