How does deep learning/machine learning perform in comparison to radiologists in distinguishing glioblastomas (or grade IV astrocytomas) from primary CNS lymphomas?: a meta-analysis and systematic review

BACKGROUND

Several studies have been published comparing deep learning (DL)/machine learning (ML) to radiologists in differentiating PCNSLs from GBMs with equivocal results. We aimed to perform this meta-analysis to evaluate the diagnostic accuracy of ML/DL versus radiologists in classifying PCNSL versus GBM using MRI.

METHODOLOGY

The study was performed in accordance with PRISMA guidelines. Data was extracted and interpreted by two researchers with 12 and 23 years' experience, respectively, and QUADAS-2 tool was used for quality and risk-bias assessment. We constructed contingency tables to derive sensitivity, specificity accuracy, summary receiver operating characteristic (SROC) curve, and the area under the curve (AUC).

RESULTS

Our search identified 11 studies, of which 8 satisfied our inclusion criteria and restricted the analysis in each study to reporting the model showing highest accuracy, with a total sample size of 1159 patients. The random effects model showed a pooled sensitivity of 0.89 [95% CI:0.84-0.92] for ML and 0.82 [95% CI:0.76-0.87] for radiologists. Pooled specificity was 0.88 [95% CI: 0.84-0.91] for ML and 0.90 [95% CI: 0.81-0.95] for radiologists. Pooled accuracy was 0.88 [95% CI: 0.86-0.90] for ML and 0.86 [95% CI: 0.78-0.91] for radiologists. Pooled AUC of ML was 0.94 [95% CI:0.92-0.96]and for radiologists, it was 0.90 [95% CI: 0.84-0.93].

CONCLUSIONS

MRI-based ML/DL techniques can complement radiologists to improve the accuracy of classifying GBMs from PCNSL, possibly reduce the need for a biopsy, and avoid any unwanted neurosurgical resection of a PCNSL.

Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic.

METHODS

The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic.

FINDINGS

Global DALYs increased from 2·63 billion (95% UI 2·44-2·85) in 2010 to 2·88 billion (2·64-3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7-17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8-6·3) in 2020 and 7·2% (4·7-10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0-234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7-198·3]), neonatal disorders (186·3 million [162·3-214·9]), and stroke (160·4 million [148·0-171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3-51·7) and for diarrhoeal diseases decreased by 47·0% (39·9-52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54-1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5-9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0-19·8]), depressive disorders (16·4% [11·9-21·3]), and diabetes (14·0% [10·0-17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7-27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6-63·6) in 2010 to 62·2 years (59·4-64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6-2·9) between 2019 and 2021.

INTERPRETATION

Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades.

FUNDING

Bill & Melinda Gates Foundation.

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.

METHODS

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.

FINDINGS

The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.

INTERPRETATION

Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere.

FUNDING

Bill & Melinda Gates Foundation.

Examining the interplay between cardiovascular disease and cancer incidence: Data from NHANES III and continuous

Introduction

This study aimed to investigate the relationship between risk factors of cancer among individuals with existing cardiovascular disease (CVD).

Methods

The analysis included 438 and 2100 CVD patients aged 65+ from NHANES-III and Continuous datasets, respectively. Competing risk models with subdistribution hazards ratio (aHR) were used to identify risk factors.

Results

Females in NHANES-III had lower cancer risk (aHR 0.39, P = 0.001) compared to males. Poor physical activity was associated with increased cancer risk in both datasets (aHR 2.59 in NHANES-III, aHR 1.59 in Continuous). In NHANES-Continuous, age (aHR 1.07, P < 0.001) and current smoking (aHR 2.55, P = 0.001) also showed a significant association with developing cancer. No other factors investigated showed significant associations.

Discussion

This study highlights the interplay between traditional risk factors and the elevated risk of cancer in CVD patients. Further research with larger samples and wider age ranges is needed to solidify these findings and inform intervention strategies.

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020-21 COVID-19 pandemic period.

METHODS

22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution.

FINDINGS

Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5-65·1] decline), and increased during the COVID-19 pandemic period (2020-21; 5·1% [0·9-9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98-5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50-6·01) in 2019. An estimated 131 million (126-137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7-17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8-24·8), from 49·0 years (46·7-51·3) to 71·7 years (70·9-72·5). Global life expectancy at birth declined by 1·6 years (1·0-2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67-8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4-52·7]) and south Asia (26·3% [9·0-44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations.

INTERPRETATION

Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic.

FUNDING

Bill & Melinda Gates Foundation.

Performance of the pooled cohort equations in cancer survivors: the Atherosclerosis Risk in Communities study

BACKGROUND

Cancer survivors may have elevated atherosclerotic cardiovascular disease (ASCVD) risk. Therefore, we tested how accurately the American College of Cardiology/American Heart Association 2013 pooled cohort equations (PCEs) predict 10-year ASCVD risk in cancer survivors.

OBJECTIVES

To estimate the calibration and discrimination of the PCEs in cancer survivors compared to non-cancer participants in the Atherosclerosis Risk in Communities (ARIC) study.

METHODS

We evaluated the PCEs' performance among 1244 cancer survivors and 3849 cancer-free participants who were free of ASCVD at the start of follow-up. Each cancer survivor was incidence-density matched with up to five controls by age, race, sex, and study center. Follow-up began at the first study visit at least 1 year after the diagnosis date of the cancer survivor and finished at the ASCVD event, death, or end of follow-up. Calibration and discrimination were assessed and compared between cancer survivors and cancer-free participants.

RESULTS

Cancer survivors had higher PCE-predicted risk, at 26.1%, compared with 23.1% for cancer-free participants. There were 110 ASCVD events in cancer survivors and 332 ASCVD events in cancer-free participants. The PCEs overestimated ASCVD risk in cancer survivors and cancer-free participants by 45.6% and 47.4%, respectively, with poor discrimination in both groups (C-statistic for cancer survivors = 0.623; for cancer-free participants, C = 0.671).

CONCLUSIONS

The PCEs overestimated ASCVD risk in all participants. The performance of the PCEs was similar in cancer survivors and cancer-free participants.

IMPLICATIONS FOR CANCER SURVIVORS

Our findings suggest that ASCVD risk prediction tools tailored to survivors of adult cancers may not be needed.

