Effect of Once-Weekly Exenatide on Clinical Outcomes According to Baseline Risk in Patients With Type 2 Diabetes Mellitus: Insights From the EXSCEL Trial.
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2018-10
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Background In the EXSCEL (Exenatide Study of Cardiovascular Event Lowering), exenatide once-weekly resulted in a nonsignificant reduction in major adverse cardiovascular events ( MACEs ) and a nominal 14% reduction in all-cause mortality in 14 752 patients with type 2 diabetes mellitus (T2 DM ) with and without cardiovascular disease. Whether patients at increased risk for events experienced a comparatively greater treatment benefit with exenatide is unknown. Methods and Results In the EXSCEL population, we created risk scores for MACEs and all-cause mortality using step-wise selection of baseline characteristics. A risk score was calculated for each patient, and a time-to-event model for each end point was developed including the risk score, treatment assignment, and risk-treatment interaction. Interaction P values evaluating for a differential treatment effect by baseline risk were reported. Over a median follow-up of 3.2 years (interquartile range, 2.2, 4.4), 1091 (7.4%) patients died and 1744 (11.8%) experienced a MACE . Independent predictors of MACEs and all-cause mortality included age, sex, comorbidities (eg, previous cardiovascular event), body mass index, blood pressure, hemoglobin A1c, and estimated glomerular filtration rate. The all-cause mortality and MACE risk models had modest discrimination with optimism-corrected c-indices of 0.73 and 0.71, respectively. No interaction was observed between treatment effect and risk profile for either end point (both interactions, P>0.1). Conclusions Baseline characteristics (eg, age, previous cardiovascular events) and routine laboratory values (eg, hemoglobin A1c, estimated glomerular filtration rate) provided modest prognostic value for mortality and MACEs in a broad population of patients with type 2 diabetes mellitus. Exenatide's effects on mortality and MACEs were consistent across the spectrum of baseline risk. Clinical Trial Registration URL: https://www.clinicaltrials.gov . Unique identifier: NCT 01144338.
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Mentz, Robert J, M Angelyn Bethel, Peter Merrill, Yuliya Lokhnygina, John B Buse, Juliana C Chan, João S Felício, Shaun G Goodman, et al. (2018). Effect of Once-Weekly Exenatide on Clinical Outcomes According to Baseline Risk in Patients With Type 2 Diabetes Mellitus: Insights From the EXSCEL Trial. Journal of the American Heart Association, 7(19). p. e009304. 10.1161/JAHA.118.009304 Retrieved from https://hdl.handle.net/10161/19763.
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Yuliya Vladimirovna Lokhnygina
Statistical methods in clinical trials, survival analysis, adaptive designs, adaptive treatment strategies, causal inference in observational studies, semiparametric inference
Neha Pagidipati
Neha J. Pagidipati, MD, MPH, is an Assistant Professor of Medicine and cardiovascular disease prevention specialist. Since 2011, she has conducted research on cardiometabolic disease prevention, lifestyle modification and weight management. She is currently an NIH K12 scholar in Implementation and Dissemination Science.
Dr. Pagidipati is building the Duke Cardiometabolic Disease Prevention Program, which focuses on behavior change and risk factor management in patients with high risk of cardiovascular and metabolic diseases such as diabetes and obesity. The program’s multi-disciplinary team of cardiologists, endocrinologists, nephrologists, and hepatologists will work together to provide coordinated, team-based care to the most high-risk and complex patients in the health system.
Dr. Pagidipati’s research grants include the COORDINATE-Diabetes Trial, to improve the quality of care for patients with diabetes and cardiovascular disease across the U.S., and QuBBD: Deep Poisson Methods for Biomedical Time-to-Event and Longitudinal Data. She served as a study clinician on the large, longitudinal EXSCEL (Exenatide Study of Cardiovascular Event Lowering) trial. She is currently conducting a nation-wide study of obesity management using real-world data sources, and is a site investigator for the Baseline Health Study in collaboration with Verily Life Sciences. In addition, she is leading a large study within the Duke Health System to study heterogeneity within cardiovascular disease risk and response to weight loss interventions among individuals with obesity.
Dr. Pagidipati graduated from Harvard College and Harvard Medical School. She completed her internal medicine residency at Brigham and Women’s Hospital. During a two-year research fellowship in Global Women’s Health at the Brigham, she obtained an MPH from the Harvard School of Public Health and studied cardiovascular disease prevention in women in India. Dr. Pagidipati completed a four-year cardiology fellowship at the Duke University School of Medicine and served as Chief Research Fellow at the Duke Clinical Research Institute. In 2017, she became a faculty member of the Duke University School of Medicine School.
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