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Evaluation of Risk Prediction Models to Identify Cancer Therapeutics Related Cardiac Dysfunction in Women with HER2+ Breast Cancer.

ABSTRACT: Cancer-therapeutics-related cardiac dysfunction (CTRCD) is an important concern in women receiving trastuzumab therapy for HER2+ breast cancer. However, the ability to assess CTRCD risk remains limited. In this retrospective cohort study, we apply three published risk prediction models (Ezaz et al., NSABP-31 cardiac risk scores (CRS), and HFA-ICOS trastuzumab proforma) to 629 women (mean age 52.4 ± 10.9 years) with Stage I-III HER2+ breast cancer treated with trastuzumab ± anthracyclines to assess their performance to identify CTRCD during or immediately post treatment. Using these models, patients were classified into CTRCD risk categories according to the pre-treatment characteristics. With NSABP-31 CRS and HFA-ICOS proformas, patients in the highest risk category had a 1.7-to-2.4-fold higher relative risk of CTRCD than the low-risk category (p = 0.010 and 0.005, respectively). However, with all three risk models, those in the low-risk category had a high absolute risk of CTRCD (15.5-25.5%). The discrimination of the models for CTRCD (AUC 0.51-0.60) and their calibration was limited. NSAP-31 CRS and HFA-ICOS proformas can identify relative differences in CTRCD risk between patients, but when considering absolute risk, they are only able to identify the highest risk patients. There remains an ongoing need for accurate CTRCD risk prediction models in women with HER2+ breast cancer.

SUBMITTER: Suntheralingam S

PROVIDER: S-EPMC8836544 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Evaluation of Risk Prediction Models to Identify Cancer Therapeutics Related Cardiac Dysfunction in Women with HER2+ Breast Cancer.

Suntheralingam Sivisan S Fan Chun-Po Steve CS Calvillo-Argüelles Oscar O Abdel-Qadir Husam H Amir Eitan E Thavendiranathan Paaladinesh P

Journal of clinical medicine 20220205 3

Cancer-therapeutics-related cardiac dysfunction (CTRCD) is an important concern in women receiving trastuzumab therapy for HER2+ breast cancer. However, the ability to assess CTRCD risk remains limited. In this retrospective cohort study, we apply three published risk prediction models (Ezaz et al., NSABP-31 cardiac risk scores (CRS), and HFA-ICOS trastuzumab proforma) to 629 women (mean age 52.4 ± 10.9 years) with Stage I-III HER2+ breast cancer treated with trastuzumab ± anthracyclines to asse ...[more]

PMID: 35160296

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Project description:BackgroundRisk stratification strategies for cancer therapeutics-related cardiac dysfunction (CTRCD) rely on serial monitoring by specialized imaging, limiting their scalability. We aimed to examine an application of artificial intelligence (AI) to ECG images as a surrogate for imaging risk biomarkers and its association with early CTRCD.MethodsAcross a US-based health system (2013-2023), we identified 1550 patients (aged, 60 [interquartile range, 51-69] years, 1223 [78.9%] women) without cardiomyopathy who received anthracyclines or trastuzumab for breast cancer or non-Hodgkin lymphoma and had ECG performed ≤12 months before treatment. We deployed a validated AI model of left ventricular systolic dysfunction to baseline ECG images and defined low-, intermediate-, and high-risk groups based on AI-ECG left ventricular systolic dysfunction probabilities of <0.01, 0.01 to 0.1, and ≥0.1 (positive screen), respectively. We explored the association with early CTRCD (new cardiomyopathy, heart failure, or left ventricular ejection fraction <50%), or left ventricular ejection fraction <40%, up to 12 months after treatment. In a mechanistic analysis, we assessed the association between global longitudinal strain and AI-ECG left ventricular systolic dysfunction probabilities in studies performed within 15 days of each other.ResultsAmong 1550 patients without known cardiomyopathy (median follow-up, 14.1 [interquartile range, 13.4-17.1] months), 83 (5.4%), 562 (36.3%), and 905 (58.4%) were classified as high, intermediate, and low risk, respectively, by baseline AI-ECG. A high-risk versus low-risk AI-ECG screen (≥0.1 versus <0.01) was associated with a 3.4-fold and 13.5-fold higher incidence of CTRCD (adjusted hazard ratio, 3.35 [95% CI, 2.25-4.99]) and left ventricular ejection fraction <40% (adjusted hazard ratio, 13.52 [95% CI, 5.06-36.10]), respectively. Post hoc analyses supported longitudinal increases in AI-ECG probabilities within 6 to 12 months of a CTRCD event. Among 1428 temporally linked echocardiograms and ECGs, AI-ECG left ventricular systolic dysfunction probabilities were associated with worse global longitudinal strain (global longitudinal strain, -19% [interquartile range, -21% to -17%] for probabilities <0.1, to -15% [interquartile range, -15% to -9%] for ≥0.5 [P<0.001]).ConclusionsAI applied to baseline ECG images can stratify the risk of early CTRCD associated with anthracycline or trastuzumab exposure in the setting of breast cancer and non-Hodgkin lymphoma therapy.

Project description:ObjectivesThis study sought to determine the relationships between echocardiography-derived measures of myocardial mechanics and cancer therapeutics-related cardiac dysfunction (CTRCD).BackgroundDoxorubicin and trastuzumab are highly effective breast cancer therapies, but have a substantial risk of CTRCD. There is a critical need for the early detection of patients at increased risk of toxicity.MethodsWe performed a prospective, longitudinal cohort study of breast cancer participants undergoing doxorubicin and/or trastuzumab therapy. Echocardiography was performed prior to therapy initiation (baseline) and at standardized follow-up intervals during and after completion of therapy. Ejection fraction (EF), strain, strain rate, and ventricular-arterial coupling (effective arterial elastance [Ea]/end-systolic elastance [Eessb]) were quantitated. CTRCD was defined as a ≥10% reduction in EF from baseline to <50%. Multivariable logistic regression models were used to determine the associations between baseline levels and changes from baseline in echocardiographic measures and CTRCD. Receiver-operating characteristic curves were used to evaluate the predictive ability of these measures.ResultsIn total, 135 participants contributed 517 echocardiograms to the analysis. Over a median follow-up time of 1.9 years (interquartile range: 0.9 to 2.4 years), 21 participants (15%) developed CTRCD. In adjusted models, baseline levels and changes in Ea/Eessb, circumferential strain, and circumferential strain rate were associated with 21% to 38% increased odds of CTRCD (p < 0.001). Changes in longitudinal strain (p = 0.037), radial strain (p = 0.015), and radial strain rate (p = 0.006) were also associated with CTRCD. Ea/Eessb (area under the curve: 0.703; 95% confidence interval: 0.583 to 0.807) and circumferential strain (area under the curve: 0.655; 95% confidence interval: 0.517 to 0.767) demonstrated the greatest predictive utility. Sensitivity analyses using an alternative CTRCD definition did not impact our results.ConclusionsOver an extended follow-up time, ventricular-arterial coupling and circumferential strain were strongly predictive of CTRCD. Our findings suggest a noninvasive strategy to identify high-risk patients prior to, during, and after cardiotoxic cancer therapy.

Dataset Information

Evaluation of Risk Prediction Models to Identify Cancer Therapeutics Related Cardiac Dysfunction in Women with HER2+ Breast Cancer.

Publications

Evaluation of Risk Prediction Models to Identify Cancer Therapeutics Related Cardiac Dysfunction in Women with HER2+ Breast Cancer.

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