Advancing the care of individuals with cancer through innovation & technology: Proceedings from the cardiology oncology innovation summit 2020 and 2021

As cancer therapies increase in effectiveness and patients' life expectancies improve, balancing oncologic efficacy while reducing acute and long-term cardiovascular toxicities has become of paramount importance. To address this pressing need, the Cardiology Oncology Innovation Network (COIN) was formed to bring together domain experts with the overarching goal of collaboratively investigating, applying, and educating widely on various forms of innovation to improve the quality of life and cardiovascular healthcare of patients undergoing and surviving cancer therapies. The COIN mission pillars of innovation, collaboration, and education have been implemented with cross-collaboration among academic institutions, private and public establishments, and industry and technology companies. In this report, we summarize proceedings from the first two annual COIN summits (inaugural in 2020 and subsequent in 2021) including educational sessions on technological innovations for establishing best practices and aligning resources. Herein, we highlight emerging areas for innovation and defining unmet needs to further improve the outcome for cancer patients and survivors of all ages. Additionally, we provide actionable suggestions for advancing innovation, collaboration, and education in cardio-oncology in the digital era.

Calcium channel blockers and clinical outcomes in patients with continuous-flow left ventricular assist devices

AIMS

Current guidelines suggest calcium channel blockers (CCBs) as the second or third option for blood pressure management in patients with left ventricular assist device (LVAD). However, the clinical outcomes of patients with LVAD who receive CCBs remain unclear. Our study aims to analyse the association of CCBs with clinical outcomes in patients after LVAD implantation.

METHODS AND RESULTS

This is a retrospective analysis based on the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) from 2006 to 2017, and adult patients who were alive with LVAD and CCB treatment information at 6 months after implantation were included. Among 10 717 patients, 1369 received CCBs 6 months after implantation, and there was an increasing trend of CCB use after LVAD. Patients receiving CCB therapy at 6 months had a similar 5 year survival rate to those not receiving CCB [49.6%, 95% confidence interval (CI): 47.5-51.7% vs. 51.1%, 95% CI: 45.3-56.7%]. In both Cox and competing risk regressions after adjusting for confounding factors, CCB treatment at 6 months after implantation was not associated with long-term mortality [hazard ratio (HR): 1.03, 95% CI: 0.91-1.17, P = 0.624 and subdistribution HR (SHR): 1.07, 95% CI: 0.95-1.22, P = 0.260]. Consistently, in time-varying models, CCB treatment was not linked to long-term mortality (HR: 0.97, 95% CI: 0.87-1.09, P = 0.682 and SHR: 1.05, 95% CI: 0.94-1.18, P = 0.359). This null association remained in subgroup analysis according to device strategy and propensity-matching analyses. Neurological dysfunction, stroke, bleeding, rehospitalization, and renal dysfunction were more likely to occur among those with CCB when compared with those without CCB treatment.

CONCLUSIONS

In patients with LVAD, CCB therapy fails to show benefits in long-term survival and is associated with increased incidences of neurological dysfunction, bleeding, renal dysfunction, and rehospitalization.

Incident Atrial Fibrillation and Survival Outcomes in Esophageal Cancer following Radiotherapy

PURPOSE

Radiation therapy (RT) associates with long-term cardiotoxicity. In preclinical models, RT exposure induces early cardiotoxic arrhythmias including atrial fibrillation (AF). Yet, whether this occurs in patients is unknown.

METHODS AND MATERIALS

Leveraging a large cohort of consecutive patients with esophageal cancer treated with thoracic RT from 2007 to 2019, we assessed incidence and outcomes of incident AF. Secondary outcomes included major adverse cardiovascular events (MACE), defined as AF, heart failure, ventricular arrhythmias, and sudden death, by cardiac RT dose. We also assessed the relationship between AF development and progression-free and overall survival. Observed incident AF rates were compared with Framingham predicted rates, and absolute excess risks were estimated. Multivariate regression was used to define the relationship between clinical and RT measures, and outcomes. Differences in outcomes, by AF status, were also evaluated via 30-day landmark analysis. Furthermore, we assessed the effect of cardiac substructure RT dose (eg, left atrium, LA) on the risk of post RT-related outcomes.

RESULTS

Overall, from 238 RT treated patients with esophageal cancer, 21.4% developed incident AF, and 33% developed MACE with the majority (84%) of events occurring ≤2 years of RT initiation (median time to AF, 4.1 months). Cumulative incidence of AF and MACE at 1 year was 19.5%, and 25.7%, respectively; translating into an observed incident AF rate of 824 per 10,000 person-years, compared with the Framingham predicted rate of 92 (relative risk, 8.96; P < .001, absolute excess risk 732). Increasing LA dose strongly associated with incident AF (P = .001); and those with AF saw worse disease progression (hazard ratio, 1.54; P = .03). In multivariate models, outside of traditional cancer-related factors, increasing RT dose to the LA remained associated with worse overall survival.

CONCLUSIONS

Among patients with esophageal cancer, radiation therapy increases AF risk, and associates with worse long-term outcomes.

Association between cancer, CHA2DS2VASc risk, and in-hospital ischaemic stroke in patients hospitalized for atrial fibrillation

BACKGROUND

Atrial fibrillation (AF) is commonly encountered in cancer patients. We investigated the CHA2DS2VASc score, and its association with in-hospital ischaemic stroke in patients with cancer who were hospitalized for AF.

METHODS AND RESULTS

Using the United States National Inpatient Sample, all hospitalizations with principal diagnosis of AF between October 2015 and December 2018 were stratified by cancer diagnosis, type, and CHA2DS2VASc risk categories (low risk, low-moderate risk, moderate-high risk). In-hospital ischaemic stroke and its association with the CHA2DS2VASc risk score was assessed across the groups using hierarchical multivariable logistic regression with adjusted odds ratios (aOR) and 95% confidence intervals (95% CI). Discrimination of CHA2DS2VASc score for in-hospital ischaemic stroke was evaluated with Receiver Operating Characteristic and Area Under the Curve (AUC). Among 1 341 870 included hospitalizations, 71 965 (5.4%) had comorbid cancer. Cancer patients had a higher proportion of moderate-high CHA2DS2VASc risk compared with their non-cancer counterparts (86.5% vs. 82.3%, P < 0.001). Compared with their low CHA2DS2VASc risk counterparts, cancer patients in low-moderate and moderate-high risk scores had similar odds of developing stroke (aOR 1.28 95% CI 0.22-7.63 and aOR 1.78 95% CI 0.41-7.66, respectively). The CHA2DS2VASc risk score had poor discrimination for ischaemic stroke in the cancer group (AUC 0.538 95% CI 0.477-0.598).

