ACCEL Video Series

Zeroing in on Ovarian Cancer

Nearly a quarter of a million new cases of ovarian cancer are diagnosed worldwide every year. Unfortunately, we still do not have an effective screening tool for early detection and current treatment options are not curative. As a result, the case-to-fatality ratio is 3-4 times higher than breast cancer and the five-year survival rates remain poor. However, new insights into the pathogenesis of ovarian cancer are having direct clinical impact on new and innovative prevention strategies and early detection approaches. In addition, new insights from genomic studies are opening up avenues for novel targeted approaches to attack unique vulnerabilities in this disease. This presentation will discuss the latest advances in ovarian cancer pathogenesis, genomics, and strategies to improve prevention, early detection, and treatment.

Dr. Drapkin is the Franklin Payne Associate Professor of Pathology in Obstetrics & Gynecology at Penn Medicine’s Abramson Cancer Center and Director of the Penn Ovarian Cancer Research Center. His research, teaching, and clinical activities focus on understanding the pathogenesis and genetic alterations involved in women's cancers, with the intent to translate these important biological principles into clinically useful diagnostic and therapeutic tools. Dr. Drapkin is an elected member of the prestigious American Society for Clinical Investigation and was recently awarded the Rosalind Franklin Award for Excellence in Ovarian Cancer Research from the Ovarian Cancer Research Fund Alliance. He serves on the editorial boards of Cancer Research, Clinical Cancer Research, and Gynecologic Oncology, and has authored over 140 peer-reviewed articles.

 

 

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Engaging Stakeholders in Research Using Online Crowdsourcing Methods

Online crowdsourcing is an innovative method to engage multiple stakeholder groups in research studies. Dr. Sood will present on the use of online crowdsourcing for her ACCEL Pilot Grant titled “Family psychosocial care model for congenital heart disease: A crowdsourced study.” She will discuss strengths and limitations of this methodology based on her experiences.

Dr. Sood is a pediatric psychologist at Nemours/A.I. duPont Hospital for Children and Assistant Professor of Pediatrics at Thomas Jefferson University. She directs the Nemours Cardiac Learning and Early Development (LEAD) Program and trains psychology residents and fellows in the specialty area of cardiac neurodevelopment. Dr. Sood’s research focuses on neurodevelopmental outcomes, developmental care and family psychosocial interventions for congenital heart disease. She is the principal investigator on an ACCEL Pilot Grant that has engaged stakeholders in the development of a family-based psychosocial care model for congenital heart disease using online crowdsourcing methods. Dr. Sood is also Co-Vice Chair of the Cardiac Neurodevelopmental Outcome Collaborative (CNOC), co-leads the Patient/Family Support learning lab within the National Pediatric Cardiology Quality Improvement Collaborative (NPC-QIC), and is on the editorial board for Clinical Practice in Pediatric Psychology.

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RCaDES

This presentation focuses on describing three randomized trials designed to identify intervention strategies that can  increase colorectal cancer screening in health system primary care patient populations. The studies, which were supported by the National Cancer Institute, American Cancer Society, and Patient Centered Outcomes Research Institute, were conducted in three different health systems and primary care practice patient populations: 1) general patients, 2) African American patients, and 3) Hispanic patients. The presentation also highlights the need to develop learning health care systems that can support and sustain implementation of evidence-based cancer prevention and control interventions in routine care. A collective impact learning community strategy that can be used to catalyze this process is described. Application of this strategy is discussed relative to interventions intended to increase health system colorectal cancer and lung cancer screening rates.

Ronald E. Myers received a DSW, Social Welfare Policy, in 1983 and a PhD in Medical Sociology in 1989 from the University of Pennsylvania in Philadelphia. Dr. Myers completed postdoctoral training in Behavioral Epidemiology at Fox Chase Cancer Center from 1983 to 1985.  Dr. Myers served as an Associate Member, Division of Cancer Control and Population Sciences, Fox Chase Cancer Center in Philadelphia from 1985 to 1994. In 1994, he joined the Sidney Kimmel Cancer Center at Thomas Jefferson University in Philadelphia as an Associate Professor and Associate Director for Population Science. In 2001, Dr. Myers was appointed as Professor and Director, Division of Population Science, Thomas Jefferson University in Philadelphia, and in 2006 became the Director of the Center for Health Decision at Thomas Jefferson University. He has conducted cancer prevention and control research for more than 30 years, has been principal investigator on numerous peer-reviewed research grants, and has published widely in the field. Dr. Myers’ areas of expertise include patient adherence to cancer screening; shared decision making in cancer risk assessment, screening, and treatment; and decision support in cancer clinical trials participation. Currently, Dr. Myers leads a Patient Centered Outcomes Research Institute (PCORI)-funded randomized trial of decision support and navigation in colorectal cancer screening among Hispanic primary care patients, and a PCORI-funded project on develop a learning community approach to increasing cancer screening in health systems. His is also a principal co-investigator of a project that focuses on lung cancer screening in vulnerable populations.

