A clinical trial is research study that prospectively assigns humans to one or more intervention(s) to evaluate the effects on health outcomes (World Health Organization, 2020). Traditionally conducted in an idealized settings to give an intervention its best chance to demonstrate a beneficial effect; often involving: narrow patient populations; well-controlled settings, interventions delivered by experts; close monitoring during study follow-up; emphasizes one primary outcome (often clinical efficiency).
A real world clinical trial is a trial intended to answer how well interventions work beyond the confines of a clinical trial setting. They seek to include broad patient populations; deliver interventions in usual care settings using minimal extra resources; evaluate multiple outcomes that are important to patients.
In reality, there isn’t a defined set of things we can do to make a clinical trial representative of everyday settings. Real world clinical trials try their best to represent everyday care settings the best they can. However, the degree to which they accurately represent everyday settings will vary depending on what they are compared to.
September 2020 | Publication
Read the latest paper from the “Embedding Patient Values in Randomized Control Trials: A Case Study”
Go to the article.
June 2020 | Publication
Read the latest paper from the “Evidence Synthesis of Pragmatic Clinical Trial Methodology”.
Go to the article
Projects in This ClusterProjects are coded by colour to the themes listed above.
Embedding Patient Values in Randomized Control Trials: A Case Study
Project Leads: Joel Singer and Nick Bansback
It isn't easy for to figure out which treatment is best for a medical condition or illness. Usually, researchers compare different options for treatment by looking at the results of the treatments on more than one factor or outcome (e.g. pain and stiffness and fatigue). When these outcomes are grouped ... read more
Developing & Evaluating Causal Inference Methods for Pragmatic Trials
Project Lead: Mohammad Ehsanul Karim
In medical research, to find out whether a treatment works for a disease typically depends on comparing the results of two groups of people; those who get the treatment versus those who do not, ideally in a clinical trial. To avoid bias in results, researchers who design clinical trials make ... read more
How to analyze and present work productivity loss due to health problems in clinical trials?
Project Lead: Wei Zhang
Health problems can have an adverse impact on work productivity of patents and their caregivers. Patients and caregivers might have to stop working, reduce their routine work hours, miss work days, or not able be perform their work at their full capacity. Work productivity loss has been considered as an ... read more
Ethical Design and Data Integrity for Cluster Trials: A Framework
Project Lead: Anita Ho & Kip Kramer
Summary coming soon!
Evidence Synthesis of Pragmatic Clinical Trial Methodology
Project Lead: Hubert Wong
Clinical trials are used to test new treatments, interventions, or tests on participants in order to determine their effects. The beginning of every clinical trial is its design, which involves making decisions about how participants will be assigned to treatment groups, how many participants are needed, and how the ... read more
Increasing statistical efficiency in RWCTs
Project Lead : Hubert Wong
The goal of this project is to develop and test new ways of designing and analyzing medical research studies so that they are more efficient by needing fewer participants and less resources. Two different methods of increasing efficiency will be used. The first method will be to improve how research teams ... read more
Improving the efficiency and robustness of statistical inference for patient-oriented treatment effect in real-world clinical trials
Research Lead: Hui Xie
The randomized clinical trials (RCT) is the preferred study design for assessing causal effects of medical interventions. A patient and their treatment decision makers are often interested in intervention efficacy that informs what to expect when the patient actually complies with treatment. In many real-world ... read more
Cluster Lead | Hubert Wong
Dr. Wong is seconded to the Unit from the University of British Columbia (UBC), where he is an Associate Professor at the School of Population and Public Health, Program Head of Biostatistics at the Centre for Health Evaluation and Outcome Sciences (CHÉOS), and Associate Head of Methodology and Statistics at the Canadian Institutes of Health Research (CIHR) Canadian HIV Trials Network (CTN).