Abstract
Background Severe juvenile dermatomyositis(JDM)may progress rapidly with a poor prognosis.Early identification is somewhat difficult,and currently,there is a lack of a risk prediction model for severe JDM.Objective To describe the clinical characteristics of different myositis antibody subtypes in JDM,to construct and validate a risk prediction model for severe JDM.Design A case-control study.Methods Clinical data including demographic characteristics,clinical manifestations,laboratory indices,and imaging findings of JDM patients admitted to Children's Hospital of Chongqing Medical University from January 2015 to January 2025 were collected.The relationship between clinical characteristics and myositis antibodies was analyzed.According to the Chinese guidelines for the diagnosis and treatment of JDM,patients were divided into the severe group and the non-severe group.The study population were randomly divided into a development set and a validation set at a ratio of 7∶3.The least absolute shrinkage and selection operator(LASSO)was used in the development set to identify predictive laboratory indices and create a laboratory risk score.Multivariate logistic regression analysis was performed to analyze the risk factors for severe JDM and construct a nomogram risk prediction model,the predictive performance of the model was then validated and evaluated.Main Outcome Measures Clinical phenotypic characteristics of children with different myositis antibodies;the predictive performance of the model for JDM complicated with severity.Results(1)A total of 236 JDM children were included in the analysis of clinical characteristics and myositis antibodies.There were 123 males(52.1%),the median age of onset was 6.42(4.31,9.67)years.Myositis antibodies were detected in 190 children at the first diagnosis,and 125(65.8%)were positive for myositis antibodies.The positive rate of myositis-specific autoantibodies was 54.7%(104/190).The anti-nuclear matrix protein 2(NXP2)antibody was the most common(43/190,22.6%),followed by the anti-melanoma differentiation-associated gene 5(MDA5)antibody(35/190,18.4%)and the anti-transcriptional intermediate factor 1γ(TIF1-γ)antibody(12/190,6.3%).There were significant differences in the composition ratios of severe conditions,Gottron sign,joint pain,dysphagia,fever,calcinosis,interstitial lung disease(ILD),abnormal electromyogram,and the counts of AST,ALT,ALB,and CK among different myositis antibodies(P<0.05).Among them,severe conditions,dysphagia,calcinosis,increased counts of AST and CK,and decreased count of ALB were mainly seen in children with anti-NXP2 antibody.Joint pain,fever,ILD,and increased ALT count were mainly seen in children with anti-MDA5 antibody.Gottron sign was mainly seen in children with anti-TIF1-γ antibody.(2)A total of 201 cases were included in model construction,with 140 cases in the development set(20 severe cases)and 61 cases in the validation set(12 severe cases).LASSO regression identified four optimal laboratory index characteristics in the development set:anti-NXP2 antibody,ALB,PLT,and AST,and formed a laboratory risk score.Multivariate logistic regression analysis identified 6 predictors,including hoarseness(OR=7.493,95%CI:1.396-48.678,P=0.023),oral ulcers(OR=5.304,95%CI:0.840-38.149,P=0.079),subcutaneous edema(OR=9.348,95%CI:2.167-47.504,P=0.004),calcinosis(OR=8.844,95%CI:0.798-105.194,P=0.071),ascites(OR=5.781,95%CI:0.659-48.940,P=0.099),and laboratory risk score(OR=11.739,95%CI:3.366-59.930,P=0.001),to construct a nomogram prediction model.The AUC of the development set and the validation set were 0.960(95%CI:0.929-0.991)and 0.920(95%CI:0.841-0.999)respectively.The calibration curve was close to the ideal curve,indicating good calibration.Clinical decision curve analysis(DCA)suggested that the prediction model provided a greater net benefit at most threshold probabilities.Conclusion There are differences in the clinical manifestations of different myositis antibody subtypes in JDM.The prediction model for severe JDM based on indicators such as positive anti-NXP2 antibody,hoarseness,subcutaneous edema,calcinosis,and ascites has good predictive value.关键词
幼年型皮肌炎/重症/肌炎抗体/预测模型/列线图Key words
Juvenile dermatomyositis/Severe/Myositis antibodies/Prediction model/Nomogram
