Clinico‐sero‐pathological profiles and risk prediction model of idiopathic inflammatory myopathy (IIM) patients with different perifascicular changes

Author:

Zhang Lining12ORCID,Fu Lijun3,Zhang Guoyong2,Hou Ying2ORCID,Ma Xiaotian4,Zhao Dandan2,Li Wei2,Dai Tingjun2ORCID,Shu Qiang15,Yan Chuanzhu2678ORCID,Zhao Bing6ORCID

Affiliation:

1. Department of Rheumatology Qilu Hospital of Shandong University Jinan Shandong China

2. Department of Neurology Qilu Hospital of Shandong University Jinan Shandong China

3. School of Finance Southwestern University of Finance and Economics Chengdu China

4. Department of Medicine Experimental Center, Qilu Hospital (Qingdao), Cheeloo College of Medicine Shandong University Qingdao Shandong China

5. Shandong Key Laboratory of Medicine and Prevention Integration in Rheumatism and Immunity Disease Qilu Hospital of Shandong University Jinan Shandong China

6. Department of Neurology, Qilu Hospital (Qingdao), Cheeloo College of Medicine Shandong University Qingdao Shandong China

7. Research Institute of Neuromuscular and Neurodegenerative Diseases and Department of Neurology, Qilu Hospital Shandong University Jinan Shandong China

8. Mitochondrial Medicine Laboratory, Qilu Hospital (Qingdao) Shandong University Qingdao Shandong China

Abstract

AbstractAimsTo explore the clinico‐sero‐pathological characteristics and risk prediction model of idiopathic inflammatory myopathy (IIM) patients with different muscular perifascicular (PF) changes.MethodsIIM patients in our center were enrolled and the clinico‐sero‐pathological data were retrospectively analyzed. A decision tree model was established through machine learning.ResultsThere were 231 IIM patients enrolled, including 53 with perifascicular atrophy (PFA), 39 with perifascicular necrosis (PFN), and 26 with isolated perifascicular enhancement of MHC‐I/MHC‐II (PF‐MHCn). Clinically, PFA patients exhibited skin rashes and dermatomyositis‐specific antibodies (DM‐MSAs, 74.5%) except for anti‐Mi2. PFN patients showed the most severe muscle weakness, highest creatine kinase (CK), anti‐Mi2 (56.8%), and anti‐Jo‐1 (24.3%) antibodies. PF‐MHCn patients demonstrated negative MSAs (48.0%) and elevated CK. Histopathologically, MAC predominantly deposited on PF capillaries in PFA but on non‐necrotic myofiber in PFN (43.4% and 36.8%, p < 0.001). MxA expression was least in PF‐MHCn (36.0% vs. 83.0% vs. 63.2%, p < 0.001). The decision tree model could effectively predict different subgroups, especially PFA and PFN.ConclusionsThree types of PF change of IIMs representing distinct clinico‐serological characteristics and pathomechanism. Undiscovered MSAs should be explored especially in PF‐MHCn patients. The three pathological features could be accurately predicted through the decision tree model.

Funder

Natural Science Foundation of Shandong Province

National Natural Science Foundation of China

Publisher

Wiley

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