CONCLUSION

Cancer patients with AF have high CHA2DS2VASc risk. Discrimination of CHA2DS2VASc for ischaemic stroke is lower in cancer than non-cancer patients, and CHA2DS2VASc may not be adequate in determining ischaemic risk in cancer population.

Chemotherapy in Pregnancy: Assessing the Safety of Adriamycin Administration in Pregnancy Complicated by Breast Cancer

Pregnancy-associated breast cancer is challenging to treat. Treatment with chemotherapeutic agents such as anthracyclines poses a risk of cardiotoxicity, despite being considered safe after the second trimester of pregnancy. Management requires multidisciplinary comanagement with cardio-obstetrics, cardiology-oncology, maternal-fetal medicine, and oncology.

Integrative multiomics analysis of neointima proliferation in human saphenous vein: implications for bypass graft disease

Introduction

Human saphenous veins (SV) are widely used as grafts in coronary artery bypass (CABG) surgery but often fail due to neointima proliferation (NP). NP involves complex interplay between vascular smooth muscle cells (VSMC) and fibroblasts. Little is known, however, regarding the transcriptomic and proteomic dynamics of NP. Here, we performed multi-omics analysis in an ex vivo tissue culture model of NP in human SV procured for CABG surgery.

Methods and results

Histological examination demonstrated significant elastin degradation and NP (indicated by increased neointima area and neointima/media ratio) in SV subjected to tissue culture. Analysis of data from 73 patients suggest that the process of SV adaptation and NP may differ according to sex and body mass index. RNA sequencing confirmed upregulation of pro-inflammatory and proliferation-related genes during NP and identified novel processes, including increased cellular stress and DNA damage responses, which may reflect tissue trauma associated with SV harvesting. Proteomic analysis identified upregulated extracellular matrix-related and coagulation/thrombosis proteins and downregulated metabolic proteins. Spatial transcriptomics detected transdifferentiating VSMC in the intima on the day of harvesting and highlighted dynamic alterations in fibroblast and VSMC phenotype and behavior during NP. Specifically, we identified new cell subpopulations contributing to NP, including SPP1 + , LGALS3 + VSMC and MMP2 + , MMP14 + fibroblasts.

Conclusion

Dynamic alterations of gene and protein expression occur during NP in human SV. Identification of the human-specific molecular and cellular mechanisms may provide novel insight into SV bypass graft disease.

CT Based Tumor Radiomics with Machine Learning Classifiers for Molecular Subtyping of Diffuse Large B Cell Lymphoma

PURPOSE/OBJECTIVE(S)

Diffuse large B-cell lymphoma (DLBL) has been classified into two distinct molecular subtypes based on their cell of origin- namely germinal center B-cell-like (GCB) and activated B-cell-subtype (ABC) based on Han's algorithm. These two entities are also prognostically distinct. We assessed CT based tumor radiomic features using machine learning classifiers to distinguish the two molecular subtypes.

MATERIALS/METHODS

One hundred one patients were accrued in the study after institutional ethics committee approval. GCB subtype was diagnosed in 59 while 42 patients were ABC subtype. Lesion with maximum SUV was delineated using a semi-automated segmentation tool (3D slicer) and radiomic features were extracted using Pyradiomics. A total of 1030 features were extracted including Shape features, first, second, third, higher order and wavelet-based features. Recursive feature elimination was used for feature selection and optimal 10 features were selected. Five machine learning (ML) tools were used to build a model to sub- classify the two molecular subtypes. (Table -1) Model performance was assessed using Accuracy, Precision, Recall, F1 score and Area under curve of receiver operating characteristic curve. The models were constructed by two methods.1) A 5-fold internal cross validation strategy & 2) splitting the data into training (70%) and validation set (30%).

RESULTS

Recursive feature elimination using a random forest algorithm method was used to select 7 radiomic features. These 7 features were then used to build the model using the 5 ML classifiers. Of the five classifiers, Random Forest Classifier (RFC) using a 70:30 training: test strategy was the best performer among all the ML models, with the highest accuracy of 80%, AUC of 0.87, recall(sensitivity), f1score(specificity) & precision (Positive Predictive value; PPV) or precision of 82% respectively. When an internal 5-fold cross validation strategy was used, RFC again performed better than other ML classifiers with an accuracy of 75%, AUC of 0.80, recall of 79%, PPV of 77% and specificity of 79%.

CONCLUSION

The machine-learning based Radiomics features extracted from pre-treatment CT images can provide a simple and non-invasive method for the prediction of DLBL molecular subtypes with favorable predictive accuracy. The Random Forest Classifier was the most accurate in distinguishing GCB subtype from the ABC subtype.

Developing a Clinical Cardio-Oncology Program and the Building Blocks for Success: JACC: CardioOncology How To

•Cardio-oncology programs are necessary to provide optimal cardiovascular care to cancer patients and survivors.•Focus on developing a clear vision and mission-successful programs must be tailored to an organization's unique landscape.•Fostering partnerships with cardiologists and oncologists to provide high-quality patient-centered care is crucial.•Patience is essential-program development takes time, but success can be achieved.

Global Cardio Oncology Registry (G-COR): Registry Design, Primary Objectives, and Future Perspectives of a Multicenter Global Initiative

BACKGROUND

Global collaboration in cardio-oncology is needed to understand the prevalence of cancer therapy-related cardiovascular toxicity in different risk groups, practice settings, and geographic locations. There are limited data on the socioeconomic and racial/ethnic disparities that may impact access to care and outcomes. To address these gaps, we established the Global Cardio-Oncology Registry, a multinational, multicenter prospective registry.

METHODS

We assembled cardiologists and oncologists from academic and community settings to collaborate in the first Global Cardio-Oncology Registry. Subsequently, a survey for site resources, demographics, and intention to participate was conducted. We designed an online data platform to facilitate this global initiative.

RESULTS

A total of 119 sites responded to an online questionnaire on their practices and main goals of the registry: 49 US sites from 23 states and 70 international sites from 5 continents indicated a willingness to participate in the Global Cardio-Oncology Registry. Sites were more commonly led by cardiologists (85/119; 72%) and were more often university/teaching (81/119; 68%) than community based (38/119; 32%). The average number of cardio-oncology patients treated per month was 80 per site. The top 3 Global Cardio-Oncology Registry priorities in cardio-oncology care were breast cancer, hematologic malignancies, and patients treated with immune checkpoint inhibitors. Executive and scientific committees and specific committees were established. A pilot phase for breast cancer using Research Electronic Data Capture Cloud platform recently started patient enrollment.

