More than 100 million U.S. adults have been diagnosed with hypertension, one of the leading risk factors for cardiovascular disease. While more than 70% of people with hypertension cannot achieve adequate blood pressure control with just one drug, current guidelines only make recommendations for first-line therapy.
“The question is: when the first drug is not enough, what is the optimal second drug to add?” said Yuan Lu, ScD, assistant professor of medicine (cardiology) and assistant professor of biomedical informatics and data science and of epidemiology (chronic disease). “There are more than 50 drugs across five major classes available for treating hypertension. Conducting clinical trials to compare every possible drug and combination thereof is impractical; it would be incredibly time-consuming and costly. Consequently, this creates a significant gap in evidence.”
Lu recently received a Research Project Grant (R01) from the National Institutes of Health (NIH) for the project, “Real-World Evidence to Inform Decisions for Hypertension Treatment Escalation,” to help address this question.
Lu and her team will analyze real-world data that is routinely collected by clinicians in health care settings to compare the effectiveness of second antihypertensive agents on major cardiovascular events as well as their comparative risk on potential drug-related adverse events. This study will also look at the effectiveness and safety of each second hypertensive agent when used in different patient subgroups defined by age, sex, race, ethnicity, and comorbidities, which Lu hopes will help address disparities for patients with hypertension. This is the first research study of its kind that uses real-world data assets and reproducible methods to comprehensively evaluate the safety and effectiveness of second anti-hypertensive drugs added after monotherapy.
“Clinicians often face this important patient scenario and lack comprehensive, high-quality evidence on how best to guide the implementation of the available drug options for patients into real-world practice,” said Eric Velazquez, MD, Robert W. Berliner Professor of Medicine and chief of Yale Cardiovascular Medicine. “Hypertension impacts nearly every family in the world. It has been a substantial frustration for me that randomized clinical trials such as ACCOMPLISH, which we completed over 15 years ago, have not been adequately integrated into everyday care. Yuan’s work is pivotal to ensure our research meets its potential to improve the lives of millions of people living with hypertension.”
The study will analyze data from more than 100 million patients in the United States in five electronic health record (EHR) databases. Lu and her team are collaborating with the Observational Health Data Science and Informatics (OHDSI), a multi-stakeholder, international organization that aims to use systematic approaches to improve observational study. OHDSI created the OMOP Common Data Model, which is an open community data standard that allows institutions to efficiently share data for analysis.
“By mapping EHR data into a common data model, we can now combine the power of computing, data science, and clinical knowledge to generate new evidence to address these important clinical questions,” said Lu. “We hope our research will inform the prioritization of future clinical trials, assisting investigators in selecting the most promising drug combinations for testing.”
Lu joined Yale in 2015 after receiving her ScD in Global Health and Population at the Harvard School of Public Health. “I was intrigued by this area of study because instead of a doctor, who can only treat 20 or 30 patients a day, I would have the opportunity to impact health at the population level,” she said.
She hopes that this research will inform the development of clinical guidelines. Even though clinical trials provide the highest quality of evidence, real-world data from observational studies can provide important evidence to complement clinical trials and support guideline development, especially when clinical trials are too expensive or unethical to conduct.
“Physicians can’t just wait for clinical trials to end before they help their patients. They need to keep treating people using the best available information and practices,” said Lu.
Eventually, Lu and her team plan to develop a clinical decision support tool that would incorporate the knowledge gained from this project. The tool would help doctors quickly and easily see recommendations about the types of combination therapies that may work best for their individual patients. “It’s often said that it takes about 17 years to translate about 14% of research findings to be implemented into routine clinical practice. It’s a long time. I want to try to reduce the time it takes to get research into clinical practice and increase the percentage of knowledge translation," she said.
The research team is beginning to refine their protocol for the study, which they aim to publish online via GitHub so that anyone interested in this work can read the proposal and provide feedback to help make improvements. Lu sees tremendous potential for this type of study in other areas of medicine, including diabetes, obesity, and other common health conditions. She and other team members are already beginning work on other projects using real-world data.
For example, Lu, along with other researchers from Yale and colleagues at Sentara Health, recently published a paper in the Journal of the American Heart Association (JAHA), which used real-world EHR data to identify the prevalence, control rates, and diagnostic codes used in a large patient population. The study found that prevalence is increasing, a quarter of patients’ hypertension was not controlled, and there were marked disparities between non-Hispanic Black patients and other racial and ethnic groups. Lu and the study authors say other regional health systems could emulate this study to better understand their hypertension prevalence and control rates and to inform strategies to improve hypertension care. Other study authors include: Yuntian Liu, MPH, Shu-Xia Li, PhD, Mitsuaki Sawano, MD, Patrick Young, PhD, Wade Schulz, MD, and Harlan Krumholz, MD, SM, from Yale, and John E. Brush, Jr., MD, Jordan R. Asher, MD, MS, Mark Anderson, AS, and John S. Burrows, MBA.
“I feel so fortunate that I decided to come to Yale. As an investigator, it can sometimes seem like the only deliverable is a paper. But at Yale, I’m able to work closely with clinicians and see how this knowledge can inform their clinical practice or help them do their job better,” Lu said. “I’m excited to come to work every day.”