Yang, Eric H.

Background and Objectives: Cancer and coronary artery disease (CAD) often coexist. Compared to quantitative coronary angiography (QCA), fractional flow reserve (FFR) has emerged as a more reliable method of identifying significant coronary stenoses. We aimed to assess the specific management, safety and outcomes of FFR-guided percutaneous coronary intervention (PCI) in cancer patients with stable CAD. Materials and Methods: FFR was used to assess cancer patients that underwent coronary angiography for stable CAD between September 2008 and May 2016, and were found to have ≥50% stenosis by QCA. Patients with lesions with an FFR > 0.75 received medical therapy alone, while those with FFR ≤ 0.75 were revascularized. Procedure-related complications, all-cause mortality, nonfatal myocardial infarction, or urgent revascularizations were analyzed. Results: Fifty-seven patients with stable CAD underwent FFR on 57 lesions. Out of 31 patients with ≥70% stenosis as measured by QCA, 14 (45.1%) had an FFR ≥ 0.75 and lesions were reclassified as moderate and did not receive PCI nor DAPT. Out of 26 patients with <70% stenosis as measured by QCA, 6 (23%) had an FFR < 0.75 and were reclassified as severe and were treated with PCI and associated DAPT. No periprocedural complications, urgent revascularization, acute coronary syndromes, or cardiovascular deaths were noted. There was a 22.8% mortality at 1 year, all cancer related. Patients who received a stent by FFR assessment showed a significant association with decreased risk of all-cause death (HR: 0.37, 95% CI 0.15–0.90, p = 0.03). Conclusions: Further studies are needed to define the optimal therapeutic approach for cancer patients with CAD. Using an FFR cut-off point of 0.75 to guide PCI translates into fewer interventions and can facilitate cancer care. There was an overall reduction in mortality in patients that received a stent, suggesting increased resilience to cancer therapy and progression.

In patients with cancer, myocardial infarction (MI) has distinct features and mechanisms compared to the non-oncology population. Triggers of myocardial ischemia specific to the oncology population have been increasingly identified. Coronary plaque disruption, coronary vasospasm, coronary microvascular dysfunction, spontaneous coronary artery dissection, and coronary oxygen supply-demand mismatch are all causes of MI that have been shown to have specific triggers related to either the treatments or complications of cancer. MI can occur in the presence or absence of atherosclerotic coronary artery disease (CAD). MI with nonobstructive CAD (MINOCA) is a heterogeneous syndrome that has distinct pathophysiology and different epidemiology from MI with significant CAD (MI-CAD). Recognition and differentiation of MI-CAD and MINOCA is essential in the oncology population, due to unique etiology and impact on diagnosis, management, and overall outcomes. There are currently no reports in the literature concerning MINOCA as a unified syndrome in oncology patients. The purpose of this review is to analyze the literature for studies related to known triggers of myocardial ischemia in cancer patients, with a focus on MINOCA. We propose that certain cancer treatments can induce MINOCA-like states, and further research is warranted to investigate mechanisms that may be unique to certain cancer states and types of treatment.

Background: There are good data to support using a single high-sensitivity cardiac troponin T (hs-cTnT) below the limit of detection of 5 ng/L to exclude acute myocardial infarction. Per the US Food and Drug Administration, hs-cTnT can only report to the limit of quantitation of 6 ng/L, a threshold for which there are limited data. Our goal was to determine whether a single hs-cTnT below the limit of quantitation of 6 ng/L is a safe strategy to identify patients at low risk for acute myocardial injury and infarction. Methods: The efficacy (proportion identified as low risk based on baseline hs-cTnT<6 ng/L) of identifying low-risk patients was examined in a multicenter (n=22 sites) US cohort study of emergency department patients undergoing at least 1 hs-cTnT (CV Data Mart Biomarker cohort). We then determined the performance of a single hs-cTnT<6 ng/L (biomarker alone) to exclude acute myocardial injury (subsequent hs-cTnT >99th percentile in those with an initial hs-cTnT<6 ng/L). The clinically intended rule-out strategy combining a nonischemic ECG with a baseline hs-cTnT<6 ng/L was subsequently tested in an adjudicated cohort in which the diagnostic performance for ruling out acute myocardial infarction and safety (myocardial infarction or death at 30 days) were evaluated. Results: A total of 85 610 patients were evaluated in the CV Data Mart Biomarker cohort, among which 24 646 (29%) had a baseline hs-cTnT<6 ng/L. Women were more likely than men to have hs-cTnT<6 ng/L (38% versus 20%, P <0.0001). Among 11 962 patients with baseline hs-cTnT<6 ng/L and serial measurements, only 1.2% developed acute myocardial injury, resulting in a negative predictive value of 98.8% (95% CI, 98.6–99.0) and sensitivity of 99.6% (95% CI, 99.5–99.6). In the adjudicated cohort, a nonischemic ECG with hs-cTnT<6 ng/L identified 33% of patients (610/1849) as low risk and resulted in a negative predictive value and sensitivity of 100% and a 30-day rate of 0.2% for myocardial infarction or death. Conclusions: A single hs-cTnT below the limit of quantitation of 6 ng/L is a safe and rapid method to identify a substantial number of patients at very low risk for acute myocardial injury and infarction.

