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.
BACKGROUND: Millions of cancer survivors are at risk of cardiovascular diseases, a leading cause of morbidity and mortality. Tools to potentially facilitate implementation of cardiology guidelines, consensus recommendations, and scientific statements to prevent atherosclerotic cardiovascular disease (ASCVD) and other cardiovascular diseases are limited. Thus, inadequate utilization of cardiovascular medications and imaging is widespread, including significantly lower rates of statin use among cancer survivors for whom statin therapy is indicated. METHODS: In this methodological study, we leveraged published guidelines documents to create a rules-based tool to include guidelines, expert consensus, and medical society scientific statements relevant to point of care cardiovascular disease prevention in the cardiovascular care of cancer survivors. Any overlap, redundancy, or ambiguous recommendations were identified and eliminated across all converted sources of knowledge. The integrity of the tool was assessed with use case examples and review of subsequent care suggestions. RESULTS: An initial selection of 10 guidelines, expert consensus, and medical society scientific statements was made for this study. Then 7 were kept owing to overlap and revisions in society recommendations over recent years. Extensive formulae were employed to translate the recommendations of 7 selected guidelines into rules and proposed action measures. Patient suitability and care suggestions were assessed for several use case examples. CONCLUSION: A simple rules-based application was designed to provide a potential format to deliver critical cardiovascular disease best-practice prevention recommendations at the point of care for cancer survivors. A version of this tool may potentially facilitate implementing these guidelines across clinics, payers, and health systems for preventing cardiovascular diseases in cancer survivors. TRIAL REGISTRATION: ClinicalTrials.Gov Identifier: NCT05377320.
Study objective: A multi-institutional interdisciplinary team was created to develop a research group focused on leveraging artificial intelligence and informatics for cardio-oncology patients. Cardio-oncology is an emerging medical field dedicated to prevention, screening, and management of adverse cardiovascular effects of cancer/ cancer therapies. Cardiovascular disease is a leading cause of death in cancer survivors. Cardiovascular risk in these patients is higher than in the general population. However, prediction and prevention of adverse cardiovascular events in individuals with a history of cancer/cancer treatment is challenging. Thus, establishing an interdisciplinary team to create cardiovascular risk stratification clinical decision aids for integration into electronic health records for oncology patients was considered crucial. Design/setting/participants: Core team members from the Medical College of Wisconsin (MCW), University of Wisconsin-Milwaukee (UWM), and Milwaukee School of Engineering (MSOE), and additional members from Cleveland Clinic, Mayo Clinic, and other institutions have joined forces to apply high-performance computing in cardio-oncology. Results: The team is comprised of clinicians and researchers from relevant complementary and synergistic fields relevant to this work. The team has built an epidemiological cohort of ~5000 cancer survivors that will serve as a database for interdisciplinary multi-institutional artificial intelligence projects. Conclusion: Lessons learned from establishing this team, as well as initial findings from the epidemiology cohort, are presented. Barriers have been broken down to form a multi-institutional interdisciplinary team for health informatics research in cardio-oncology. A database of cancer survivors has been created collaboratively by the team and provides initial insight into cardiovascular outcomes and comorbidities in this population.
African Americans have a higher rate of cardiovascular morbidity and mortality and a lower rate of specialty consultation and treatment than Caucasians. These disparities also exist in the care and treatment of chemotherapy-related cardiovascular complications. African Americans suffer from cardiotoxicity at a higher rate than Caucasians and are underrepresented in clinical trials aimed at preventing cardiovascular injury associated with cancer therapies. To eliminate racial and ethnic disparities in the prevention of cardiotoxicity, an interdisciplinary and innovative approach will be required. Diverse forms of digital transformation leveraging health informatics have the potential to contribute to health equity if they are implemented carefully and thoughtfully in collaboration with minority communities. A learning healthcare system can serve as a model for developing, deploying, and disseminating interventions to minimize health inequities and maximize beneficial impact.
