Development and validation of a predictive model for cancer therapy-related cardiac dysfunction in breast cancer patients using echocardiographic indicators.

IF 2.9 3区医学 Q2 ONCOLOGY

American journal of cancer research Pub Date : 2025-05-15 eCollection Date: 2025-01-01 DOI:10.62347/WPUW2205

Shan Hui, Junyi Yu, Yuanyuan Tang

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引用次数: 0

Abstract

Objective: This 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.

Methods: A retrospective analysis was conducted on 506 patients treated at Hunan Provincial People's Hospital (2018-2023).

Results: Clinical 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).

Conclusion: This validated tool facilitates early CTRCD risk stratification (C-index 0.80, P < 0.001), supporting personalized monitoring of cardiotoxicity.

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利用超声心动图指标建立和验证乳腺癌患者癌症治疗相关心功能障碍预测模型。

目的：本研究旨在建立和验证乳腺癌化疗、靶向治疗或免疫治疗患者癌症治疗相关性心功能障碍（CTRCD）的预测模型。方法：对2018-2023年湖南省人民医院收治的506例患者进行回顾性分析。结果：临床和影像学生物标志物，包括NT-proBNP （P < 0.001）、左室射血分数(LVEF；P = 0.003)，左房径(LA；P = 0.012)。Lasso-Cox回归鉴定出8个显著预测因子（均P < 0.05），并将其纳入nomogram。该模型在训练队列（AUC 0.82, 95% CI 0.78-0.86）和验证队列（AUC 0.79, 95% CI 0.74-0.83）中都表现出极好的辨别能力。随时间变化的ROC曲线在4周（AUC 0.80, P < 0.001）、8周（AUC 0.81, P < 0.001）和12周（AUC 0.79, P = 0.002）时显示出一致的预测准确性。校准曲线显示出良好的一致性（Hosmer-Lemeshow检验P = 0.34），决策曲线分析证实了该模型的临床效用（净效益>超过阈值概率15%）。结论：该验证工具有助于早期CTRCD风险分层（C-index 0.80, P < 0.001），支持心脏毒性的个性化监测。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

American journal of cancer research ONCOLOGY-

自引率

3.80%

发文量

263

期刊介绍： The American Journal of Cancer Research (AJCR) (ISSN 2156-6976), is an independent open access, online only journal to facilitate rapid dissemination of novel discoveries in basic science and treatment of cancer. It was founded by a group of scientists for cancer research and clinical academic oncologists from around the world, who are devoted to the promotion and advancement of our understanding of the cancer and its treatment. The scope of AJCR is intended to encompass that of multi-disciplinary researchers from any scientific discipline where the primary focus of the research is to increase and integrate knowledge about etiology and molecular mechanisms of carcinogenesis with the ultimate aim of advancing the cure and prevention of this increasingly devastating disease. To achieve these aims AJCR will publish review articles, original articles and new techniques in cancer research and therapy. It will also publish hypothesis, case reports and letter to the editor. Unlike most other open access online journals, AJCR will keep most of the traditional features of paper print that we are all familiar with, such as continuous volume, issue numbers, as well as continuous page numbers to retain our comfortable familiarity towards an academic journal.