Abstract Purpose: Cardiac toxicity is a serious potential complication of HER2-directed therapies and anthracyclines. HER2 codon 655 and SLC28A3 gene polymorphisms have been reported to be associated with cardiac toxicity from anti-HER2 and anthracycline therapy, respectively. Association of the polymorphism at HER2 codon 655 with prognosis has also been reported. Experimental Design: Whole blood samples from patients treated on a randomized adjuvant breast cancer trial (BCIRG-006) that compared chemotherapy with or without trastuzumab plus either anthracycline or nonanthracycline chemotherapy were tested for genetic polymorphisms in HER2 codon 655 and SLC28A3. Genotypes were correlated with cardiac function and disease-free survival (DFS) outcomes. Results: Of 3,222 patients enrolled in BCIRG-006, 662 patient samples were successfully genotyped for the rs1136201 allele in HER2 (codon 655): 424 (64%) were AA, 30 (4.5%) were GG, and 208 (31%) were AG genotype. In addition, 665 patient samples were successfully genotyped for the rs7853758 allele in the SLC28A3 gene: 19 (3%) were AA, 475 (71%) were GG, and 171 (26%) were AG genotype. Follow-up time was 10 years. No correlation between DFS, cardiac event rate, or mean left ventricular ejection fraction (LVEF) and rs1136201 genotype was seen in the trastuzumab-treated or non–trastuzumab-treated patients. Moreover, mean LVEF and cardiac event rates were similar in all rs7853758 genotype groups treated with anthracycline-based therapy. Conclusions: In the largest study to date to evaluate whether two polymorphisms are associated with DFS and/or cardiac toxicity in HER2-positive breast cancer treated with trastuzumab and/or anthracyclines, we observed no correlation.

Introduction: Ischemic stroke (IS) causes substantial morbidity and mortality in patients undergoing percutaneous coronary intervention (PCI) with a 5 yr incidence ~ 3%. We sought the test the accuracy of Machine learning (ML) algorithms in predicting IS in patients undergoing PCI. Methods: Mayo Clinic CathPCI registry data were retrospectively analyzed from Jan 2003 - June 2018 including 21,872 patients who underwent PCI. The cohort was randomly divided into a training sample (75%, n=16404) and a unique test sample (25%, n=5468) prior to model generation. The risk prediction model was generated utilizing a random forest algorithm (RF model) on 188 unique variables to predict the risk of IS at 6-month, 1, 2, and 5-year post PCI. Conventional risk factors for stroke were used for logistic regression. The receiver operating characteristic (ROC) curve and area under the curve for the RF and logistic regression models were compared for the test cohort. Results: The mean age was 66.9 ± 12.4 years, and 71% were male. Patient demographics and outcomes are shown in Table 1 . The ROC area under the curve for the RF model was superior compared to the logistic regression model in predicting IS at 6 months, 1,2 and 5 yrs for the test cohort ( Figure 1 .) Conclusions: The RF model accurately predicts short and long term risk of IS and outperforms logistic regression analysis in patients undergoing PCI.

