Rationale, design, and baseline characteristics of the CArdiovascular safety and Renal Microvascular outcomE study with LINAgliptin (CARMELINA®): a randomized, double-blind, placebo-controlled clinical trial in patients with type 2 diabetes and high cardio-renal risk.

Abstract

BACKGROUND:Cardiovascular (CV) outcome trials in type 2 diabetes (T2D) have underrepresented patients with chronic kidney disease (CKD), leading to uncertainty regarding their kidney efficacy and safety. The CARMELINA® trial aims to evaluate the effects of linagliptin, a DPP-4 inhibitor, on both CV and kidney outcomes in a study population enriched for cardio-renal risk. METHODS:CARMELINA® is a randomized, double-blind, placebo-controlled clinical trial conducted in 27 countries in T2D patients at high risk of CV and/or kidney events. Participants with evidence of CKD with or without CV disease and HbA1c 6.5-10.0% (48-86 mmol/mol) were randomized 1:1 to receive linagliptin once daily or matching placebo, added to standard of care adjusted according to local guidelines. The primary outcome is time to first occurrence of CV death, non-fatal myocardial infarction, or non-fatal stroke. The key secondary outcome is a composite of time to first sustained occurrence of end-stage kidney disease, ≥ 40% decrease in estimated glomerular filtration rate (eGFR) from baseline, or renal death. CV and kidney events are prospectively adjudicated by independent, blinded clinical event committees. CARMELINA® was designed to continue until at least 611 participants had confirmed primary outcome events. Assuming a hazard ratio of 1.0, this provides 90% power to demonstrate non-inferiority of linagliptin versus placebo within the pre-specified non-inferiority margin of 1.3 at a one-sided α-level of 2.5%. If non-inferiority of linagliptin for the primary outcome is demonstrated, then its superiority for both the primary outcome and the key secondary outcome will be investigated with a sequentially rejective multiple test procedure. RESULTS:Between July 2013 and August 2016, 6980 patients were randomized and took ≥ 1 dose of study drug (40.6, 33.1, 16.9, and 9.4% from Europe, South America, North America, and Asia, respectively). At baseline, mean ± SD age was 65.8 ± 9.1 years, HbA1c 7.9 ± 1.0%, BMI 31.3 ± 5.3 kg/m2, and eGFR 55 ± 25 mL/min/1.73 m2. A total of 5148 patients (73.8%) had prevalent kidney disease (defined as eGFR < 60 mL/min/1.73 m2 or macroalbuminuria [albumin-to-creatinine ratio > 300 mg/g]) and 3990 patients (57.2%) had established CV disease with increased albuminuria; these characteristics were not mutually exclusive. Microalbuminuria (n = 2896 [41.5%]) and macroalbuminuria (n = 2691 [38.6%]) were common. CONCLUSIONS:CARMELINA® will add important information regarding the CV and kidney disease clinical profile of linagliptin by including an understudied, vulnerable cohort of patients with T2D at highest cardio-renal risk. Trial registration ClinicalTrials.gov identifier-NCT01897532; registered July 9, 2013.

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10.1186/s12933-018-0682-3

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Rosenstock, Julio, Vlado Perkovic, John H Alexander, Mark E Cooper, Nikolaus Marx, Michael J Pencina, Robert D Toto, Christoph Wanner, et al. (2018). Rationale, design, and baseline characteristics of the CArdiovascular safety and Renal Microvascular outcomE study with LINAgliptin (CARMELINA®): a randomized, double-blind, placebo-controlled clinical trial in patients with type 2 diabetes and high cardio-renal risk. Cardiovascular diabetology, 17(1). p. 39. 10.1186/s12933-018-0682-3 Retrieved from https://hdl.handle.net/10161/22865.

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Scholars@Duke

Alexander

John Hunter Peel Alexander

Professor of Medicine

John H. Alexander, MD, MHS is a cardiologist and Professor of Medicine in the Department of Medicine, Division of Cardiology at Duke University School of Medicine, as well as the Vice Chief, Clinical Research in the Division of Cardiology. He is the Director of Cardiovascular Research at the Duke Clinical Research Institute where he oversees a large group of clinical research faculty and a broad portfolio of cardiovascular clinical trials and observational clinical research programs. He is a member of the American Society of Clinical Investigation.

Dr. Alexander’s clinical interests are in acute and general cardiovascular disease, valvular heart disease, and echocardiology. His research is focused on the translation of novel therapeutic concepts into clinical data through clinical trials, specifically on the therapeutics of acute coronary syndromes, chronic coronary artery disease, and cardiac surgery and on novel methodological approaches to clinical trials. He was on the Executive Committee of the ARISTOTLE trial of apixaban in patients with atrial fibrillation and was the Principal Investigator of the APPRAISE-2 trial of apixaban in patients with acute coronary syndromes.

Dr. Alexander has published extensively and has served as the principal investigator of numerous multicenter clinical trials. He currently serves as the co-chair of the Clinical Trial Transformation Initiative (CTTI).

Pencina

Michael J Pencina

Professor of Biostatistics & Bioinformatics

Michael J. Pencina, PhD
Chief Data Scientist, Duke Health
Vice Dean for Data Science
Director, Duke AI Health
Professor, Biostatistics & Bioinformatics
Duke University School of Medicine

Michael J. Pencina, PhD, is Duke Health's chief data scientist and serves as vice dean for data science, director of Duke AI Health, and professor of biostatistics and bioinformatics at the Duke University School of Medicine. His work bridges the fields of data science, health care, and AI, contributing to Duke’s national leadership in trustworthy health AI.

Dr. Pencina partners with key leaders to develop data science strategies for Duke Health that span and connect academic research and clinical care. As vice dean for data science, he develops and implements quantitative science strategies to support the School of Medicine’s missions in education and training, laboratory and clinical science, and data science.

He co-founded and co-leads the national Coalition for Health AI (CHAI), a multi-stakeholder effort whose mission is to increase trustworthiness of AI by developing guidelines to drive high-quality health care through the adoption of credible, fair, and transparent health AI systems. He also spearheaded the establishment and co-chairs Duke Health’s Algorithm-Based Clinical Decision Support (ABCDS) Oversight Committee and serves as co-director of Duke’s Collaborative to Advance Clinical Health Equity (CACHE).

Dr. Pencina is an internationally recognized authority in the evaluation of AI algorithms. Guideline groups rely on his work to advance best practices for the application of clinical decision support tools in health delivery. He interacts frequently with investigators from academic and industry institutions as well as government officials. Since 2014, he has been acknowledged annually by Thomson Reuters/Clarivate Analytics as one of the world’s "highly cited researchers" in clinical medicine and social sciences, with over 400 publications cited over 100,000 times. He serves as a deputy editor for statistics at JAMA-Cardiology.

Dr. Pencina joined the Duke University faculty in 2013, and served as director of biostatistics for the Duke Clinical Research Institute until 2018. Previously, he was an associate professor in the Department of Biostatistics at Boston University and the Framingham Heart Study, and director of statistical consulting at the Harvard Clinical Research Institute. He received his PhD in Mathematics and Statistics from Boston University in 2003 and holds master’s degrees from the University of Warsaw in actuarial mathematics and business culture.

Email: michael.pencina@duke.edu

Web Sites:  medschool.duke.edu; aihealth.duke.edu; https://scholars.duke.edu/person/michael.pencina

Phone:  919.613.9066

Address:  Duke University School of Medicine; 2424 Erwin Road, Suite 903; Durham, NC 27705

 


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