CONCLUSIONS

We present the structure for a global collaboration. Information derived from the Global Cardio-Oncology Registry will help understand the risk factors impacting cancer therapy-related cardiovascular toxicity in different geographic locations and therefore contribute to reduce access gaps in cardio-oncology care. Risk calculators will be prospectively derived and validated.

Social Determinants of Health Data Improve the Prediction of Cardiac Outcomes in Females with Breast Cancer

Cardiovascular disease is the leading cause of mortality among breast cancer (BC) patients aged 50 and above. Machine Learning (ML) models are increasingly utilized as prediction tools, and recent evidence suggests that incorporating social determinants of health (SDOH) data can enhance its performance. This study included females ≥ 18 years diagnosed with BC at any stage. The outcomes were the diagnosis and time-to-event of major adverse cardiovascular events (MACEs) within two years following a cancer diagnosis. Covariates encompassed demographics, risk factors, individual and neighborhood-level SDOH, tumor characteristics, and BC treatment. Race-specific and race-agnostic Extreme Gradient Boosting ML models with and without SDOH data were developed and compared based on their C-index. Among 4309 patients, 11.4% experienced a 2-year MACE. The race-agnostic models exhibited a C-index of 0.78 (95% CI 0.76-0.79) and 0.81 (95% CI 0.80-0.82) without and with SDOH data, respectively. In non-Hispanic Black women (NHB; n = 765), models without and with SDOH data achieved a C-index of 0.74 (95% CI 0.72-0.76) and 0.75 (95% CI 0.73-0.78), respectively. Among non-Hispanic White women (n = 3321), models without and with SDOH data yielded a C-index of 0.79 (95% CI 0.77-0.80) and 0.79 (95% CI 0.77-0.80), respectively. In summary, including SDOH data improves the predictive performance of ML models in forecasting 2-year MACE among BC females, particularly within NHB.

Vascular Inflammation, Cancer, and Cardiovascular Diseases

PURPOSE OF REVIEW

Cancer and cardiovascular disease are among the leading causes of morbidity and mortality in the USA. Cancer and cardiovascular disease have inflammatory underpinnings that have been associated with both the development and progression of these disease states.

RECENT FINDINGS

Inflammatory signaling has been found to be a critical event in both cardiovascular disease and cancer formation and progression. Further, many chemotherapeutic agents potentiate inflammation exacerbating existing cardiovascular disease or leading to its presence. The exact mechanisms of these interactions remain poorly understood. The proinflammatory milieu observed in both cancer and cardiovascular disease likely plays an important role in the development and potentiation of both conditions. Further evaluation of this relationship will be critical in the development of new diagnostic and therapeutic modalities.

Immune checkpoint inhibitor-associated myocarditis and fulminant type I diabetes in a patient with metastatic non-small cell lung cancer

A woman in her mid-60s presented to the hospital due to a history of nausea, vomiting, shortness of breath, dyspnoea on exertion and polyuria. She was receiving medical therapy for advanced non-small cell lung cancer and recently initiated immune checkpoint inhibitor (ICI) immunotherapy. Investigations revealed lab results consistent with diabetic ketoacidosis (DKA), elevated cardiac biomarkers, multiple cardiac arrhythmias and reduced ejection fraction on transthoracic echocardiogram. Cardiac catheterisation showed non-obstructive coronary arteries.The patient was diagnosed with an ICI-associated myocarditis and type I diabetes due to recent initiation of the ICI durvalumab. She was treated with the institutional DKA protocol and received corticosteroid therapy for drug toxicity according to guidelines. She was discharged with marked improvement in symptoms. The patient had good recovery after discharge with further investigations showing improvement in her cardiac ejection fraction on cardiac MRI. She remains on medical therapy with an insulin regimen for diabetes management.

Geographical Patterns and Risk Factor Association of Cardio-Oncology Mortality in the United States

Cardio-oncology mortality (COM) is a complex issue that is compounded by multiple factors that transcend a depth of socioeconomic, demographic, and environmental exposures. Although metrics and indexes of vulnerability have been associated with COM, advanced methods are required to account for the intricate intertwining of associations. This cross-sectional study utilized a novel approach that combined machine learning and epidemiology to identify high-risk sociodemographic and environmental factors linked to COM in United States counties. The study consisted of 987,009 decedents from 2,717 counties, and the Classification and Regression Trees model identified 9 county socio-environmental clusters that were closely associated with COM, with a 64.1% relative increase across the spectrum. The most important variables that emerged from this study were teen birth, pre-1960 housing (lead paint indicator), area deprivation index, median household income, number of hospitals, and exposure to particulate matter air pollution. In conclusion, this study provides novel insights into the socio-environmental drivers of COM and highlights the importance of utilizing machine learning approaches to identify high-risk populations and inform targeted interventions for reducing disparities in COM.

Hepatocyte-specific disruption of soluble epoxide hydrolase attenuates abdominal aortic aneurysm formation: novel role of the liver in aneurysm pathogenesis

Introduction

Inflammation is a key pathogenic feature of abdominal aortic aneurysm (AAA). Soluble epoxide hydrolase (sEH) is a pro-inflammatory enzyme that converts cytochrome P450-derived epoxides of fatty acids to the corresponding diols, and pharmacological inhibition of sEH prevented AAA formation. Both cytochrome P450 enzymes and sEH are highly expressed in the liver. Here, we investigated the role of hepatic sEH in AAA using a selective pharmacological inhibitor of sEH and hepatocyte-specific Ephx2 (which encodes sEH gene) knockout (KO) mice in two models of AAA [angiotensin II (AngII) infusion and calcium chloride (CaCl 2 ) application].

Methods and results

sEH expression and activity were strikingly higher in mouse liver compared with aorta and further increased the context of AAA, in conjunction with elevated expression of the transcription factor Sp1 and the epigenetic regulator Jarid1b, which have been reported to positively regulate sEH expression. Pharmacological sEH inhibition, or liver-specific sEH disruption, achieved by crossing sEH floxed mice with albumin-cre mice, prevented AAA formation in both models, concomitant with reduced expression of hepatic sEH as well as complement factor 3 (C3) and serum amyloid A (SAA), liver-derived factors linked to AAA formation. Moreover, sEH antagonism markedly reduced C3 and SAA protein accumulation in the aortic wall. Co-incubation of liver ex vivo with aneurysm-prone aorta resulted in induction of sEH in the liver, concomitant with upregulation of Sp1, Jarid1b, C3 and SAA gene expression, suggesting that the aneurysm-prone aorta secretes factors that activate sEH and downstream inflammatory signaling in the liver. Using an unbiased proteomic approach, we identified a number of dysregulated proteins [ e.g., plastin-2, galectin-3 (gal-3), cathepsin S] released by aneurysm-prone aorta as potential candidate mediators of hepatic sEH induction.