Abstract Background: While pre-existing cardiovascular disease (CVD) appears to be associated with poor outcomes in patients with Coronavirus Disease 2019 (COVID-19), data on patients with CVD and concomitant cancer is limited. Evaluate the effect of underlying CVD and CVD risk factors with cancer history on in-hospital mortality in those with COVID-19.Methods: Data from symptomatic adults hospitalized with COVID-19 at 86 hospitals in the US enrolled in the American Heart Association’s COVID-19 CVD Registry was analyzed. The primary exposure was cancer history. The primary outcome was in-hospital death. Multivariable logistic regression models were adjusted for demographics, CVD risk factors, and CVD. Interaction between history of cancer with concomitant CVD and CVD risk factors were tested.Results: Among 8222 patients, 892 (10.8%) had a history of cancer and 1501 (18.3%) died. Cancer history had significant interaction with CVD risk factors of age, body mass index (BMI), and smoking history, but not underlying CVD itself. History of cancer was significantly associated with increased in-hospital death (among average age and BMI patients, adjusted odds ratio [aOR]=3.60, 95% confidence interval [CI]: 2.07-6.24; p<0.0001 in those with a smoking history and aOR=1.33, 95%CI: 1.01 - 1.76; p=0.04 in non-smokers). Among the cancer subgroup, prior use of chemotherapy within 2 weeks of admission was associated with in-hospital death (aOR=1.72, 95%CI: 1.05-2.80; p=0.03). Underlying CVD demonstrated a numerical but statistically nonsignificant trend toward increased mortality (aOR=1.18, 95% CI: 0.99 - 1.41; p=0.07).Conclusion: Among hospitalized COVID-19 patients, cancer history was a predictor of in-hospital mortality. Notably, among cancer patients, recent use of chemotherapy, but not underlying CVD itself, was associated with worse survival. These findings have important implications in cancer therapy considerations and vaccine distribution in cancer patients with and without underlying CVD and CVD risk factors.

Background: Identifying patients at a high risk of mortality post percutaneous coronary intervention (PCI) is of vital clinical importance. We investigated the utility of machine learning algorithms to predict short and intermediate-term risk of all-cause mortality in patients undergoing PCI. Methods: Patient-level demographics, clinical, electrocardiographic ,echocardiographic and angiographic data from January 2006 to December 2017 were extracted from the Mayo Clinic CathPCI registry and clinical records. For patients with multiple PCI events, data collected at the time of the index PCI was used for analysis. Patients who underwent bailout coronary artery bypass graft surgery (CABG) prior to discharge were excluded. 306 variables were incorporated into random forest machine learning model (RF) to predict all-cause mortality at 6 months and 1 year after PCI. Ten-fold cross-validation repeated five times was used to optimize the hyperparameters and estimate its external performance. The National Cardiovascular Data Registry (NCDR) based logistic regression model was used for comparison. The area under receiver operator characteristic curves (AUC) was calculated to assess the ability of the models to predict all-cause mortality. Results: A total of 17356 unique patients were included for the final analysis after excluding 165 patients who underwent CABG surgery during the index hospitalization. The mean age was 66.9 ± 12.5 years;71% were male. Indications for PCI were ST-elevation myocardial infarction (9.4%), non-ST elevation myocardial infarction (12.9%), unstable angina (17.7%), and stable angina (52.8%) in the cohort. In-hospital, 6-month & 1 year mortality rates were 1.9%,4.2% & 5.8% respectively. The RF model was superior to the NCDR model in predicting inhospital, 6-month, 1 year mortality (p<0.0001) ( Figure 1 ). Conclusion: Machine learning is superior to NCDR model in predicting short and intermediate risk of all-cause mortality post PCI.

