Development of peripheral biomarker-based prognostic nomograms for short-term and long-term survival in immune checkpoint inhibitor-associated myocarditis

基于外周生物标志物的免疫检查点抑制剂相关性心肌炎短期和长期生存预后预测列线图的构建

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Abstract

BACKGROUND: Immune checkpoint inhibitor-associated myocarditis (ICI myocarditis) is a rare but highly fatal immune-related adverse reaction. This study aimed to develop nomogram prognostic models for both short-term and long-term survival outcomes in patients with ICI myocarditis based on key biomarkers in peripheral blood. METHODS: In this single-center retrospective study, we included 90 patients with ICI myocarditis at the Fourth Hospital of Hebei Medical University. Critical peripheral biomarkers associated with 40-day and 1-year overall survival (OS) were identified. Two prognostic models were developed and evaluation of the models were performed with receiver operating characteristic (ROC) curves, C-index, calibration curves, and decision curve analysis (DCA). RESULTS: A total of 24 patients (26.7%) succumbed within 40 days, while 40 patients (44.4%) died within one year. Cardiac troponin-I (cTnI), N-terminal pro-brain natriuretic peptide (NTBNP) and lactic dehydrogenase-to-albumin ratio (LAR) were identified as critical prognostic factors for 40-day OS in patients with ICI myocarditis and utilized to develop a nomogram model. The model demonstrates an area under the curve (AUC) of 0.867 [95% confidence interval (CI): 0.774-0.960] and a C-index of 0.824. Another predictive model for the 1-year OS was developed based on cTnI, NTBNP, LAR and systemic inflammatory response index (SIRI) with an AUC of 0.765 (95% CI: 0.664-0.866) and a C index of 0.742. The calibration curve demonstrates that both models exhibit strong consistency. The results of the DCA further indicate that both nomograms possess substantial clinical utility. CONCLUSIONS: These two prediction models will enable clinicians to more effectively utilize readily available peripheral blood biomarkers for the convenient and efficient identification of high-risk patients with poor prognoses, thereby facilitating early intervention.

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