Conclusion

We provide the first direct evidence of the liver's role in orchestrating AAA via the enzyme sEH. These findings not only provide novel insight into AAA pathogenesis, but they have potentially important implications with regard to developing effective medical therapies for AAA.

Social Determinants of Health and Racial Disparities in Cardiac Events in Breast Cancer

BACKGROUND

Racial disparities have been reported for breast cancer and cardiovascular disease (CVD) outcomes. The determinants of racial disparities in CVD outcomes are not yet fully understood. We aimed to examine the impact of individual and neighborhood-level social determinants of health (SDOH) on the racial disparities in major adverse cardiovascular events (MACE; consisting of heart failure, acute coronary syndrome, atrial fibrillation, and ischemic stroke) among female patients with breast cancer.

METHODS

This 10-year longitudinal retrospective study was based on a cancer informatics platform with electronic medical record supplementation. We included women aged ≥18 years diagnosed with breast cancer. SDOH were obtained from LexisNexis, and consisted of the domains of social and community context, neighborhood and built environment, education access and quality, and economic stability. Race-agnostic (overall data with race as a feature) and race-specific machine learning models were developed to account for and rank the SDOH impact in 2-year MACE.

RESULTS

We included 4,309 patients (765 non-Hispanic Black [NHB]; 3,321 non-Hispanic white). In the race-agnostic model (C-index, 0.79; 95% CI, 0.78-0.80), the 5 most important adverse SDOH variables were neighborhood median household income (SHapley Additive exPlanations [SHAP] score [SS], 0.07), neighborhood crime index (SS = 0.06), number of transportation properties in the household (SS = 0.05), neighborhood burglary index (SS = 0.04), and neighborhood median home values (SS = 0.03). Race was not significantly associated with MACE when adverse SDOH were included as covariates (adjusted subdistribution hazard ratio, 1.22; 95% CI, 0.91-1.64). NHB patients were more likely to have unfavorable SDOH conditions for 8 of the 10 most important SDOH variables for the MACE prediction.

CONCLUSIONS

Neighborhood and built environment variables are the most important SDOH predictors for 2-year MACE, and NHB patients were more likely to have unfavorable SDOH conditions. This finding reinforces that race is a social construct.

Adverse Cardiovascular Events Associated With Cyclin-Dependent Kinase 4/6 Inhibitors in Patients With Metastatic Breast Cancer

Background Cyclin-dependent kinase (CDK) 4 and 6 inhibitors have significantly improved survival in patients with hormone receptor-positive metastatic breast cancer. There are few data regarding the epidemiology of cardiovascular adverse events (CVAEs) with these therapies. Methods and Results Using the OneFlorida Data Trust, adult patients without prior cardiovascular disease who received at least 1 CDK4/6 inhibitor were included in the analysis. CVAEs identified from International Classification of Diseases, Ninth and Tenth Revisions (ICD-9/10) codes included hypertension, atrial fibrillation(AF)/atrial flutter (AFL), heart failure/cardiomyopathy, ischemic heart disease, and pericardial disease. Competing risk analysis (Fine-Gray model) was used to determine the association between CDK4/6 inhibitor therapy and incident CVAEs. The effect of CVAEs on all-cause death was studied using Cox proportional hazard models. Propensity-weight analyses were performed to compare these patients to a cohort of patients treated with anthracyclines. A total of 1376 patients treated with CDK4/6 inhibitors were included in the analysis. CVAEs occurred in 24% (35.9 per 100 person-years). CVAEs were slightly higher in patients who received CKD4/6 inhibitors compared with anthracyclines (P=0.063), with higher death rate associated with the development of AF/AFL or cardiomyopathy/heart failure in the CDK4/6 group. The development of cardiomyopathy/heart failure and AF/AFL was associated with increased all-cause death (adjusted hazard ratio [HR], 4.89 [95% CI, 2.98-8.05]; and 5.88 [95% CI, 3.56-9.73], respectively). Conclusions CVAEs may be more common with CDK4/6 inhibitors than previously recognized, with increased death rates in these patients who develop AF/AFL or heart failure. Further research is needed to definitively determine cardiovascular risk associated with these novel anticancer treatments.

Quantitative cardiovascular magnetic resonance findings and clinical risk factors predict cardiovascular outcomes in breast cancer patients

BACKGROUND

Cardiac magnetic resonance (CMR) global longitudinal strain and circumferential strain abnormalities have been associated with left ventricular ejection fraction (LVEF) reduction and cardiotoxicity from oncologic therapy. However, few studies have evaluated the associations of strain and cardiovascular outcomes.

OBJECTIVES

To assess CMR circumferential and global longitudinal strain (GLS) correlations with cardiovascular outcomes including myocardial infarction, systolic dysfunction, diastolic dysfunction, arrhythmias and valvular disease in breast cancer patients treated with and without anthracyclines and/or trastuzumab therapy.

METHODS

Breast cancer patients with a CMR from 2013-2017 at Yale New Haven Hospital were included. Patient co-morbidities, medications, and cardiovascular outcomes were obtained from chart review. Biostatistical analyses, including Pearson correlations, competing risk regression model, and competing risk survival curves comparing the two groups were analyzed.

RESULTS

116 breast cancer with CMRs were included in our analysis to assess differences between Anthracycline/Trastuzumab (AT) (62) treated versus non anthracycline/trastuzumab (NAT) (54) treated patients in terms of imaging characteristics and outcomes. More AT patients 17 (27.4%) developed systolic heart failure compared to the NAT group 6 (10.9%), p = 0.025. Statin use was associated with a significant reduction in future arrhythmias (HR 0.416; 95% CI 0.229-0.755, p = 0.004). In a sub-group of 13 patients that underwent stress CMR, we did not find evidence of microvascular dysfunction by sub-endocardial/sub-epicardial myocardial perfusion index ratio after adjusting for ischemic heart disease.

CONCLUSIONS

In our study, CMR detected signs of subclinical cardiotoxicity such as strain abnormalities despite normal LV function and abnormal circumferential strain was associated with adverse cardiovascular outcomes such as valvular disease and systolic heart failure. Thus, CMR is an important tool during and after cancer treatment to identity and prognosticate cancer treatment-related cardiotoxicity.

