Anti-melanoma differentiation-associated gene 5-positive dermatomyositis-associated interstitial lung disease (MDA5 + DM-ILD) is a life-threatening disease. This study aimed to develop a novel pulmonary CT visual scoring method for assessing the prognosis of the disease, and an artificial intelligence (AI) algorithm-based analysis and an idiopathic pulmonary fibrosis (IPF)-based scoring were conducted as comparators. A retrospective cohort of hospitalized patients with MDA5 + DM-ILD was analyzed. Since most fatalities occur within the first half year of the disease course, the primary outcome was the six-month all-cause mortality since the time of admission. A ground glass opacity (GGO) and consolidation-weighted CT visual scoring model for MDA5 + DM-ILD, namely ‘MDA5 score’, was then developed with C-index values of 0.80 (95%CI 0.75–0.86) in the derivation dataset (n = 116) and 0.84 (95%CI 0.71–0.97) in the validation dataset (n = 57), respectively. While, the AI algorithm-based analysis, namely ‘AI score’, yielded C-index 0.78 (95%CI 0.72–0.84) for the derivation dataset and 0.77 (95%CI 0.64–0.90) for the validation dataset. These findings suggest that the newly derived ‘MDA5 score’ may serve as an applicable prognostic predictor for MDA5 + DM-ILD and facilitate further clinical trial design. The AI based CT quantitative analysis provided a promising solution for ILD evaluation.
【저자키워드】 Risk factors, Idiopathic inflammatory myopathies, 【초록키워드】 Prognosis, pulmonary fibrosis, Interstitial lung disease, MDA5, Clinical trial design, dataset, GGO, prognostic, disease, ILD, Admission, fatality, Analysis, Ground glass opacity, Quantitative analysis, Primary outcome, 95%CI, C-index, all-cause mortality, life-threatening, retrospective cohort, while, pulmonary CT, Course, analyzed, develop, the disease, conducted, provided, facilitate, occur, hospitalized patient, 【제목키워드】 Prognosis, Interstitial lung disease, predict, dermatomyositis, positive,