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Bifactor Modeling of Multifaceted Constructs in HealthCare Research

Many constructs in social, behavioral, and health care research are measured by multiple related domains. However, there is a long-standing and unresolved debate on how to measure and test such multifaceted constructs. Researchers often have to choose between two problematic approaches for analyzing multifaceted constructs: the total score approach and the individual score approach. Both approaches can result in conceptual ambiguity. We recommend the bifactor model as a more advantageous approach for testing multifaceted constructs. The bifactor model is comprised of a general factor that accounts for the commonality shared by the domains, and multiple specific factors, each of which accounts for the unique influence of the domains over and above the general factor. The bifactor model combines the advantages but avoid the drawbacks of the two existing methods and can lead to greater conceptual clarity. We illustrate the bifactor approach by examining the relations of multifaceted well-being to biomarkers.

Dr. Chen is a senior research biostatistician at the Nemours Center for HealthCare Delivery Science, Associate Professor of Pediatrics at the Thomas Jefferson University, and an adjunct Associate Professor of Psychology at the University of Delaware. Before joining Nemours, Dr. Chen was an Assistant Professor of Psychology in the Department of Psychology at the University of Delaware and later at the University of Hong Kong. Dr. Chen obtained her Ph.D. from Arizona State University, where she pursued a rigorous course of training in both quantitative and social psychology. Dr. Chen’s scholarly work builds on the foundation of her dual training in quantitative methodology and social psychology as well as her bicultural experiences. She conducts basic research on measurement, basic research on social/cultural psychology, and applies her work on measurement to key constructs in social/cultural psychology. Dr. Chen’s work has been widely cited by researchers, including top ranked journals’ top 10 most cited list, and 2006 Classics in Academic & Psychological Testing by Google Scholar Metrics.

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Healthcare Engineering – System Engineering approach to healthcare delivery

The Regenstrief Center for Healthcare Engineering (RCHE) started in 2006 by the Regenstrief Foundation with a mission to pursue a transformed health system by conducting impactful research through collaborative partnerships.  In this presentation I will give an overview of RCHE and present selected on-going projects/studies in the center that are applying system engineering principles to improve access and care quality.  Examples will include research in the areas of evidence generation from observational data, matching supply and need, and improving care for vulnerable populations. 

Dr. Yuehwern Yih is a Professor of Industrial Engineering and the Associate Director of Regenstrief Center for Healthcare Engineering at the Discovery Park at Purdue University. Her expertise resides in system and process design, monitor, and control to improve its quality and efficiency for complex systems, such as health systems, manufacturing, and supply chains. Dr. Yih published over 150 scientific articles and book chapters, four edited books, and a patent on system engineering and management.  Her Handbook of Healthcare Delivery Systems is the first handbook covering the wide arrays of sectors in healthcare delivery systems to provide a holistic view of healthcare delivery as an integrated system. Her contributions in this area have been recognized by a National Science Foundation Young Investigator Award (NYI), a Dell K. Allen Outstanding Young Manufacturing Engineer Award, GE Faculty Fellow, NEC Faculty Fellow, Institute for Industrial (and Systems) Engineers (IIE) Fellow, Purdue Engagement Faculty Fellow Award, and Executive Leadership in Academic Technology and Engineering (ELATE) Fellow. Dr. Yih received the highest honor at Purdue in engagement, the Faculty Engagement Fellow Award, based on her work at AMPATH that designs and implements a nutrition information system and a food distribution system for HIV patients in Western Kenya.  In addition to paper publications in top journals in medical and health informatics area, this integrated nutrition system was deployed in 2005 and provided food for over 38,000 HIV patients and their families each year.  Her work was also featured in Industrial Engineer Magazine cover article in January 2014.  Currently,  Dr.  Yih is working on connecting patient demands to health supply chain operations to improve maternal and child health I Uganda, funded by the Melinda and Bill Gates Foundation Grand Challenge Grant.

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Using Machine Learning for Disease Prediction and Patient Risk-Stratification: Studies in the Context of Chronic Kidney Disease

Electronic Health Records (EHRs) are an emerging data source that enables researchers to employ a data-driven approach for the prediction of health outcomes and for patient risk- stratification. Machine learning methods can be used to identify underlying patterns in an individual’s EHRs, which can predict his/her future health condition. In this talk I will present two machine learning models we have developed, one for identifying patterns of associated medical conditions among patients suffering from kidney disease and the other for identifying CKD severity-stages from standard office visit records.

For the former, we apply a machine learning method, namely, topic modeling, to EHRs, to identify distinct groups of co-occurring conditions. For the latter, that is, identifying CKD severity-stages from standard office visit records, we propose a hierarchical meta-classification method, employing simple quantitative non-text features gathered from office visit records, while addressing data imbalance. Our method effectively stratifies CKD severity-levels, obtaining high average sensitivity, precision and F-measure (~93%).

 I am a 5th year Computer Science PhD candidate working at the Computational Biomedicine and Machine Learning Lab (Advisor: Dr. Hagit Shatkay) at University of Delaware. My dissertation research is in computational medicine, and concerns prediction of disease applying machine learning models on clinical data. I focus specifically on CKD and Heart Disease. My goal is to assist healthcare providers in clinical decision making by predicting onset of disease or adverse events such as hospitalization. We have obtained a number of promising results, including predicting the risk of CKD severity-levels from standard office visit records, identifying several novel risk factors of sudden cardiac death in hypertrophic cardiomyopathy patients, and characterizing patterns of co-occurring medical conditions among patients suffering from kidney disease.

