Risk factors analysis and prediction model establishment of anti-MDA5 antibody-positive dermatomyositis with rapid progression of interstitial lung disease
10.3760/cma.j.cn431274-20221017-01032
- VernacularTitle:抗黑色素瘤分化相关基因5抗体阳性皮肌炎合并间质性肺病急进性进展的危险因素分析与预测模型建立
- Author:
Yafei WANG
1
;
Hongxia LI
;
Yuan FENG
;
Yan ZHANG
;
Zhenbiao WU
Author Information
1. 空军军医大学第二附属医院风湿免疫科，西安 710038
- Keywords:
Dermatomyositis;
Lung diseases, interstitial;
Melanoma differentiation-associated gene-5;
Models, statistical
- From:
Journal of Chinese Physician
2023;25(8):1153-1158
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the Risk factors for rapid progression of inpatients with anti-melanoma differentiation associated gene5 (MDA5) antibody-positive dermamyositis (DM) complicated with interstitial lung disease (ILD), and construct a clinical predictive model.Methods:A total of 63 hospitalized patients with anti MDA5 positive DM combined with ILD (MDA5+ DM-ILD) from January 1, 2016 to May 30, 2022 at the Second Affiliated Hospital of the Air Force Military Medical University were included in the study. They were divided into a control group (DM-ILD) and an observation group (DM-RPPILD) based on whether they had rapidly progressing interstitial lung disease (RPILD). Retrospective collection and organization of clinical case data from patients were conducted, and binary logistic regression was used to summarize the risk factors of DM-RPILD. R software was used to construct a clinical prediction model for RPILD occurrence using training set data, and validation set data was used to verify the predictive ability of the model.Results:The proportion of patients with SpO 2<90% at the initial diagnosis of ILD, the titers of anti MDA5 antibodies, immunoglobulin M (IgM), serum ferritin (FER) levels, and positive rates of anti Ro52 antibodies in the observation group were higher than those in the control group, the lymphocyte (LYM) count level was lower than that of the control group (all P<0.05). Binary logistic regression analysis showed SpO 2<90% at the initial diagnosis of ILD, FER level, LYM count, and anti Ro52 antibody were the influencing factors for the occurrence of RPILD (all P<0.05). The area under the curve (AUC) of the training set prediction model for predicting resistance to MDA5+ DM-RPILD was 0.922(95% CI: 0.887-0.957), with a sensitivity of 95.7% and a specificity of 72.5%; In the validation set, the prediction model predicted an AUC of 0.939(95% CI: 0.904-0.974) for resistance to MDA5+ DM-RPILD, with a sensitivity of 90.0% and a specificity of 88.9%; The calibration curves of the training and validation sets indicated that the predictive model had good calibration ability. Conclusions:SpO 2<90% at the initial diagnosis of ILD, FER levels increase, LYM count levels decrease, and anti Ro52 antibody positivity are risk factors for RPILD. The constructed clinical model has good predictive ability and has certain guiding significance for clinical work.
