Validation and optimization of classification criteria for childhood-onset systemic lupus erythematosus in a multi-center Chinese cohort

This study evaluated the diagnostic accuracy of the 2012 SLICC and 2019 EULAR/ACR criteria in Chinese cSLE patients and aimed to develop an optimized classification schema based on the 2019 EULAR/ACR criteria, specifically tailored for cSLE. Data from cSLE and control cases were extracted from the CAPRID database. Gold-standard diagnosis were established by consensus among 43 rheumatologists (≥80% agreement). From 1,390 consensus cases, a random selection of 1,045 cases (512 cSLE/533 non-cSLE) were allocated to derivation (n=522) and validation (n=523) cohorts. The 2012 SLICC and 2019 EULAR/ACR criteria were evaluated in the total cohort. Multiple optimization schemes were then developed through LASSO regression with expert consultation in the derivation cohort. All potential optimization schemes underwent validation in the validation cohort, from which the optimal scheme was selected and further evaluated in an ANA-positive subgroup. The 2012 SLICC criteria demonstrated sensitivity of 96.7% and specificity of 96.5%, while the 2019 EULAR/ACR criteria had sensitivity of 95.3% and specificity of 97.8%, with an optimal total score threshold of 10. When both the non-scarring alopecia and arthritis criteria were removed alongside the redefined urinary protein criterion, specificity significantly improved to 99.3% (P < 0.05), while sensitivity remained unaffected at 94.1% (P = 0.210). In the ANA-positive cohort, the optimized integrated scheme significantly improved specificity (97.7% vs. 86.4%, P = 0.012) while maintaining comparable sensitivity (96.2% vs. 97.8%, P = 0.138). Both criteria performed well in Chinese cSLE patients. Optimizing the 2019 EULAR/ACR criteria by removing alopecia and arthritis criteria and modifying the urinary protein criterion enhanced specificity without compromising sensitivity.