Author:
Wang Lei,Lv Chengyin,You Hanxiao,Xu Lingxiao,Yuan Fenghong,Li Ju,Wu Min,Zhou Shiliang,Da Zhanyun,Qian Jie,Wei Hua,Yan Wei,Zhou Lei,Wang Yan,Yin Songlou,Zhou Dongmei,Wu Jian,Lu Yan,Su Dinglei,Liu Zhichun,Liu Lin,Ma Longxin,Xu Xiaoyan,Zang Yinshan,Liu Huijie,Ren Tianli,Liu Jin,Wang Fang,Zhang Miaojia,Tan Wenfeng
Abstract
BackgroundThe prognosis of anti-melanoma differentiation-associated gene 5 positive dermatomyositis (anti-MDA5+DM) is poor and heterogeneous. Rapidly progressive interstitial lung disease (RP-ILD) is these patients’ leading cause of death. We sought to develop prediction models for RP-ILD risk in anti-MDA5+DM patients.MethodsPatients with anti-MDA5+DM were enrolled in two cohorts: 170 patients from the southern region of Jiangsu province (discovery cohort) and 85 patients from the northern region of Jiangsu province (validation cohort). Cox proportional hazards models were used to identify risk factors of RP-ILD. RP-ILD risk prediction models were developed and validated by testing every independent prognostic risk factor derived from the Cox model.ResultsThere are no significant differences in baseline clinical parameters and prognosis between discovery and validation cohorts. Among all 255 anti-MDA5+DM patients, with a median follow-up of 12 months, the incidence of RP-ILD was 36.86%. Using the discovery cohort, four variables were included in the final risk prediction model for RP-ILD: C-reactive protein (CRP) levels, anti-Ro52 antibody positivity, short disease duration, and male sex. A point scoring system was used to classify anti-MDA5+DM patients into moderate, high, and very high risk of RP-ILD. After one-year follow-up, the incidence of RP-ILD in the very high risk group was 71.3% and 85.71%, significantly higher than those in the high-risk group (35.19%, 41.69%) and moderate-risk group (9.54%, 6.67%) in both cohorts.ConclusionsThe CROSS model is an easy-to-use prediction classification system for RP-ILD risk in anti-MDA5+DM patients. It has great application prospect in disease management.
Funder
National Natural Science Foundation of China
Cited by
4 articles.
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