Abstract Background Limited data exist on high-sensitivity cardiac troponin (hs-cTn) for risk-stratification in COVID-19. Methods We conducted a multicenter, retrospective, observational, US-based study of COVID-19 patients undergoing hs-cTnT. Outcomes included short-term mortality (in-hospital and 30-days post-discharge) and a composite of major adverse events, including respiratory failure requiring mechanical ventilation, cardiac arrest, and shock within the index presentation and/or mortality during the index hospitalization or within 30-days post-discharge. Results Among 367 COVID-19 patients undergoing hs-cTnT, myocardial injury was identified in 46%. They had a higher risk for mortality (20% vs 12%, P &lt; 0.0001; unadjusted HR 4.44, 95% CI 2.13–9.25, P &lt; 0.001) and major adverse events (35% vs. 11%, P &lt; 0.0001; unadjusted OR 4.29, 95% CI 2.50–7.40, P &lt; 0.0001). Myocardial injury was associated with major adverse events (adjusted OR 3.84, 95% CI 2.00–7.36, P &lt; 0.0001) but not mortality. Baseline (adjusted OR 1.003, 95% CI 1.00–1.007, P = 0.047) and maximum (adjusted OR 1.005, 95% CI 1.001–1.009, P = 0.0012) hs-cTnT were independent predictors of major adverse events. Most (95%) increases were due to myocardial injury, with 5% (n = 8) classified as type 1 or 2 myocardial infarction. A single hs-cTnT &lt;6 ng/L identified 26% of patients without mortality, with a 94.9% (95% CI 87.5–98.6) negative predictive value and 93.1% sensitivity (95% CI 83.3–98.1) for major adverse events in those presenting to the ED. Conclusions Myocardial injury is frequent and prognostic in COVID-19. While most hs-cTnT increases are modest and due to myocardial injury, they have important prognostic implications. A single hs-cTnT &lt;6 ng/L at presentation may facilitate the identification of patients with a favorable prognosis.

Introduction: The impact of beta blocker use on surgical outcomes of cancer patients receiving immunotherapy is unknown. Hypothesis: Beta blocker use is associated with lower post-operative mortality in cancer patients on immunotherapy. Methods: We used an institutional Advanced Cohort Explorer to identify all patients who underwent any surgical procedure less than 90 days after receiving immunotherapy. Data on the procedure performed as well as the post-operative outcome were collected and analyzed per the pre-operative beta blocker use status. Results: A total of 233 patients underwent surgery between 09/2011-06/2019. Mean age was 64.7 years (range: 16-92). The most common cancer diagnoses were lung (48, 44.4%), melanoma (49, 45.4%) and kidney (11, 10.2%). Immunotherapy medications were pembrolizumab ( 127, 54.5%), nivolumab (51, 21.9%), ipilimumab (43, 18.5%), atezolizumab (11, 4.7%) and avelumab (1, 0.43%). Pre-operative beta blocker use was documented in 140 (60.1%) patients. Most common surgical procedures were skin resection (75, 32.1%), wound repair (47, 20.2%), vascular procedures (36, 15.5%), urethral procedures 16 (6.9%) and sentinel lymph node biopsies (10, 4.3%). The 30-day mortality rate was 10.3% (24 deaths). In a multi-variable logistic regression analysis, pre-operative use of beta blockers was associated with a lower risk of death within 30 days from surgery (OR 0.34, CI 0.13-0.87, P=0.024). 30-day mortality rates were higher in patients undergoing vascular (50%, 17 of 34) versus non-vascular (3.5%, 7 of 199) procedures (P<0.0001) in a Chi Square test. Conclusions: Beta blocker use is associated with a lower 30-day mortality rate after surgical procedures in cancer patients treated with immunotherapy. Further investigation is warranted.

Abstract In response to the coronavirus disease 2019 (COVID-19) pandemic, the Cardio-Oncology and Imaging Councils of the American College of Cardiology offers recommendations to clinicians regarding the cardiovascular care of cardio-oncology patients in this expert consensus statement. Cardio-oncology patients—individuals with an active or prior cancer history and with or at risk of cardiovascular disease—are a rapidly growing population who are at increased risk of infection, and experiencing severe and/or lethal complications by COVID-19. Recommendations for optimizing screening and monitoring visits to detect cardiac dysfunction are discussed. In addition, judicious use of multimodality imaging and biomarkers are proposed to identify myocardial, valvular, vascular, and pericardial involvement in cancer patients. The difficulties of diagnosing the etiology of cardiovascular complications in patients with cancer and COVID-19 are outlined, along with weighing the advantages against risks of exposure, with the modification of existing cardiovascular treatments and cardiotoxicity surveillance in patients with cancer during the COVID-19 pandemic.