RESUMEN
BACKGROUND: Systemic lupus erythematosus (SLE) is a chronic inflammatory multisystemic disease. Monitoring disease activity thoughtout the disease course is important for effective management and assessment of disease outcome. OBJECTIVE: To assess whether the pan-immune inflammation value (PIIV) at diagnosis could predict organ involvement and disease activity in childhood SLE (cSLE) patients after 12 months of disease onst. METHODS: This is an observational retrospective multicenter study that comprised cSLE patients seen and followed at the participating centers between January 2010 and December 2022. All patients met the EULAR/ACR-19 criteria, were immunosuppressive drug-naïve at the time of SLE diagnosis and had a minimal follow-up period of 12 months. The data included clinical and laboratory findings and disease activity using the SLEDAI-2K. Receiver operating characteristic (ROC) curves were employed to determine the optimal cut-off value of PIIV and assess its predictive potential for disease activity, and organ involvement. RESULTS: A total of 125 patients (104 female) with a median age of 16.0 (IQR 5.6) years, a median age at disease onset of 10.9 (IQR 3.0) years, and a median disease duration of 4.8 (IQR 5.3) years were included. The most frequent involved organs at diagnosis were hematological (89.6%), musculoskeletal (68.8%), mucocutaneous (63.2%), and renal (58.4%). However, at a 12-month follow-up visit, the most frequent involved organs were renal (40.0%), hematological (39.2%), musculoskeletal (15.2%), and mucocutaneous (10.4%). The median PIIV at diagnosis was 139 (IQR 229.6), while the median SLEDAI was 12 (IQR 6.5) and 3.5 (IQR 7.0) at diagnosis and 12 months, respectively. An optimal PIIV cut-off of 250 was found to be a predicative for disease activity, with a sensitivity of 45% and a specificity of 86%. The study revealed that the PIIV successfully predicted four systems in our cohort of patients. CONCLUSION: Our work suggests the PIIV might be a reasonable predictor for organ involvement and disease activity in newly diagnosed cSLE, though further research, particularly larger studies, is required to validate these findings, especially regarding organ involvement.
RESUMEN
BACKGROUND: The spectrum of Juvenile Idiopathic Arthritis (JIA) in Africa is still largely unknown. We thus set out to illustrate how we set up the PAFLAR JIA registry and describe the clinical profile of Juvenile Idiopathic Arthritis across various regions in Africa. METHODS: We carried out a retrospective observational cohort study where collaborators were trained on use of the existing PAFLAR REDCAP database to enter data for the JIA patients currently under their care capturing their epidemiological data, clinical features, laboratory investigations, diagnosis and therapy at initial diagnosis. Descriptive statistics including means, standard deviations, medians, interquartile ranges (IQR) for continuous variables and proportions for categorical variables were calculated as appropriate. Tests for difference between groups were performed between categorical variables using Pearson's chi-square or Fisher's exact tests. All analyses were performed using SPSS version 22 software. RESULTS: We enrolled 302 patients, 58.6% (177 of 302) of whom were female. The median age of disease onset was 7 years (range 3-11 years) and the median age at diagnosis was 8.5 years (range 5-12 years). The median duration delay in diagnosis was 6 months (range 1-20.8 months). The JIA categories included Systemic JIA 18.9% (57), Oligoarticular JIA 19.2% (83), Polyarticular RF + ve 5% (15), Polyarticular RF-ve 17.9% (54), Enthesitis Related Arthritis (ERA) 18.2% (55), Psoriatic Arthritis 7% (21) and undifferentiated JIA 5.6% (17). As regards treatment the commonest therapies were NSAID therapy at 31.1%, synthetic DMARDs at 18.1%, synthetic DMARDs combined with NSAIDs at 17.5% and steroid therapy at 9.6%. Biological DMARDs accounted for 2.3% of therapies offered to our patients at diagnosis. The average JADAS score was 10.3 (range 4.8-18.2) and the average CHAQ score was 1.3 (range 0.7-2.0). CONCLUSION: Our study highlights strategies involved in setting up a Pan-African paediatric rheumatology registry that embraces our broad diversity and the vast spectrum of JIA in Africa while comparing the various therapies available to our patients. The PAFLAR JIA registry strives to ensure a comprehensive representation of the diverse healthcare landscapes within the continent. Further longitudinal observation studies are required to ascertain the long-term outcomes of our patients and ultimately help inform policy to create a more favorable health ecosystem to support the healthcare needs of JIA patients in Africa.
