Evidence map›Paper›PMID 42839683›Full record

ArticleClinical and translational medicine2026

A serum proteomics-based predictive model for steroid-resistant immune checkpoint inhibitor associated myocarditis.

Yerui Zhang, Yihan Li, Jian Zhang, Xiaozhen He, Yihui Shen, Yuchen Xu, Hui Zhang, Jianan Pan, Xuejun Wang, Shilong Zhang and 2 more

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Article in Clinical and translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

12 authors.

Yerui Zhang *Department of Echocardiography, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China.
Yihan Li *Department of Cardiovascular Medicine, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Jian Zhang *Department of Echocardiography, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China.ORCID https://orcid.org/0000-0002-7582-0965
Xiaozhen HeDepartment of Echocardiography, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China.
Yihui ShenDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China.ORCID https://orcid.org/0000-0001-8724-1381
Yuchen XuDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China.
Hui ZhangDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China.
Jianan PanDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China.ORCID https://orcid.org/0000-0002-5538-4078
Xuejun WangDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China.
Shilong ZhangDepartment of Medical Oncology, Zhongshan Hospital, Fudan University, Shanghai, China.
Yan WangDepartment of Medical Oncology, Zhongshan Hospital, Fudan University, Shanghai, China.
Leilei ChengDepartment of Echocardiography, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China.ORCID https://orcid.org/0000-0003-0677-7892

Funding

National Natural Science Foundation of China 82170359National Natural Science Foundation of China 82470354Noncommunicable Chronic Diseases-National Science and Technology Major Project 2023ZD0502800Non-Profit Central Research Institute Fund of Chinese Academy of Medical Sciences 2024-JKCS-28Shanghai Shenkang Hospital Development CenterShanghai Shenkang Hospital Development Center municipal hospital diagnosis and treatment technology project SHDC22023207
6 · The paper itself

Abstract

backgroundImmune checkpoint inhibitor-associated myocarditis (ICIAM) is one of the immune-related adverse events (irAEs) with low incidence but extremely high mortality. High-dose glucocorticoid pulse therapy remains the recommended initial treatment for patients with ICIAM. However, an inadequate response to corticosteroid therapy is observed in some patients, who are subsequently classified as having steroid-resistant immune checkpoint inhibitor-associated myocarditis (srICIAM). Early combination of second-line immunosuppression may represent an effective therapeutic strategy. However, Biomarkers capable of identifying such patients before treatment are currently lacking. We therefore sought to characterize circulating inflammatory proteins associated with corticosteroid responsiveness and to derive a preliminary serum-based prediction model for steroid-resistant ICIAM (srICIAM).

methodsSerum specimens obtained from patients with ICIAM at baseline and after methylprednisolone treatment were analyzed to quantify circulating immune-related proteins using an antibody-based proteomic assay. We developed a preliminary model for the early identification of patients at risk of srICIAM using proteins selected by three complementary machine-learning algorithms and evaluated its discriminatory performance in an internal hold-out cohort.

resultsPretreatment serum samples from 47 patients with ICIAM were used to establish a protein-based prediction model, with 33 patients assigned to model development and 14 to internal validation. Patients with a high srICIAM predictive score (≥.5625) based on CXCL9, TRANCE and MMP1 were more likely to show an inadequate early response to corticosteroid therapy and may warrant closer clinical monitoring and further evaluation. The analysis also revealed that several serum immune proteins decreased in patients with ICIAM after methylprednisolone therapy. Serum CXCL9 levels were positively correlated with lactate dehydrogenase (LDH) and cardiac troponin T (cTnT).

conclusionSerum immune proteins were dynamically altered in patients with ICIAM after methylprednisolone therapy. The preliminary score may enable earlier recognition of patients at risk of an inadequate corticosteroid response.

Indexed as

Immune Checkpoint InhibitorsMyocarditisProteomicsAdrenal Cortex HormonesAdultBiomarkersFemaleHumansMaleMiddle AgedAdrenal Cortex HormonesBiomarkersImmune Checkpoint Inhibitorsdisease biomarkerimmune checkpoint inhibitorsmachine learningmyocarditis

Identifiers

PMID42839683
PMCPMC13643220

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.