2021 NephCure Award Recipients CureGN Pilot Project Grant Awardees CHIA-SHI WANG, MD, MSc (Emory University) Electronic health tools for glomerulonephritis disease monitoring and management support Chia-shi Wang, MD, MSc is a pediatric nephrologist in Atlanta, Georgia. Her passion to improve the lives of patients with nephrotic syndrome began in medical school and led her to become a nephrologist and clinician-scientist focused on nephrotic syndrome research. Dr. Wang’s research has included projects examining nephrotic syndrome risk factors, outcomes, and medication treatments. She has been a CureGN and NEPTUNE investigator since 2015. Working directly with patients and their families in the clinical setting, she learned first-hand that families face heavy management burden. Yet, there are few tools to support families in this chronic disease. She began working with pediatric patient families and Georgia Institute of Technology engineers as well as other scientists and clinicians to develop and evaluate electronic health (eHealth) tools. Her team has developed a mobile app for nephrotic syndrome management in children (UrApp®) which is currently being evaluated in an NIH-funded multicenter trial (NCT04075656). Dr. Wang is originally from Taiwan and moved to the U.S when she was 13 years old. She has lived in Atlanta since 2012 and loves its abundant green spaces. She has two children, ages 9 and 6, who keep her on her toes! Lay Summary of the Project: Description: Electronic health tools (eHealth), such as text-messaging programs, mobile apps, or webpages and web apps may help improve the care of patients with glomerulonephritis. We previously found that text messaging and mobile apps work well to help track symptoms and disease activity and are liked by pediatric patients and their families. In this project, we will study how well the text-messaging program used among adult CureGN participants improves glomerulonephritis management. We will then partner with patients, nephrologists, health education experts, and engineers to design a comprehensive eHealth tool that is tailored to the specific needs of glomerulonephritis patients. In the first part of the study, we will use CureGN data to find out how feasible it is for patients to use text-messaging for disease monitoring; how well the program tracks disease activity; whether it helps patients with taking medications; and whether it helps prevent hospitalizations. For the second part of the study to design a comprehensive eHealth tool, we will interview physicians in the CureGN network as well as patients at the University of Michigan and Emory University. We will ask them for their opinions on what features they would like to have in an eHealth tool to help with glomerulonephritis management. Based on the survey results, health education experts and engineers at Emory and Georgia Institute of Technology will built mock-ups of the tool. We will then invite 10 patients to join nephrologists, health education experts, and engineers in stakeholder meetings to review the mock-ups and refine the tool design with the collaborative input of all stakeholders. Goals and Significance: Our team’s long-term goal is to develop robust, effective, user-centered eHealth tools to improve glomerulonephritis management and patient outcomes. We will capitalize on the incredibly rich data collected from CureGN patients and the expert opinions of CureGN clinicians to glean insights into glomerulonephritis management needs. We will bring together patients, clinicians, and experts in equal partnership to create a tool that directly addresses the needs of patients. In doing so, the tool will have the features and quality that users want and be feasible to use in the real world. We hope to lead to a paradigm change of usual care and improve patient outcomes. JARCY ZEE, PhD (Children’s Hospital of Philadelphia and the University of Pennsylvania) Causal effects of time-varying exposures on recurrent outcomes with time-dependent confounding Dr. Jarcy Zee is an Assistant Professor of Biostatistics at the University of Pennsylvania and Children’s Hospital of Philadelphia. She received her PhD in Biostatistics from the University of Pennsylvania and has been doing research in kidney diseases since then. While she does not see patients directly, she sees the massive amounts of data that those patients have graciously provided to researchers. Her work is therefore focused on developing and applying statistical methods to analyze data in the most accurate and efficient ways. Specifically, Dr. Zee provides statistical expertise for the Nephrotic Syndrome Study Network (NEPTUNE) and Cure Glomerulonephropathy (CureGN) studies. She has specific interests in the integration and analysis of clinical, pathology, and gene expression data to understand treatment effects and identify new biomarkers of glomerular disease outcomes. While working with the NEPTUNE and CureGN datasets and her clinical collaborators, Dr. Zee discovered that there were research questions related to estimating medication effects on recurrent event outcomes that could not be answered with existing statistical techniques. Her current project thus aims to develop novel data analysis methods to enable a wide array of new research. Lay Summary of the Project: Unlike in many clinical trials, treatments for patients in observational studies or in the real world often change over time. Advanced statistical methods are required to understand cause-effect relationships between these time-varying treatment exposures and clinical outcomes. Unfortunately, such methods have not yet been developed for recurrent event outcomes. In patients with glomerular diseases, many clinical outcomes of interest repeat over time—for example, recurrent infections and recurrent remission events. This project will therefore fill the gap by developing a novel statistical model that can accurately estimate the effects of time-varying exposures on recurrent outcomes. The proposed model’s theoretical properties will be developed, and the model’s performance will be extensively tested through a series of computer simulations. Then, the model will be applied to data from the CureGN study to estimate the effect of time-varying steroid use on recurrent infections and the effect of time-varying renin-angiotensin aldosterone system inhibitor use on recurrent proteinuria remissions. Statistical software will be developed to implement the model in a wide variety of settings. The new statistical model can be used to investigate many existing and future clinical research questions in glomerular disease for the first time. The accurate and precise estimation of time-varying treatment effects on recurrent outcomes will ultimately inform improvements in clinical care for patients with glomerular diseases. See Awardees From Other Years: 2021 2022 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2009 2008