Racial and Ethnic Differences in Cardiac Surveillance Evaluation of Patients Treated With Anthracycline-Based Chemotherapy

Background Anthracyclines remain a key treatment for many malignancies but can increase the risk of heart failure or cardiomyopathy. Specific guidelines recommend echocardiography and serum cardiac biomarkers such as BNP (B-type natriuretic peptide) or NT-proBNP (N-terminal proBNP) evaluation before and 6 to 12 months after treatment. Our objective was to evaluate associations between racial and ethnic groups in cardiac surveillance of survivors of cancer after exposure to anthracyclines. Methods and Results Adult patients in the OneFlorida Consortium without prior cardiovascular disease who received at least 2 cycles of anthracyclines were included in the analysis. Multivariable logistic regression was performed to estimate the odds ratios (ORs) and 95% CIs for receiving cardiac surveillance at baseline before anthracycline therapy, 6 months after, and 12 months after anthracycline exposure among different racial and ethnic groups. Among the entire cohort of 5430 patients, 63.4% had a baseline echocardiogram, with 22.3% receiving an echocardiogram at 6 months and 25% at 12 months. Non-Hispanic Black (NHB) patients had a lower likelihood of receiving a baseline echocardiogram than Non-Hispanic White (NHW) patients (OR, 0.75 [95% CI, 0.63-0.88]; P=0.0006) or any baseline cardiac surveillance (OR, 0.76 [95% CI, 0.64-0.89]; P=0.001). Compared with NHW patients, Hispanic patients received significantly less cardiac surveillance at the 6-month (OR, 0.84 [95% CI, 0.72-0.98]; P=0.03) and 12-month (OR, 0.85 [95% CI, 0.74-0.98]; P=0.03) time points, respectively. Conclusions There were significant racial and ethnic differences in cardiac surveillance among survivors of cancer at baseline and following anthracycline-based treatment in NHB and Hispanic cohorts. Health care providers need to be cognizant of these social inequities and initiate efforts to ensure recommended cardiac surveillance occurs following anthracyclines.

Cardiovascular Magnetic Resonance Imaging in Patients With Ibrutinib-Associated Cardiotoxicity

Importance

Ibrutinib has been associated with serious cardiotoxic arrhythmias. In preclinical models, these events are paralleled or proceeded by diffuse myocardial injury (inflammation and fibrosis). Yet whether this is seen in patients or has implications for future cardiotoxic risk is unknown.

Objective

To assess the incidence and outcomes of myocardial injury among patients with ibrutinib-related cardiotoxicity.

Design, Setting, and Participants

This cohort study included consecutive patients treated with ibrutinib from 2012 to 2019, phenotyped using cardiovascular magnetic resonance (CMR) from a large US Comprehensive Cancer Center registry.

Exposures

Ibrutinib treatment for cancer control.

Main Outcomes and Measures

The primary outcome was the presence of late gadolinium enhancement (LGE) fibrosis. The secondary outcome was the occurrence of major adverse cardiac events (MACE), defined as atrial fibrillation, heart failure, symptomatic ventricular arrhythmias, and sudden death of probable or definite ibrutinib association after CMR. We also assessed parametric-mapping subclinical fibrosis (native-T1, extracellular volume fraction) and inflammation/edema (max-T2) measures. Cardiovascular magnetic resonance measures were compared with those obtained in similar consecutive patients with cancer without ibrutinib treatment (pretreatment controls). Observed measures were also compared with similar-aged broad population rates (general-population controls) and a broader pool of cardiovascular disease (CVD) risk-matched cancer controls. Multivariable regression was used to assess the association between CMR measures and MACE.

Results

Overall, 49 patients treated with ibrutinib were identified, including 33 imaged after treatment initiation (mean [SD] age, 65 [10] years, 9 [27%] with hypertension, and 23 [69.7%] with index-arrhythmias); median duration of ibrutinib-use was 14 months. The mean (SD) pretreatment native T1 was 977.0 (73.0) ms, max-T2 56.5 (4.0) ms, and 4 (13.3%) had LGE. Posttreatment initiation, mean (SD) native T1 was 1033.7 (48.2) ms, max-T2 61.5 (4.8) ms, and 17 (54.8%) had LGE (P < .001, P = .01, and P < .001, respectively, pre- vs post-ibrutinib treatment). Native T12SDs was elevated in 9 (28.6%), and max-T22SDs in 21 (63.0%), respectively. Cardiovascular magnetic resonance measures were highest in those with suspected toxic effects (P = .01 and P = .01, respectively). There was no association between traditional CVD-risk or cancer-treatment status and abnormal CMR measures. Among those without traditional CVD, 16 (58.6%) had LGE vs 38 (13.3%) in matched-controls (relative-risk, 4.8; P < .001). Over a median follow-up of 19 months, 13 (39.4%) experienced MACE. In multivariable models inclusive of traditional CVD risk factors, LGE (hazard ratio [HR], 4.9; P = .04), and native-T12SDs (HR, 3.3; P = .05) associated with higher risks of MACE.

Conclusions and Relevance

In this cohort study, myocardial injury was common in ibrutinib users, and its presence was associated with higher cardiotoxic risk.

Presence of Multi-Morbidities and Colorectal Cancer Screening Utilization among Breast Cancer Survivors

Purpose: Our study aimed to examine the association between the presence of chronic diseases with guideline-concordant colorectal cancer (CRC) screening utilization among breast cancer survivors. Methods: We analyzed data among women with a history of breast cancer from the 2016, 2018, and 2020 Behavioral Risk Factor Surveillance System. Receipt of guideline-concordant CRC screening was the outcome of interest. Diabetes, coronary heart disease/myocardial infarction, stroke, chronic obstructive pulmonary disease, emphysema/chronic bronchitis, arthritis, depressive disorder, or kidney diseases were included in chronic disease conditions. Results: Among 1324 survivors, those with multi-morbidities (3+ chronic diseases; 88.3%) had higher CRC screening use compared to those with one (84.4%) or two (85.4%) diseases (p-value < 0.05). In multivariable analysis, survivors with multi-morbidities were two times more likely to have CRC screening compared to those with only one disease (OR, 2.10; 95% CI, 1.11–3.98). Among survivors with multi-morbidities, Black women (OR, 14.07; 95% CI, 5.61–35.27), and those with frequent poor physical health (OR, 3.32; 95% CI, 1.57–7.00) were positively associated with CRC screening use. Conversely, survivors with frequent poor mental health were 67% less likely to receive CRC screening (OR, 0.33; 95% CI, 0.14–0.74). Conclusion: Among breast cancer survivors, multi-morbidities were positively associated with CRC screening.

