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BACKGROUND - Immune checkpoint inhibitors (ICIs) have substantially improved clinical outcomes in multiple cancer types and are increasingly being used in early disease settings and in combinations of different immunotherapies. However, ICIs can also cause severe or fatal immune-related adverse-events (irAEs). We aimed to identify and characterise cardiovascular irAEs that are significantly associated with ICIs.
METHODS - In this observational, retrospective, pharmacovigilance study, we used VigiBase, WHO's global database of individual case safety reports, to compare cardiovascular adverse event reporting in patients who received ICIs (ICI subgroup) with this reporting in the full database. This study included all cardiovascular irAEs classified by group queries according to the Medical Dictionary for Regulatory Activities, between inception on Nov 14, 1967, and Jan 2, 2018. We evaluated the association between ICIs and cardiovascular adverse events using the reporting odds ratio (ROR) and the information component (IC). IC is an indicator value for disproportionate Bayesian reporting that compares observed and expected values to find associations between drugs and adverse events. IC is the lower end of the IC 95% credibility interval, and an IC value of more than zero is deemed significant. This study is registered with ClinicalTrials.gov, number NCT03387540.
FINDINGS - We identified 31 321 adverse events reported in patients who received ICIs and 16 343 451 adverse events reported in patients treated with any drugs (full database) in VigiBase. Compared with the full database, ICI treatment was associated with higher reporting of myocarditis (5515 reports for the full database vs 122 for ICIs, ROR 11·21 [95% CI 9·36-13·43]; IC 3·20), pericardial diseases (12 800 vs 95, 3·80 [3·08-4·62]; IC 1·63), and vasculitis (33 289 vs 82, 1·56 [1·25-1·94]; IC 0·03), including temporal arteritis (696 vs 18, 12·99 [8·12-20·77]; IC 2·59) and polymyalgia rheumatica (1709 vs 16, 5·13 [3·13-8·40]; IC 1·33). Pericardial diseases were reported more often in patients with lung cancer (49 [56%] of 87 patients), whereas myocarditis (42 [41%] of 103 patients) and vasculitis (42 [60%] of 70 patients) were more commonly reported in patients with melanoma (χ test for overall subgroup comparison, p<0·0001). Vision was impaired in five (28%) of 18 patients with temporal arteritis. Cardiovascular irAEs were severe in the majority of cases (>80%), with death occurring in 61 (50%) of 122 myocarditis cases, 20 (21%) of 95 pericardial disease cases, and five (6%) of 82 vasculitis cases (χ test for overall comparison between pericardial diseases, myocarditis, and vasculitis, p<0·0001).
INTERPRETATION - Treatment with ICIs can lead to severe and disabling inflammatory cardiovascular irAEs soon after commencement of therapy. In addition to life-threatening myocarditis, these toxicities include pericardial diseases and temporal arteritis with a risk of blindness. These events should be considered in patient care and in combination clinical trial designs (ie, combinations of different immunotherapies as well as immunotherapies and chemotherapy).
FUNDING - The Cancer Institut Thématique Multi-Organisme of the French National Alliance for Life and Health Sciences (AVIESAN) Plan Cancer 2014-2019; US National Cancer Institute, National Institutes of Health; the James C. Bradford Jr. Melanoma Fund; and the Melanoma Research Foundation.
Copyright © 2018 Elsevier Ltd. All rights reserved.
Isolevuglandins are 4-ketoaldehydes formed by peroxidation of arachidonic acid. Isolevuglandins react rapidly with primary amines including the lysyl residues of proteins to form irreversible covalent modifications. This review highlights evidence for the potential role of isolevuglandin modification in the disease processes, especially atherosclerosis, and some of the tools including small molecule dicarbonyl scavengers utilized to assess their contributions to disease.
Copyright © 2018. Published by Elsevier Inc.
Cancer therapies can cause a variety of cardiac toxicities, including ischemia, cardiomyopathy, heart failure, myocarditis, arrhythmias, vascular disease, hypertension, and hyperlipidemia. Addressing cardiovascular risk at baseline, before initiating therapy, during cancer treatment, and in the survivorship period is imperative. It may be useful to risk stratify individuals with cardiovascular risk factors using biomarkers or imaging before they receive potentially cardiotoxic therapies. Additionally, new guidelines recommend cardiac imaging with echocardiography in the survivorship period 6 to 12 months after completing cancer therapy for these high-risk individuals. Close collaboration between cardiology and oncology in both clinical practice and future research is essential.
