Development of cardiac risk prediction model in patients with HER-2 positive breast cancer on trastuzumab therapy.

IF 3.2 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS
Prince Otchere, Olusola Adekoya, Samuel B Governor, Naveen Vuppuluri, Akruti Prabhakar, Stella Pak, Oduro Oppong-Nkrumah, Francis Cook, Rudy Bohinc, Gregory Aune
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引用次数: 0

Abstract

Background: 25% of all breast cancer patients have HER-2 overexpression. Breast Cancer patients with HER-2 overexpression are typically treated with HER-2 inhibitors such as Trastuzumab. Trastuzumab is known to cause a decrease in left ventricular ejection fraction. The aim of this study is to create a cardiac risk prediction tool among women with Her-2 positive breast cancer to predict cardiotoxicity.

Method: Using a split sample design, we created a risk prediction tool using patient level data from electronic medical records. The study included women 18 years of age and older diagnosed with HER-2 positive breast cancer who received Trastuzumab. Outcome measure was defined as a drop in LVEF by more than 10% to less than 53% at any time in the 1-year study period. Logistic regression was used to test predictors.

Results: The cumulative incidence of cardiac dysfunction in our study was 9.4%. The sensitivity and specificity of the model are 46% and 84%, respectively. Given a cumulative incidence of cardiotoxicity of 9%, the negative predictive value of the test was 94%. This suggests that in a low-risk population, the interval of screening for cardiotoxicity may be performed less frequently.

Conclusion: Cardiac risk prediction tool can be used to identify Her-2 positive breast cancer patients at risk of developing cardiac dysfunction. Also, test characteristics in addition to disease prevalence may inform a rational strategy in performing cardiac ultrasound in Her-2 breast cancer patients. We have developed a cardiac risk prediction model with high NPV in a low-risk population which has an appealing cost-effectiveness profile.

Abstract Image

Abstract Image

HER-2阳性乳腺癌患者接受曲妥珠单抗治疗时心脏风险预测模型的建立
背景:25%的乳腺癌患者有HER-2过表达。HER-2过表达的乳腺癌患者通常使用HER-2抑制剂如曲妥珠单抗进行治疗。曲妥珠单抗可导致左心室射血分数降低。本研究的目的是在Her-2阳性乳腺癌患者中建立一种心脏风险预测工具,以预测心脏毒性。方法:采用分离样本设计,利用电子病历中的患者水平数据创建风险预测工具。该研究包括18岁及以上诊断为HER-2阳性乳腺癌并接受曲妥珠单抗治疗的女性。结果测量定义为在1年研究期间的任何时间LVEF下降超过10%至53%以下。采用Logistic回归对预测因子进行检验。结果:本研究中心功能障碍的累计发生率为9.4%。该模型的敏感性为46%,特异性为84%。鉴于心脏毒性的累积发生率为9%,该试验的阴性预测值为94%。这表明,在低风险人群中,心脏毒性筛查的间隔时间可能不那么频繁。结论:心脏风险预测工具可用于识别Her-2阳性乳腺癌患者发生心功能障碍的风险。此外,除了疾病患病率之外,测试特征可能会为Her-2乳腺癌患者进行心脏超声检查提供合理的策略。我们开发了一种低风险人群中具有高净现值的心脏风险预测模型,该模型具有吸引人的成本效益概况。
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
Cardio-oncology
Cardio-oncology Medicine-Cardiology and Cardiovascular Medicine
CiteScore
5.00
自引率
3.00%
发文量
17
审稿时长
7 weeks
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