Perivascular adipose tissue promotes vascular dysfunction in murine lupus

Introduction

Patients with systemic lupus erythematosus (SLE) are at elevated risk for Q10 cardiovascular disease (CVD) due to accelerated atherosclerosis. Compared to heathy control subjects, lupus patients have higher volumes and densities of thoracic aortic perivascular adipose tissue (PVAT), which independently associates with vascular calcification, a marker of subclinical atherosclerosis. However, the biological and functional role of PVAT in SLE has not been directly investigated.

Methods

Using mouse models of lupus, we studied the phenotype and function of PVAT, and the mechanisms linking PVAT and vascular dysfunction in lupus disease.

Results and discussion

Lupus mice were hypermetabolic and exhibited partial lipodystrophy, with sparing of thoracic aortic PVAT. Using wire myography, we found that mice with active lupus exhibited impaired endothelium-dependent relaxation of thoracic aorta, which was further exacerbated in the presence of thoracic aortic PVAT. Interestingly, PVAT from lupus mice exhibited phenotypic switching, as evidenced by "whitening" and hypertrophy of perivascular adipocytes along with immune cell infiltration, in association with adventitial hyperplasia. In addition, expression of UCP1, a brown/beige adipose marker, was dramatically decreased, while CD45-positive leukocyte infiltration was increased, in PVAT from lupus mice. Furthermore, PVAT from lupus mice exhibited a marked decrease in adipogenic gene expression, concomitant with increased pro-inflammatory adipocytokine and leukocyte marker expression. Taken together, these results suggest that dysfunctional, inflamed PVAT may contribute to vascular disease in lupus.

Patterns of Care and Outcomes of Ambulatory Endovascular Interventions in Lower Extremity Peripheral Arterial Disease

Lower extremity endovascular intervention (LE-EVI) is gaining popularity as the primary treatment modality for patients with symptomatic peripheral artery disease refractory to noninvasive management. We examined the contemporary patterns of care, regional variation, and outcomes of ambulatory LE-EVI in the United States. The National Ambulatory Surgery Sample was analyzed to identify 266,563 records with peripheral artery disease and LE-EVI between January 1, 2016 and December 31, 2017. The mean age of the study cohort was 68.9 years and 40.5% were women. The majority of the endovascular interventions were performed at large (58.1%), urban teaching (64.1%), private not-for-profit (76.8%) centers, and the southern region accounted for most cases (43%). Periprocedural major adverse renal and cardiovascular events and other complications were 0.5% and 3.3%, respectively. Most patients (97.6%) were discharged home after the procedure. Age, female gender, uncontrolled hypertension, ischemic heart disease, heart failure, arrhythmia, chronic kidney disease, malnutrition, non-Medicare insurance, private for-profit, urban teaching facilities, and southern and midwest regions were associated with higher odds of major adverse renal and cardiovascular events. The mean charges per patient encounter were $56,500, with significant differences across various patient and facility characteristics. In conclusion, our study demonstrates the use, patterns of care, financial aspect, and overall safety of ambulatory LE-EVIs in a real-world setting.

Allostatic load and cardiovascular outcomes in males with prostate cancer

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of death in men with prostate cancer (PC). Accumulated stress plays an important role in CVD development. The cumulative burden of chronic stress and life events can be measured using allostatic load (AL).

METHODS

The initial cohort included males aged 18 years and older diagnosed with PC (2005-2019). AL was modeled as an ordinal variable (0-11). Fine-Gray competing risk regressions measured the impact of precancer diagnosis AL and postdiagnosis AL in 2-year major cardiac events (MACE). The effect of AL changes over time on MACE development was calculated via piecewise Cox regression (before, and 2 months, 6 months, and 1 year after PC diagnosis).

RESULTS

We included 5261 PC patients of which 6.6% had a 2-year MACE. For every 1-point increase in AL before and within 60 days after PC diagnosis, the risk of MACE increased 25% (adjusted hazard ratio [aHR] =1.25, 95% confidence interval [CI] = 1.18 to 1.33) and 27% (aHR = 1.27, 95% CI = 1.20 to 1.35), respectively. Using AL as a time-varying exposure, the risk of MACE increased 19% (aHR = 1.19, 95% CI = 1.11 to 1.27), 22% (aHR = 1.22, 95% CI = 1.14 to 1.33), 28% (aHR = 1.28, 95% CI = 1.23 to 1.33), and 31% (aHR = 1.31, 95% CI = 1.27 to 1.35) for every 1-point increase in AL before, 2 months after, 6 months after, and 1 year after PC diagnosis, respectively.

CONCLUSION

AL and its changes over time are associated with MACE in PC patients, suggesting a role of a biological measure of stress as a marker of CVD risk among men with PC.

Cardiovascular Toxicities Associated with Tyrosine Kinase Inhibitors

PURPOSE OF REVIEW

To provide a detailed overview of cardiovascular adverse events associated with the use of tyrosine kinase inhibitors across different tumor types.

RECENT FINDINGS

Despite an undeniable survival advantage of tyrosine kinase inhibitors (TKIs) in patients with hematologic or solid malignancies, the accompanying off-target cardiovascular adverse events can be life-threatening. In patients with B cell malignancies, the use of Bruton tyrosine kinase inhibitors has been associated with atrial and ventricular arrhythmias, as well as hypertension. Cardiovascular toxic profiles are heterogeneous among the several approved breakpoint cluster region (BCR)-ABL TKIS. Notably, imatinib might be cardioprotective. Vascular endothelial growth factor TKIs, constituting the central axis in the treatment of several solid tumors, including renal cell carcinoma and hepatocellular carcinoma, have strongly been associated with hypertension and arterial ischemic events. Epidermal growth factor TKIs as therapy for advanced non-small cell lung cancer (NSCLC) have been reported to be infrequently associated with heart failure and QT prolongation. While tyrosine kinase inhibitors have been demonstrated to increase overall survival across different types of cancers, special consideration should be given to cardiovascular toxicities. High-risk patients can be identified by undergoing a comprehensive workup at baseline.

Cardiovascular toxicities with pediatric tyrosine kinase inhibitor therapy: An analysis of adverse events reported to the Food and Drug Administration

We sought to examine cardiovascular toxicities associated with tyrosine kinase inhibitors in pediatrics. We examined 1624 pediatric adverse events with imatinib, dasatinib, sorafenib, pazopanib, crizotinib, and ruxolitinib reported to the Food and Drug Administration between January 1, 2015, and August 14, 2020. There were 102 cardiovascular event reports. Hypertension was the most commonly reported cardiovascular event and was most frequently associated with sorafenib and pazopanib. The presence of infection increased the reporting odds of cardiovascular events overall and specifically cardiac arrest, heart failure, and hypertension. These data provide early insight into cardiovascular toxicities with tyrosine kinase inhibitor use in pediatrics.