Immune checkpoint inhibitors are a new class of anticancer therapies that amplify T-cell-mediated immune responses against cancer cells. Immune checkpoint inhibitors have shown important benefits in phase 3 trials, and several agents have been approved for specific malignancies. Although adverse events from immune checkpoint inhibitors are a common occurrence, cardiotoxic effects are uncommon, but are often serious complications with a relatively high mortality. Most cardiotoxic effects appear to be inflammatory in nature. Clinical assessment of a combination of biomarkers, electrocardiography, cardiac imaging, and endomyocardial biopsy can be used to confirm a possible diagnosis. In this Review, we discuss the epidemiology of immune checkpoint inhibitor-mediated cardiotoxic effects, as well as their clinical presentation, subtypes, risk factors, pathophysiology, and clinical management, including the introduction of a new surveillance strategy.
Copyright © 2018 Elsevier Ltd. All rights reserved.
The completion of the Human Genome Project has unleashed a wealth of human genomics information, but it remains unclear how best to implement this information for the benefit of patients. The standard approach of biomedical research, with researchers pursuing advances in knowledge in the laboratory and, separately, clinicians translating research findings into the clinic as much as decades later, will need to give way to new interdisciplinary models for research in genomic medicine. These models should include scientists and clinicians actively working as teams to study patients and populations recruited in clinical settings and communities to make genomics discoveries-through the combined efforts of data scientists, clinical researchers, epidemiologists, and basic scientists-and to rapidly apply these discoveries in the clinic for the prediction, prevention, diagnosis, prognosis, and treatment of cardiovascular diseases and stroke. The highly publicized US Precision Medicine Initiative, also known as All of Us, is a large-scale program funded by the US National Institutes of Health that will energize these efforts, but several ongoing studies such as the UK Biobank Initiative; the Million Veteran Program; the Electronic Medical Records and Genomics Network; the Kaiser Permanente Research Program on Genes, Environment and Health; and the DiscovEHR collaboration are already providing exemplary models of this kind of interdisciplinary work. In this statement, we outline the opportunities and challenges in broadly implementing new interdisciplinary models in academic medical centers and community settings and bringing the promise of genomics to fruition.
© 2018 American Heart Association, Inc.
BACKGROUND - Pulmonary transit time (PTT) obtained from contrast echocardiography is a marker of global cardiopulmonary function. Pulmonary blood volume (PBV), derived from PTT, may be a noninvasive surrogate for left-sided filling pressures, such as pulmonary artery wedge pressure (PAWP). We sought to assess the relationship between PBV obtained from contrast echocardiography and PAWP.
METHODS - Participants were adult survivors of childhood cancer that had contrast echocardiography performed nearly simultaneously with right-heart catheterization. PTT was derived from time-intensity curves of contrast passage through the right ventricle (RV) and left atrium (LA). PBV relative to overall stroke volume (rPBV) was estimated from the product of PTT and heart rate during RV-LA transit. PAWP was obtained during standard right-heart catheterization. The Spearman correlation coefficient was used to assess the relationship between rPBV and PAWP.
RESULTS - The study population consisted of 7 individuals who had contrast echocardiography and right-heart catheterization within 3 hours of each other. There was a wide range of right atrial (1-17 mm Hg), mean pulmonary artery (18-42 mm Hg), and PAW pressures (4-26 mm Hg) as well as pulmonary vascular resistance (<1-6 Wood Units). We observed a statistically significant correlation between rPBV and PAWP (r = .85; P = .02).
CONCLUSION - Relative PBV derived from contrast echocardiography correlates with PAWP. If validated in larger studies, rPBV could potentially be used as an alternative to invasively determine left-sided filling pressure.
© 2018 Wiley Periodicals, Inc.
