Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations.

Background and Objectives: There are no nationally representative studies of mortality and cost effectiveness for fractional flow reserve (FFR) guided percutaneous coronary interventions (PCI) in patients with cancer. Our study aims to show how this patient population may benefit from FFR-guided PCI. Materials and Methods: Propensity score matched analysis and backward propagation neural network machine learning supported multivariable regression was performed for inpatient mortality in this case-control study of the 2016 National Inpatient Sample (NIS). Regression results were adjusted for age, race, income, geographic region, metastases, mortality risk, and the likelihood of undergoing FFR versus non-FFR PCI. All analyses were adjusted for the complex survey design to produce nationally representative estimates. Results: Of the 30,195,722 hospitalized patients meeting criteria, 3.37% of the PCIs performed included FFR. In propensity score adjusted multivariable regression, FFR versus non-FFR PCI significantly reduced inpatient mortality (OR 0.47, 95%CI 0.35−0.63; p < 0.001) and length of stay (LOS) (in days; beta −0.23, 95%CI −0.37−−0.09; p = 0.001) while increasing cost (in USD; beta $5708.63, 95%CI, 3042.70−8374.57; p < 0.001), without significantly increasing complications overall. FFR versus non-FFR PCI did not specifically change cancer patients' inpatient mortality, LOS, or cost. However, FFR versus non-FFR PCI significantly increased inpatient mortality for Hodgkin's lymphoma (OR 52.48, 95%CI 7.16−384.53; p < 0.001) and rectal cancer (OR 24.38, 95%CI 2.24−265.73; p = 0.009). Conclusions: FFR-guided PCI may be safely utilized in patients with cancer as it does not significantly increase inpatient mortality, complications, and LOS. These findings support the need for an increased utilization of FFR-guided PCI and further studies to evaluate its long-term impact.

Stress cardiomyopathy in hospitalized patients with cancer: machine learning analysis by primary malignancy type.

AIMS: Previous studies have shown that patients with stress (Takotsubo) cardiomyopathy (SC) and cancer have higher in-hospital mortality than patients with SC alone. No studies have examined outcomes in patients with active cancer and SC compared to patients with active cancer without SC. We aimed to assess the potential association between primary malignancy type and SC and their shared interaction with inpatient mortality. METHODS AND RESULTS: We analysed SC by primary malignancy type with propensity score adjusted multivariable regression and machine learning analysis using the 2016 United States National Inpatient Sample. Of 30 195 722 adult hospitalized patients, 4 719 591 had active cancer, of whom 568 239 had SC. The mean age of patients with cancer and SC was 69.1, of which 74.7% were women. Among patients with cancer, those with SC were more likely to be female and have white race, Medicare insurance, hypertension, heart failure with reduced ejection fraction, obesity, cerebrovascular disease, anaemia, and chronic obstructive pulmonary disease (P < 0.003 for all). In machine learning-augmented, propensity score multivariable regression adjusted for age, race, and income, only lung cancer [OR 1.25; 95% CI: 1.08-1.46; P = 0.003] and breast cancer [OR 1.81; 95% CI: 1.62-2.02; P < 0.001] were associated with a significantly increased likelihood of SC. Neither SC alone nor having both SC and cancer was significantly associated with in-hospital mortality. The presence of concomitant SC and breast cancer was significantly associated with reduced mortality (OR 0.48; 95% CI: 0.25-0.94; P = 0.032). CONCLUSIONS: This analysis demonstrates that primary malignancy type influences the likelihood of developing SC. Further studies will be necessary to delineate characteristics in patients with lung cancer and breast cancer which contribute to development of SC. Additional investigation should confirm lower mortality in patients with SC and breast cancer and determine possible explanations and protective factors.

TAVR and cancer: machine learning-augmented propensity score mortality and cost analysis in over 30 million patients.

INTRODUCTION: Cardiovascular disease (CVD) and cancer are the top mortality causes globally, yet little is known about how the diagnosis of cancer affects treatment options in patients with hemodynamically compromising aortic stenosis (AS). Patients with cancer often are excluded from aortic valve replacement (AVR) trials including trials with transcatheter AVR (TAVR) and surgical AVR (SAVR). This study looks at how cancer may influence treatment options and assesses the outcome of patients with cancer who undergo SAVR or TAVR intervention. Additionally, we sought to quantitate and compare both clinical and cost outcomes for patients with and without cancer. METHODS: This population-based case-control study uses the most recent year available National Inpatient Sample (NIS (2016) from the United States Department of Health and Human Services' Agency for Healthcare Research and Quality (AHRQ). Machine learning augmented propensity score adjusted multivariable regression was conducted based on the likelihood of undergoing TAVR versus medical management (MM) and TAVR versus SAVR with model optimization supported by backward propagation neural network machine learning. RESULTS: Of the 30,195,722 total hospital admissions, 39,254 (0.13%) TAVRs were performed, with significantly fewer performed in patients with versus without cancer even in those of comparable age and mortality risk (23.82% versus 76.18%, p < 0.001) despite having similar hospital and procedural mortality. Multivariable regression in patients with cancer demonstrated that mortality was similar for TAVR, MM, and SAVR, though LOS and cost was significantly lower for TAVR versus MM and comparable for TAVR versus SAVR. Patients with prostate cancer constituted the largest primary cancer among TAVR patients including those with metastatic disease. There were no significant race or geographic disparities for TAVR mortality. DISCUSSION: Comparison of aortic valve intervention in patients with and without cancer suggests that interventions are underutilized in the cancer population. This study suggests that patients with cancer including those with metastasis have similar inpatient outcomes to patients without cancer. Further, patients who have symptomatic AS and those with higher risk aortic valve disease should be offered the benefit of intervention. Modern techniques have reduced intervention-related adverse events, provided improved quality of life, and appear to be cost effective; these advantages should not necessarily be denied to patients with co-existing cancer.

The Evolving Immunotherapy Landscape and the Epidemiology, Diagnosis, and Management of Cardiotoxicity: JACC: CardioOncology Primer.

Immune checkpoint inhibitors (ICIs) are newer therapies being applied to an increasing number of patients with cancer. Data suggest that up to 36% of cancer patients may be eligible for immunotherapy and, in late 2019, there were more than 3,362 clinical trials initiated to evaluate the effectiveness of immunotherapy, either as single agents or in combination with other immunotherapy, targeted therapies, or traditional cytotoxic or radiation therapy. With the combination of both immune and non-immune treatment approaches, the complexity in making the diagnosis of cardiotoxicity related to an ICI will increase substantially. Here, we summarize the published data on the epidemiology, diagnosis, and management of cardiotoxicity of ICIs. This is a rapidly evolving field, and as our understanding continues to evolve, previously considered hypotheses may not prove to be entirely correct. Research and continued collaborations are urgently needed to provide evidence-based cardiovascular care for this rapidly expanding and vulnerable cohort of patients. (J Am Coll Cardiol CardioOnc 2021;3:35-47) © 2021 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).