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Team Building and Translational Science: Chemistry, Biomaterials, and Improving Recovery after Vascular Surgery

Adult and congenital cardiovascular diseases are significant health problems that are often managed using surgery.  Bypass grafting is a principal approach, but grafts fail at unacceptably high rates due to maladaptive tissue responses.  To address this challenge, and to improve outcomes after cardiovascular surgery, we assembled a multi-institutional, multi-disciplinary team to develop applications of stem-cell-laden, physico-chemically tunable biomaterials to improve post-surgical healing.  The presentation will focus on preclinical development and testing of artificial vascular “pedicles” to stabilize skeletonized arterial conduits and on the team-based approach used in the translation of fundamental knowledge in the fields of chemistry, physics, materials science, and cardiovascular physiology into precision therapeutics for cardiovascular surgery patients.  Specifically, data will be presented on (i) the design and use of injectable, hydrogel-based biomaterials on human arterial cells and cord-blood derived stem cells and (ii) the effects of abluminally-placed hydrogels on the compliance and tissue structure of skeletonized carotid arteries in a preclinical model.

Robert E. Akins, Jr., PhD, FAACPDM, FAHA is a Principal Scientist, Director of the Center for Pediatric Clinical Research and Development, and Head of Tissue Engineering and Regenerative Medicine Research at the Nemours - Alfred I. duPont Hospital for Children in Wilmington, DE. Dr. Akins received his doctorate from the University of Pennsylvania in 1992. He was the first American honored as a fellow of the Japan Foundation on Aging and Health for work in cardiology and pharmacology research. He is an inaugural Fellow of the American Heart Association Council on Cardiovascular Surgery and Anesthesia and a Fellow of the American Academy for Cerebral Palsy and Developmental Medicine. Dr. Akins was named "Neuroscientist of the Year" in 2013 by the DE Society for Neuroscience and "Researcher of the Year" by Nemours in 2014. His research group, which includes students, fellows, clinicians, professional staff, and collaborators from partner institutions, focuses on regenerative medicine and the development of precision therapeutics with a particular emphasis on instructive and responsive biomaterials.

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Improving Perinatal Outcomes through Research

This presentation will discuss the role that research has played in improving perinatal outcomes.  It will review the challenges that are unique to perinatal trials as well as studies that are addressing them.

Dr. Hoffman is the Marie E. Pinizotto Endowed Chair of Christiana Care Health System.  He is an active researcher in the area of perinatal medicine both nationally and internationally.  His particular focus is on the prevention of preterm delivery.

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Ongoing Issues in Kidney Transplantation

Despite the success of kidney transplantation, the burden of ESRD incidence continues to result in higher numbers of patients in need of renal replacement therapy. Various options to increase supply of organs are still unmatched by the increased demand.  Strategies to increase organ supply and optimize transplant outcomes will be discussed.

Dr. Scantlebury is currently the Associate Director of the Kidney Transplant Program at Christiana Care Health System in Newark, Delaware, as well as the Director of Outpatient Clinics for kidney transplant services.

Dr. Scantlebury is the first African American woman in the field of transplantation surgery, and was honored with the National Kidney Foundation’s Gift of Life Award for her work in Kidney Transplantation and minorities. She was voted Best Doctor in America and Top Doctors by Philadelphia Magazine for 2014 and 2015. She was recently honored by the Wilmington (DE) Chapter of the NAACP for her work in Health Advocacy as well as the Society of Foreign Consuls of New York for her outstanding achievements and community contributions. Dr. Scantlebury is a member of numerous professional societies including the American Society of Transplantation, the American College of Surgeons, the Society of Black Academic Surgeons and the Association for Multicultural Affairs in Transplantation. She also served on the National Institute of Health Immunology and Transplantation Committee. She is a member of the Wilmington Chapter of the Links, Inc.

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Joint Modeling of Longitudinal and Time-To-Event Data: GFR and Hospitalization

Studies that collect longitudinal data and time-to-event (survival / failure) data can analyze each separately if there is no association between the longitudinal data and the time-to-event data.  However, if there is an association, then a joint analysis is necessary to avoid biased results.  This study addresses whether there is a relationship between GFR measurements collected over time in CKD patients, and time to first hospitalization following a GFR value less than 60.  Separate analyses are done for change in GFR over time and time to hospitalization followed by a joint analysis to assess whether there is a statistically significant relationship between the two.  

Dr. Kolm is Director of Biostatistics at MedStar Cardiovascular Research Network, MedStar Heart and Vascular Institution. He has over 30 years of experience in consulting with principal investigators in the design and analysis of clinical trials, retrospective and observational studies, and large patient registries. Dr. Kolm has a wide range of statistical expertise including hierarchical general and generalized linear models, classification and tree regression, time-to-event analysis, cost-effectiveness analysis and multiple imputation methods for missing data.

 

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