Left Ventricular Dysfunction in Patients Receiving Cardiotoxic Cancer Therapies Are Clinicians Responding Optimally?

ObjectivesThe purpose of this study was to examine treatment practices for cancer therapy-associated decreased left ventricular ejection fraction (LVEF) detected on echocardiography and whether management was consistent with American College of Cardiology/American Heart Association guidelines.BackgroundPatients treated with anthracyclines or trastuzumab are at risk of cardiotoxicity. Decreased LVEF represents a Class I indication for drug intervention according to American College of Cardiology/American Heart Association guidelines.MethodsPatients receiving anthracycline or trastuzumab at Stanford University from October 2005 to October 2007 and who had undergone echocardiography before and after receiving an anthracycline or trastuzumab were identified. Chart review examined chemotherapy regimens, cardiac risk factors, imaging results, concomitant medications, and cardiology consultations.ResultsEighty-eight patients received therapy with an anthracycline or trastuzumab and had a pre-treatment and follow-up echocardiogram. Ninety-two percent were treated with anthracyclines, 17% with trastuzumab after an anthracycline, and 8% with trastuzumab without previous treatment with anthracycline. Mean baseline LVEF was 60%, with 14% having a baseline <55%. Forty percent had decreased LVEF (<55%) after anthracycline and/or trastuzumab treatment. Of these patients, 40% received angiotensin-converting enzyme inhibitor or angiotensin receptor blocker therapy, 51% beta-blocker therapy, and 54% cardiology consultation. Of patients with asymptomatic decreased LVEF, 31% received angiotensin-converting enzyme inhibitor or angiotensin receptor blocker therapy, 35% beta-blocker therapy, and 42% cardiology consultation. Of those with symptomatic decreased LVEF, 67% received angiotensin-converting enzyme inhibitor or angiotensin receptor blocker therapy, 100% beta-blocker therapy, and 89% cardiology consultation.ConclusionsMany cancer survivors are not receiving treatment consistent with heart failure guidelines. There is substantial opportunity for collaboration between oncologists and cardiologists to improve the care of oncology patients receiving cardiotoxic therapy

screening for transthyretin amyloid cardiomyopathy in everyday practice

Abstract Transthyretin amyloid cardiomyopathy (ATTR-CM) is a life-threatening, progressive, infiltrative disease caused by the deposition of transthyretin amyloid fibrils in the heart, and can often be overlooked as a common cause of heart failure. Delayed diagnosis due to lack of disease awareness and misdiagnosis results in a poorer prognosis. Early accurate diagnosis is therefore key to improving patient outcomes, particularly in the context of both the recent approval of tafamidis in some countries (including the United States) for the treatment of ATTR-CM, and of other promising therapies under development. With the availability of scintigraphy as an inexpensive, noninvasive diagnostic tool, the rationale to screen for ATTR-CM in high-risk populations of patients is increasingly warranted. Here the authors propose a framework of clinical scenarios in which screening for ATTR-CM is recommended, as well as diagnostic "red flags" that can assist in its diagnosis among the wider population of patients with heart failure

Proposed Cardiac End Points for Clinical Trials in Immunoglobulin Light Chain Amyloidosis: Report From the Amyloidosis Forum Cardiac Working Group

Immunoglobulin light chain amyloidosis is a rare, multisystemic, phenotypically heterogenous disease affecting cardiovascular, renal, neurological, and gastrointestinal systems to varying degrees. Its underlying cause is a plasma cell dyscrasia characterized by misfolding of monoclonal immunoglobulin light chains which leads to aggregation and deposition of insoluble amyloid fibrils in target organs. Prognosis is primarily dependent on extent of cardiac involvement and depth of hematologic response to treatment. To facilitate development of new therapies, a public-private partnership was formed between the nonprofit Amyloidosis Research Consortium and the US Food and Drug Administration Center for Drug Evaluation and Research. In 2020, the Amyloidosis Forum launched an initiative to identify novel/composite end points and analytic strategies to expedite clinical trials for development of new therapies for the primary hematologic disorder and organ system manifestations. Specialized working groups identified organ-specific end points; additional working groups reviewed health-related quality of life measures and statistical approaches to data analysis. Each working group comprised amyloidosis experts, patient representatives, statisticians, and representatives from the Food and Drug Administration, the UK Medicines and Healthcare Products Regulatory Agency, and pharmaceutical companies. This review summarizes the proceedings and recommendations of the Cardiac Working Group. Using a modified Delphi method, the group identified, reviewed, and prioritized cardiac end points relevant to immunoglobulin light chain amyloidosis in the context of an antiplasma cell therapy. Prioritized cardiovascular end points included overall survival, hospitalization, N-terminal pro-B-type natriuretic peptide level, 6-minute walk test, Kansas City Cardiac Questionnaire, and cardiac deterioration progression-free survival. These recommended components will be further explored through evaluation of clinical trial datasets and formal guidance from regulatory authorities

