Lead Investigator: Timothy Gaulton, Massachusetts General Hospital
Title of Proposal Research: Understanding the impact of body mass index on the effectiveness of baricitinib as a treatment for individuals hospitalized with COVID-19
Vivli Data Request: 8806
Funding Source: None
Potential Conflicts of Interest: None
Summary of the Proposed Research:
Over 40% of adult Americans are obese. Obesity is a major risk factor for severe illness and death from COVID-19 infection. Individuals with obesity may have an exaggerated immune response to the virus, which can contribute to severe illness and complications. Baricitinib is a medication used to treat autoimmune diseases such as rheumatoid arthritis where the body’s natural defense system cannot tell the difference between your own cells and foreign cells, causing the body to mistakenly attack normal cells. It works by inhibiting enzymes called Janus kinases (JAKs). JAKs are a type of enzyme (a protein that speeds up chemical reactions in the body) that are involved in cell growth, survival, development, and are critically important for immune cells. By inhibiting JAKs, baricitinib can help reduce the activity of these immune cells and dampen the immune response. Baricitinib has been studied as a potential treatment for COVID-19, as it may reduce severe inflammation. Clinical trials have shown that baricitinib may reduce the time to recovery and improve clinical outcomes for hospitalized COVID-19 patients. Of concern, past research has found that people with obesity and rheumatoid arthritis may have a reduced response to baricitinib compared to people without obesity and were less likely to achieve clinical remission. While the mechanism of this reduced response is unclear, it raises significant questions about the effectiveness of baricitinib in treating COVID-19 in patients with obesity.
Identifying medications that may benefit individuals with obesity who develop COVID-19 infection is very important. At the same time, it is critical to identify when medications are ineffective or even harmful, as this helps us understand disease mechanisms and improve clinical outcomes. Therefore, we plan to perform a retrospective analysis of a patient cohort from two clinical trials that investigated the effectiveness of baricitinib on clinical outcomes in individuals hospitalized with COVID-19. We will use regression modeling to quantify the impact of obesity on baricitinib effectiveness. Regression models are statistical models that estimate the relationship between one dependent variable and one or more other independent variables. The results of our study will provide high-quality evidence to inform treatment decisions in obese patients with COVID-19 and will provide a wider understanding of how obesity impacts COVID-19 infection.
A Randomized, Double-Blind, Placebo-Controlled, Parallel-Group Phase 3 Study of Baricitinib in Patients With COVID-19 Infection
Data Contributor: Lilly
Study ID: NCT04421027
Sponsor ID: 17830
A Multicenter, Adaptive, Randomized Blinded Controlled Trial of the Safety and Efficacy of Investigational Therapeutics for the Treatment of COVID-19 in Hospitalized Adults (ACTT-2)
Data Contributor: NIAID (a data-sharing platform funded by the National Institutes of Health)
Study ID: NCT04401579
Sponsor ID: 20-0006 ACTT-2