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.
April 2021 Publication
Eric Sanders, Paul Gustafson and Mohammad Ehsanul Karim have published a paper based on their work on Developing & Evaluating Causal Inference Methods for Pragmatic Trials.
Sept 2020 Publication
The team behind the project, Embedding Patient Values in Randomized Control Trials: A Case Study have published a paper based on their work asking pregnant women who have high blood pressure to identify, and then rank, a list of things that affect their decision which treatment they prefer.
June 2020 Publication
The project, Evidence Synthesis of Pragmatic Clinical Trial Methodology, asked: how do we calculate how many participants are needed in clinical trials? And what is the correct way to analyze our data?
On June 24, 2020, the team published a paper exploring some of their findings:
Read about "Explaining the variation in the attained power of a stepped-wedge trial with unequal cluster sizes" in BMC.
- Addressing real world limitations: making trials feasible and efficient in real world settings (constraints on blinding, randomization, sample size, operational procedures, ethical considerations).
- Enhancing generalizability and individualized treatment: ensuring treatment needs in the broad population are addressed but with a focus on individual patient priorities (PROMs) and needs (precision medicine).
- Leveraging external information sources: making use of non-trial information (published literature, health databases/medical records, expert opinion) to get answers more quickly and enhance the value of a trial.
Projects in this Cluster
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).