{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T15:54:50Z","timestamp":1792684490405,"version":"4.5.0"},"reference-count":46,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T00:00:00Z","timestamp":1774915200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Immune checkpoint inhibitor-associated myocarditis (ICI-associated myocarditis) is a rare but fatal immune-related adverse event. Early identification of high-risk patients remains challenging. This study aimed to identify risk factors and develop models for predicting both the occurrence and severity of ICI-associated myocarditis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This retrospective unmatched case-control study stratified patients receiving ICIs into ICI-associated myocarditis (stratified into mild and severe subgroups) and controls. Comparative analysis of baseline and onset-phase data was performed, with logistic regression used to identify risk factors for the development of ICI-associated myocarditis and the severe myocarditis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In this cohort of 196 patients (98 myocarditis cases\n                      <jats:italic>vs.<\/jats:italic>\n                      98 controls), a two-tiered risk stratification was established. Patients with myocarditis were further stratified into mild (n=71) and severe (n=27) subgroups. For predicting the occurrence of ICI-associated myocarditis, a baseline model incorporating elevated eosinophil ratio, reduced lymphocyte ratio, and elevated myoglobin demonstrated an area under the ROC curve (AUC) of 0.699 (95% CI, 0.626-0.772,\n                      <jats:italic>P<\/jats:italic>\n                      &amp;lt;\u00a00.001). Upon onset, for predicting severe myocarditis, a model combining electrocardiographic abnormalities (T-wave changes, bundle branch blocks) and marked CK elevation (&amp;gt;10\u00d7 ULN) achieved a higher AUC of 0.769 (95% CI, 0.655-0.882,\n                      <jats:italic>P<\/jats:italic>\n                      &amp;lt;\u00a00.0001). Severe cases presented significantly earlier than mild cases (33\n                      <jats:italic>vs<\/jats:italic>\n                      . 63 days,\n                      <jats:italic>P<\/jats:italic>\n                      =\u00a00.043) and had higher rates of symptoms and concurrent immune-related adverse events.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>A baseline profile of elevated eosinophil ratio, reduced lymphocyte ratio, and elevated myoglobin collectively may help identify patients at risk for ICI-associated myocarditis. At myocarditis onset, a combination of specific electrocardiographic abnormalities and marked CK elevation may predict severe cases. These findings suggest a two-stage approach for early risk stratification and targeted management.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1762144","type":"journal-article","created":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T05:32:22Z","timestamp":1774935142000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Integrated risk stratification for ICI-associated myocarditis: a baseline hematological profile and a combined ECG and enzymatic signature at onset"],"prefix":"10.3389","volume":"17","author":[{"given":"Zhuoling","family":"Zheng","sequence":"first","affiliation":[{"name":"Department of Pharmacy, The Sixth Affiliated Hospital, Sun Yat-Sen University","place":["Guangzhou, Guangdong, China"]},{"name":"Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University","place":["Guangzhou, Guangdong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunmei","family":"Dai","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, The Sixth Affiliated Hospital, Sun Yat-Sen University","place":["Guangzhou, Guangdong, China"]},{"name":"Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University","place":["Guangzhou, Guangdong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Pharmacy & Clinical Pharmacy (School of Integrated Pharmacy), Guangdong Pharmaceutical University","place":["Guangzhou, Guangdong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingwen","family":"Xie","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, The Sixth Affiliated Hospital, Sun Yat-Sen University","place":["Guangzhou, Guangdong, China"]},{"name":"Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University","place":["Guangzhou, Guangdong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, The Sixth Affiliated Hospital, Sun Yat-Sen University","place":["Guangzhou, Guangdong, China"]},{"name":"Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University","place":["Guangzhou, Guangdong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, The Sixth Affiliated Hospital, Sun Yat-Sen University","place":["Guangzhou, Guangdong, China"]},{"name":"Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University","place":["Guangzhou, Guangdong, 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