Prediction model for the pretreatment evaluation of mortality risk in anti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis with interstitial lung disease

作者：Xianhua Gui, Wang‐Zhong Li, Yanzhe Yu, Tingting Zhao, Ziyi Jin, Kaifang Meng, Rujia Wang, Shenyun Shi, Min Yu, Miao Ma, Lulu Chen, Wei Luan, Xiaoyan Xin, Yuying Qiu, Xiaohua Qiu, Yingwei Zhang, Min Cao, Mengshu Cao, Jinghong Dai, Hourong Cai, Mei Huang, Yonglong Xiao · 发表于：Frontiers in Immunology · 年份：2022 · DOI：10.3389/fimmu.2022.978708 · 被引用次数：15 · 研究领域：Inflammatory Myopathies and Dermatomyositis、Systemic Sclerosis and Related Diseases、Skin Diseases and Diabetes

Background: Anti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis with interstitial lung disease (anti-MDA5 DM-ILD) is a disease with high mortality. We sought to develop an effective and convenient prediction tool to estimate mortality risk in patients with anti-MDA5 DM-ILD and inform clinical decision-making early. Methods: This prognostic study included Asian patients with anti-MDA5 DM-ILD hospitalized at the Nanjing Drum Hospital from December 2016 to December 2020. Candidate laboratory indicators were retrospectively collected. Patients hospitalized from 2016 to 2018 were used as the discovery cohort and applied to identify the optimal predictive features using a least absolute shrinkage and selection operator (LASSO) logistic regression model. A risk score was determined based on these features and used to construct the mortality risk prediction model in combination with clinical characteristics. Results were verified in a temporal validation comprising patients treated between 2019 and 2020. The primary outcome was mortality risk within one year. The secondary outcome was overall survival. The prediction model's performance was assessed in terms of discrimination, calibration, and clinical usefulness. Results: This study included 127 patients, (72 men [56.7%]; median age, 54 years [interquartile range, 48-63 years], split into discovery (n = 87, 70%) and temporal validation (n=37, 30%) cohorts. Five optimal features were selected by LASSO lo...