Hypertensive events after the initiation of contemporary cancer therapies for breast cancer control

BACKGROUND

Contemporary therapies improve breast cancer (BC) outcomes. Yet, many of these therapies have been increasingly linked with serious cardiotoxicity, including reports of profound hypertension. Yet, the incidence, predictors, and impacts of these events are largely unknown.

METHODS

Leveraging two large U.S.-based registries, the National Inpatient Sample (NIS) and the Food and Drug Administration Adverse Event Reporting System (FAERS) databases, we assessed the incidence, factors, and outcomes of hypertensive events among BC patients from 2007 to 2015. Differences in baseline characteristics, hypertension-related discharges, and complications were examined over time. Further, we performed a disproportionality analysis using reporting-odds-ratios (ROR) to determine the association between individual BC drugs and hypertensive events. Utilizing an ROR cutoff of >1.0, we quantified associations by drug-class, and individual drugs with the likelihood of excess hypertension.

RESULTS

Overall, there were 5,464,401 BC-admissions, of which 46,989 (0.8%) presented with hypertension. Hypertensive BC patients were older, and saw initially increased in-hospital mortality, which equilibrated over time. The mean incidence of hypertension-related admissions was 732 per 100,000 among BC patients, versus 96 per 100,000 among non-cancer patients (RR 7.71, p < 0.001). Moreover, in FAERS, those with hypertension versus other BC-treatment side-effects were more frequently hospitalized (40.1% vs. 36.7%, p < 0.001), and were most commonly associated with chemotherapy (45.9%). Outside of Eribulin (ROR 3.36; 95% CI 1.37-8.22), no specific drug was associated with a higher reporting of hypertension; however, collectively BC drugs were associated with a higher odds of hypertension (ROR 1.66; 95% CI 1.09-2.53).

CONCLUSIONS

BC therapies are associated with a substantial increase in limiting hypertension.

Association of Androgen Deprivation Therapy with Metabolic Disease in Prostate Cancer Patients: An Updated Meta-Analysis

BACKGROUND

Androgen deprivation therapy (ADT), a backbone treatment for advanced prostate cancer (PC), is known to have a variety of metabolic side effects. We conducted an updated meta-analysis to quantify the metabolic risks of ADT.

MATERIALS AND METHODS

We searched PubMed, Web of Science, and Scopus in May of 2022 for studies investigating the risk of metabolic syndrome (MetS), diabetes, and hypertension from ADT in PC patients using keywords. Only full-length studies with a control group of PC patients not on ADT were included. All results compatible with each outcome domain in each included study were sought. For included studies, relative risk (RR) was pooled using a random effects model and a trim-fill approach was used to adjust for publication bias.

RESULTS

1,846 records were screened, of which 19 were found suitable for data extraction. Five studies, including 891 patients, were evaluated for MetS as an outcome, with the random effects model showing a pooled RR of 1.60 ([95% Confidence Interval (CI), 1.06-2.42]; P=0.03) for patients on ADT while twelve studies, including 336,330 patients, examined diabetes as an outcome, and the random effects model showed a RR of 1.43 ([95% CI, 1.28-1.59]; P< 0.01). After adjustment for publication bias, ADT was associated with a 25% increased risk for diabetes but was not associated with MetS. 4 studies, including 7,051 patients, examined hypertension as an outcome, and the random effects model showed a RR of 1.30 ([95% CI, 1.08-1.55]; P=0.18) in ADT patients.

CONCLUSION

In patients with PC, ADT was not associated with MetS and the association with diabetes was not as strong as previously reported. Our novel meta-analysis of hypertension showed that ADT increased the risk of hypertension by 30%. These results should be understood in the context of collaborating care between a patient's oncologist and primary care provider to optimize care.

Clinical implications of Type 2 diabetes on outcomes after cardiac transplantation

BACKGROUND

T2D is an increasingly common disease that is associated with worse outcomes in patients with heart failure. Despite this, no contemporary study has assessed its impact on heart transplantation outcomes. This paper examines the demographics and outcomes of patients with type 2 diabetes (T2D) undergoing heart transplantation.

METHODS

Using the United Network for Organ Sharing (UNOS) database, patients listed for transplant were separated into cohorts based on history of T2D. Demographics and comorbidities were compared, and cox regressions were used to examine outcomes.

RESULTS

Between January 1st, 2011 and June 12th, 2020, we identified 9,086 patients with T2D and 23,676 without T2D listed for transplant. The proportion of patients with T2D increased from 25.2% to 27.9% between 2011 and 2020. Patients with T2D were older, more likely to be male, less likely to be White, and more likely to pay with public insurance (p<0.001, all). After adjustment, T2D patients had a lower likelihood of transplantation (Hazard Ratio [HR]: 0.93, CI: 0.90-0.96, p<0.001) and a higher likelihood of post-transplant mortality (HR: 1.30, CI: 1.20-1.40, p<0.001). Patients with T2D were more likely to be transplanted in the new allocation system compared to the old allocation system (all, p<0.001).

CONCLUSIONS

Over the last ten years, the proportion of heart transplant recipients with T2D has increased. These patients are more likely to be from traditionally underserved populations. Patients with T2D have a lower likelihood of transplantation and a higher likelihood of post-transplant mortality. After the allocation system change, likelihood of transplantation has improved for patients with T2D.

Cardio oncology: Digital innovations, precision medicine and health equity

The rapid emergence of cardio-oncology has resulted in a rapid growth of cardio-oncology programs, dedicated professional societies sections and committees, and multiple collaborative networks that emerged to amplify the access to care in this new subspecialty. However, most existing data, position statements and guidelines are limited by the lack of availability of large clinical trials to support these recommendations. Furthermore, there are significant challenges regarding proper access to cardio-oncology care and treatment, particularly in marginalized and minority populations. The emergence and evolution of personalized medicine, artificial intelligence (AI), and machine learning in medicine and in cardio-oncology provides an opportunity for a more targeted, personalized approach to cardiovascular complications of cancer treatment. The proper implementation of these new modalities may facilitate a more equitable approach to adequate and universal access to cardio-oncology care, improve health related outcomes, and enable health care systems to eliminate the digital divide. This article reviews and analyzes the current status on these important issues.