Development and validation of a rapid visual technique for left ventricular hypertrophy detection from the electrocardiogram

IntroductionLeft ventricular hypertrophy (LVH) detection techniques on by electrocardiogram (ECG) are cumbersome to remember with modest performance. This study validated a rapid technique for LVH detection and measured its performance against other techniques.MethodsThis was a retrospective cohort study of patients at Stanford Health Care who received ECGs and resting transthoracic echocardiograms (TTE) from 2006 through 2018. The novel technique, Witteles-Somani (WS), assesses for S- and R-wave overlap on adjacent precordial leads. The WS, Sokolow-Lyon, Cornell, and Peguero-Lo Presti techniques were algorithmically implemented on ECGs. Classification metrics, receiver-operator curves, and Pearson correlations measured performance. Age- and sex-adjusted Cox proportional hazard models evaluated associations between incident cardiovascular outcomes and each technique.ResultsA total of 53,333 ECG-TTE pairs from 18,873 patients were identified. Of all ECG-TTE pairs, 21,638 (40.6%) had TTE-diagnosed LVH. The WS technique had a sensitivity of 0.46, specificity of 0.66, and AUROC of 0.56, compared to Sokolow-Lyon (AUROC 0.55), Cornell (AUROC 0.63), and Peguero-Lo Presti (AUROC 0.63). Patients meeting LVH by WS technique had a higher risk of cardiovascular mortality [HR 1.18, 95% CI (1.12, 1.24), P &lt; 0.001] and a higher risk of developing any cardiovascular disease [HR 1.29, 95% CI (1.22, 1.36), P &lt; 0.001], myocardial infarction [HR 1.60, 95% CI (1.44, 1.78), P &lt; 0.005], and heart failure [HR 1.24, 95% CI (1.17, 1.32), P &lt; 0.001].ConclusionsThe WS criteria is a rapid visual technique for LVH detection with performance like other LVH detection techniques and is associated with incident cardiovascular outcomes

High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning

Left ventricular hypertrophy (LVH) results from chronic remodeling caused by a broad range of systemic and cardiovascular disease including hypertension, aortic stenosis, hypertrophic cardiomyopathy, and cardiac amyloidosis. Early detection and characterization of LVH can significantly impact patient care but is limited by under-recognition of hypertrophy, measurement error and variability, and difficulty differentiating etiologies of LVH. To overcome this challenge, we present EchoNet-LVH - a deep learning workflow that automatically quantifies ventricular hypertrophy with precision equal to human experts and predicts etiology of LVH. Trained on 28,201 echocardiogram videos, our model accurately measures intraventricular wall thickness (mean absolute error [MAE] 1.4mm, 95% CI 1.2-1.5mm), left ventricular diameter (MAE 2.4mm, 95% CI 2.2-2.6mm), and posterior wall thickness (MAE 1.2mm, 95% CI 1.1-1.3mm) and classifies cardiac amyloidosis (area under the curve of 0.83) and hypertrophic cardiomyopathy (AUC 0.98) from other etiologies of LVH. In external datasets from independent domestic and international healthcare systems, EchoNet-LVH accurately quantified ventricular parameters (R2 of 0.96 and 0.90 respectively) and detected cardiac amyloidosis (AUC 0.79) and hypertrophic cardiomyopathy (AUC 0.89) on the domestic external validation site. Leveraging measurements across multiple heart beats, our model can more accurately identify subtle changes in LV geometry and its causal etiologies. Compared to human experts, EchoNet-LVH is fully automated, allowing for reproducible, precise measurements, and lays the foundation for precision diagnosis of cardiac hypertrophy. As a resource to promote further innovation, we also make publicly available a large dataset of 23,212 annotated echocardiogram videos