OBJECTIVE - A prolonged QTc (LQT) is a surrogate for the risk of torsade de pointes (TdP). QTc interval duration is influenced by sex hormones: oestradiol prolongs and testosterone shortens QTc. Drugs used in the treatment of breast cancer have divergent effects on hormonal status.
METHODS - We performed a disproportionality analysis using the European database of suspected adverse drug reaction (ADR) reports to evaluate the reporting OR (ROR χ) of LQT, TdP and ventricular arrhythmias associated with selective oestrogen receptor modulators (SERMs: tamoxifen and toremifene) as opposed to aromatase inhibitors (AIs: anastrozole, exemestane and letrozole). When the proportion of an ADR is greater in patients exposed to a drug (SERMs) compared with patients exposed to control drug (AIs), this suggests an association between the specific drug and the reaction and is a potential signal for safety. Clinical and demographic characterisation of patients with SERMs-induced LQT and ventricular arrhythmias was performed.
RESULTS - SERMs were associated with higher proportion of LQT reports versus AIs (26/8318 vs 11/14851, ROR: 4.2 (2.11-8.55), p<0.001). SERMs were also associated with higher proportion of TdP and ventricular arrhythmia reports versus AIs (6/8318 vs 2/14851, ROR: 5.4 (1.29-26.15), p:0.02; 16/8318 vs 12/14851, ROR: 2.38 (1.15-4.94), p:0.02, respectively). Mortality was 38% in patients presenting ventricular arrhythmias associated with SERMs.
CONCLUSIONS - SERMs are associated with more reports of drug-induced LQT, TdP and ventricular arrhythmias compared with AIs. This finding is consistent with oestradiol-like properties of SERMs on the heart as opposed to effects of oestrogen deprivation and testosterone increase induced by AIs.
TRIAL REGISTRATION NUMBER - NCT03259711.
© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Drug-induced cardiovascular complications are the most common adverse drug events and account for the withdrawal or severe restrictions on the use of multitudinous postmarketed drugs. In this study, we developed new in silico models for systematic identification of drug-induced cardiovascular complications in drug discovery and postmarketing surveillance. Specifically, we collected drug-induced cardiovascular complications covering the five most common types of cardiovascular outcomes (hypertension, heart block, arrhythmia, cardiac failure, and myocardial infarction) from four publicly available data resources: Comparative Toxicogenomics Database, SIDER, Offsides, and MetaADEDB. Using these databases, we developed a combined classifier framework through integration of five machine-learning algorithms: logistic regression, random forest, k-nearest neighbors, support vector machine, and neural network. The totality of models included 180 single classifiers with area under receiver operating characteristic curves (AUC) ranging from 0.647 to 0.809 on 5-fold cross-validations. To develop the combined classifiers, we then utilized a neural network algorithm to integrate the best four single classifiers for each cardiovascular outcome. The combined classifiers had higher performance with an AUC range from 0.784 to 0.842 compared to single classifiers. Furthermore, we validated our predicted cardiovascular complications for 63 anticancer agents using experimental data from clinical studies, human pluripotent stem cell-derived cardiomyocyte assays, and literature. The success rate of our combined classifiers reached 87%. In conclusion, this study presents powerful in silico tools for systematic risk assessment of drug-induced cardiovascular complications. This tool is relevant not only in early stages of drug discovery but also throughout the life of a drug including clinical trials and postmarketing surveillance.
PURPOSE OF REVIEW - The goal of this review is to highlight the potential of induced pluripotent stem cell (iPSC)-based modeling as a tool for studying human cardiovascular diseases. We present some of the current cardiovascular disease models utilizing genome editing and patient-derived iPSCs.
RECENT FINDINGS - The incorporation of genome-editing and iPSC technologies provides an innovative research platform, providing novel insight into human cardiovascular disease at molecular, cellular, and functional level. In addition, genome editing in diseased iPSC lines holds potential for personalized regenerative therapies. The study of human cardiovascular disease has been revolutionized by cellular reprogramming and genome editing discoveries. These exceptional technologies provide an opportunity to generate human cell cardiovascular disease models and enable therapeutic strategy development in a dish. We anticipate these technologies to improve our understanding of cardiovascular disease pathophysiology leading to optimal treatment for heart diseases in the future.