ArticleAmerican journal of cancer research2025
Development and validation of a predictive model for cancer therapy-related cardiac dysfunction in breast cancer patients using echocardiographic indicators.
Article in American journal of cancer research, 2025. 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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Abstract
objectiveThis study aimed to develop and validate a predictive model for cancer therapy-related cardiac dysfunction (CTRCD) in breast cancer patients undergoing chemotherapy, targeted therapy, or immunotherapy.
methodsA retrospective analysis was conducted on 506 patients treated at Hunan Provincial People's Hospital (2018-2023).
resultsClinical and imaging biomarkers, including NT-proBNP (P < 0.001), left ventricular ejection fraction (LVEF; P = 0.003), and left atrial diameter (LA; P = 0.012), were evaluated. Lasso-Cox regression identified eight significant predictors (all P < 0.05), which were incorporated into a nomogram. The model exhibited excellent discrimination in both the training (AUC 0.82, 95% CI 0.78-0.86) and validation cohorts (AUC 0.79, 95% CI 0.74-0.83). Time-dependent ROC curves demonstrated consistent predictive accuracy at 4 weeks (AUC 0.80, P < 0.001), 8 weeks (AUC 0.81, P < 0.001), and 12 weeks (AUC 0.79, P = 0.002). Calibration curves indicated good agreement (Hosmer-Lemeshow test P = 0.34), and decision curve analysis confirmed the model's clinical utility (net benefit > 15% across threshold probabilities).
conclusionThis validated tool facilitates early CTRCD risk stratification (C-index 0.80, P < 0.001), supporting personalized monitoring of cardiotoxicity.
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