Evidence map›Paper›PMID 39082198›Full record

ArticleCancer medicine2024

Early identification of severe immune checkpoint inhibitor associated myocarditis: From an electrocardiographic perspective.

Yongyin Gao, Hongdian Zhang, Yanli Qiu, Xueyan Bian, Xue Wang, Yue Li

Abstract read
In one paragraph

Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

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10citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
  2. Machine learning approaches to predict early cardiac immune-related adverse events in patients receiving immune checkpoint inhibitors.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yongyin GaoDepartment of Cardio-pulmonary Functions, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Hongdian ZhangDepartment of Esophageal Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and therapy, Key Laboratory of Digestive Cancer of Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Yanli QiuDepartment of Cardio-pulmonary Functions, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Xueyan BianDepartment of Cardio-pulmonary Functions, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Xue WangDepartment of Cardio-pulmonary Functions, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Yue LiDepartment of Cardio-pulmonary Functions, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China.ORCID 0009-0008-9979-9129

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesImmune checkpoint inhibitor (ICI)-associated myocarditis, particularly severe ICI-associated myocarditis, has a high mortality rate. However, the predictive value of electrocardiogram (ECG) remains unclear. The present study aimed to evaluate the predictive value of clinical and electrocardiographic parameters for severe myocarditis.

methodsClinical and electrocardiographic data of 73 cancer patients with ICI-associated myocarditis were retrospectively collected. The severity of ICI-associated myocarditis was graded using the NCCN guidelines for managing immunotherapy-related toxicities. Myocarditis grades 1-2 and grades 3-4 were classified as mild and severe myocarditis, respectively. Logistic regression analysis was performed to analyze the predictive value of each parameter in predicting severe myocarditis.

resultsAmong the 73 patients with myocarditis, 20 (27.4%) patients had severe myocarditis. Compared with mild myocarditis group, sinus tachycardia (p = 0.001), QRS duration ≥110 ms (p = 0.001), prolonged QTc interval (p < 0.001), and bundle branch block (p = 0.007) at the time of myocarditis were more common in the severe myocarditis group. Logistic regression analysis revealed that sinus tachycardia (p = 0.028) and QTc interval prolongation (p = 0.007) were predictors of severe myocarditis. Whereas the predictive value of other electrocardiographic parameters was weak. Concurrent targeted therapy didn't increase the risk of severe myocarditis. A high NT-proBNP level was associated with severe myocarditis.

conclusionsECG at the onset of myocarditis manifested as sinus tachycardia and prolonged QTc interval predicted a high risk of severe myocarditis. Early detection of ECG abnormalities may faciliate early detection of severe ICI-associated myocarditis.

Indexed as

ElectrocardiographyImmune Checkpoint InhibitorsMyocarditisAdultAgedFemaleHumansMaleMiddle AgedNatriuretic Peptide, BrainNeoplasmsPredictive Value of TestsRetrospective StudiesSeverity of Illness IndexImmune Checkpoint InhibitorsNatriuretic Peptide, Brainelectrocardiogramimmune checkpoint inhibitorsQTc intervalsevere ICI‐associated myocarditissinus tachycardia

Identifiers

PMID39082198
PMCPMC11289619

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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.