Systemic lupus international collaborating clinics-2012 and European league against rheumatism/American college of rheumatology-2019 classification criteria for systemic lupus erythematosus associated with childhood-onset auto-immune cytopenia.

INTRODUCTION: Systemic Lupus Erythematosus (SLE) can be diagnosed using the 2012 criteria of the Systemic Lupus International Collaborating Clinics (SLICC) and, more recently, the 2019 criteria of the European League Against Rheumatism/American College of Rheumatology (EULAR/ACR). Hematological involvement is scored differently by these classifications. Our objective was to compare both criteria in a cohort of children with autoimmune cytopenia (AIC)-associated SLE. METHOD: We included 79 patients with childhood-onset AIC as the first manifestations of SLE. RESULTS: The median age at SLE diagnosis was 14.5 years (1.1-21.4 years). The SLICC criteria were fulfilled by 76/79 (96%) patients and the EULAR/ACR criteria by 72/79 (91%) patients during follow-up. The SLICC and EULAR/ACR criteria were discordant (not concomitantly fulfilled) in 25/79 (32%) patients. Non-hematological clinical manifestations were more frequently observed in SLE diagnosis when the criteria were concordant (30/54, 56%) than when they were not (5/25, 20%) (p = 0.004). In 16/25 (64%) discordant patients, the SLICC criteria allowed earlier diagnosis of SLE. Finally, the attribution of a maximum weight of 6 to the hematological involvement of the EULAR/ACR criteria increased the sensitivity thereof from 63/79 (80%) to 76/79 (96%) in our population. CONCLUSION: The SLICC 2012 and EULAR/ACR 2019 criteria do not effectively diagnose SLE in children when AIC is the predominant feature. The SLICC criteria appear to be more effective in this population of SLE patients. An increase in the maximum weight of hematological involvement to 6 increases the sensitivity of the EULAR/ACR criteria for SLE diagnosis in children.

Prediction of the Clinical Course of Immune Thrombocytopenia in Children by Platelet Kinetics.

Childhood immune thrombocytopenia (ITP) is a rare autoimmune disorder characterized by isolated thrombocytopenia. Prolonged ITP (persistent and chronic) leads to a reduced quality of life for children in many domains. To provide optimal support for children, with ITP, it is important to be able to predict those who will develop prolonged ITP. This study aimed to develop a mathematical model based on platelet recovery that allows the early prediction of prolonged ITP. In this retrospective study, we used platelet counts from the 6 months following the diagnosis of ITP to model the kinetics of change in platelet count using a pharmacokinetic-pharmacodynamic model. In a learning set (n = 103), platelet counts were satisfactorily described by our kinetic model. The Kheal parameter, which describes spontaneous platelet recovery, allowed a distinction between acute and prolonged ITP with an area under the curve (AUC) of 0.74. In a validation set (n = 58), spontaneous platelet recovery was robustly predicted using platelet counts from 15 (AUC = 0.76) or 30 (AUC = 0.82) days after ITP diagnosis. In our model, platelet recovery quantified using the kheal parameter allowed prediction of the clinical course of ITP. Future prospective studies are needed to improve the predictivity of this model, in particular, by combining it with the predictive scores previously reported in the literature.