Dagmawi Haile
‘Evaluating causal effects of therapies in multiple sclerosis’
University of Melbourne, VIC
Awarded 2023
Co-funded by the Rotary Passport Club of Sylvania Waters
“This is the first study that will directly assess the causal effects of therapies in MS that occur with a substantial delay. The new evidence will inform treatment guidelines in MS and potentially contribute to regulatory as well as clinical decisions.”
Researcher Profile
Dagmawi Chilot is a lecturer of clinical trials at the University of Gondar, Ethiopia. He received his MSc in Clinical trials from Addis Ababa University, Center for Innovative Drug Development and Therapeutic Trials for Africa (CDT Africa), Ethiopia in 2021; and his BSc degree in Nursing from the University of Gondar, Ethiopia in 2016.
Dagmawi joined the University of Gondar as a graduate assistant II in 2016. Alongside his academic duties, he has been working as deputy coordinator of the University of Gondar Clinical Trial Centre, and a clinical data manager expert fellow of the Institute of Tropical Medicine in Antwerp, Belgium. He has been leading the data management team, and performing all the data management activities including developing paper CRFs, building GCP-compliant databases, developing data management plans and data validation plans,preparing data review overview, facilitating training in courses on GCP, GDP, and data management at the Leishmaniasis Research and Treatment Centre at the University of Gondar.
He has been engaged in several research projects and produced scientific publications in peer-reviewed journals. His research interest includes clinical trials, biostatistics, epidemiological research, clinical epidemiology research, research of treatment effectiveness, infectious diseases and chronic non-communicable diseases, and longitudinal data management and analysis.
Project Summary
Marginal structural models (MSM) are statistical methods that are used to estimate causal associations between therapies and outcomes outside of clinical trials. This is of particular importance in situations where a choice of therapy is determined by the severity of the disease such as multiple sclerosis. In a number of human diseases, there is an unmet need to evaluate causal associations, cleared of bias, between interventions and outcomes. The designs that are required to study the effect of different therapies on outcomes in multiple sclerosis using registry data extend beyond the present capabilities of the MSM methods. The shortcomings of the cohorts that complicate this research are many, such as variability in the time of patient enrolment, long-term nature of the effects of interventions, effects of interventions that occur with a delay of months to years, and simultaneous comparisons of multiple interventions. Observational registries have become one of the pillars of outcomes research in multiple sclerosis (MS).
In this PhD program, I am aiming to address the questions of long-term and delayed treatment effects and multiple treatment exposures in multiple sclerosis, using real-world registry data from the largest international MS registry – MSBase (containing clinical data from more than 90,000 patients from 150 centres in 43 countries). In order to achieve this goal, I will broaden the capabilities of the MSM methods beyond their present limitations.
Supervisors: Professor Tomas Kalincik, Dr Steve Simpson-Yap and Dr Izanne Roos.