Real-world evidence (RWE) is the clinical evidence derived from the analysis and/or synthesis of real-world data (RWD).
RWD is commonly referred to as data gathered from routine clinical practice (such as data on drug effectiveness). However, there is still no clear consensus on the definition of RWD. Although most stakeholders define it as “data collected in a non-RCT setting”, definitions related to “non-interventional/non-controlled setting” and “non-experimental setting” are also common1.
GetReal consortium2 is a project of the Innovative Medicines Initiative (IMI)3 aimed at incorporating real-life clinical data into drug development. GetReal bridged together key stakeholder groups and developed new tools and resources to support the use of RWE.
According to IMI-GetReal definition1,
“real-world data is an umbrella term for data regarding the effects of health interventions (e.g., benefit, risk, and resource use) that are not collected in the context of conventional RCTs. Instead, RWD are collected both prospectively and retrospectively from observations of routine clinical practice. Data collected include, but are not limited to, clinical and economic outcomes, patient-reported outcomes, and health-related quality of life. RWD can be obtained from many sources including patient registries, electronic medical records, and observational studies”
In the light of this definition, studies providing RWE can be roughly divided into three categories:
- Observational studies using existing RWD sources
- Observational studies with prospective data collection
- Specially designed experimental studies
RWD sources related to the first two categories comprise healthcare databases, patient registries, administrative claims records, biobanks, birth or death registries, surveillance databases, patient-powered research networks, data gathered from mobile devices, social media, etc. Retrospective data collection can be associated with some challenges and limitations regarding the quality of information obtained (e.g., data accuracy, completeness, consistency, and representativeness), and both prospective and retrospective observational studies can suffer from confounding issues.
The third category encompasses several study designs4, including
- Pragmatic trials with their subtypes: cohort multiple RCTs, cluster RCTs, and comprehensive cohort studies
- Population enrichment RCTs
- Non-randomized controlled trials
Pragmatic trials can utilize randomization schemes and be therefore designed to control for allocation bias. Moreover, these trials may incorporate other characteristics of conventional RCTs, such as blinded assessment of outcomes. At the same time, pragmatic trials, in contrast to “explanatory” trials, mimic usual clinical practice: they may apply inclusive eligibility criteria, use standard care as the control arm, follow patients over a more extended period, or otherwise approximate real-life conditions. Levels of pragmatism can be different, so pragmatic and explanatory trials are sometimes considered as a continuum.
How RWE is used?
RWE is important at many steps of drug development process. First, RWE is used to clarify real-world unmet needs, to determine disease burden and cost, and to study its natural history. RWE may guide clinical development strategies and help to choose proper clinical trial design5. Secondly, studies producing RWE have a potential to facilitate rare disease research, where traditional RCTs are often infeasible6. For some orphan drugs, efficacy has been demonstrated based on RWE7,8. Thirdly, RWE is used in post-approval drug safety assessment and pharmacovigilance. It can also inform about individual treatment choices in clinics and propose new indications of medical products. Last but not least, RWE answers important questions on clinical effectiveness of interventions. Conventional phase III RCTs provide evidence on intervention efficacy to support regulatory marketing decisions, but this evidence is not enough to fully guide clinicians and policy makers in choosing the optimal treatment9. Under the usual circumstances of health care practice, treatment effect can be modified due to both biological (genomics and environment) and behavior (physician prescribing and patients’ adherence) factors10 – a problem known as the “efficacy–effectiveness gap”. RWE can complement evidence acquired in RCTs and support decisions about care for routine patients.
Today, interest in RWE is growing. In the United States, the 21st Century Cures Act passed in 2016 placed additional focus on the use of RWE to support regulatory decision making11. In China, important governmental initiatives have been implemented, including the China Hospital Pharmacovigilance System and the China Health Policy Evaluation and Technology Assessment Network12.
 Makady A, et al. What Is Real-World Data? A Review of Definitions Based on Literature and Stakeholder Interviews. Value Heal 2017;20:858–65. http://dx.doi.org/10.1016/j.jval.2017.03.008
 RWE Navigator. What is the IMI GetReal project? https://rwe-navigator.eu/what-is-the-imi-getreal-project/
 Innovative Medicines Initiative. https://www.imi.europa.eu/
 RWE Navigator. Generate real-world evidence. https://rwe-navigator.eu/use-real-world-evidence/generate-real-world-evidence/
 Miksad RA and Abernethy AP. Harnessing the Power of Real-World Evidence (RWE): A Checklist to Ensure Regulatory-Grade Data Quality. Clin Pharmacol Ther 2018;103:202–5. http://dx.doi.org/10.1002/cpt.946
 Potter BK, et al. Translating rare-disease therapies into improved care for patients and families: what are the right outcomes, designs and engagement approaches in health-systems research? Genet Med 2016;18:117–23. http://dx.doi.org/10.1038/gim.2015.42
 Sasinowski FJ, et al. Quantum of Effectiveness Evidence in FDA’s Approval of Orphan Drugs. Ther Innov Regul Sci 2015;49:680–97. http://dx.doi.org/10.1177/2168479015580383
 Jarow JP, et al. Multidimensional Evidence Generation and FDA Regulatory Decision Making. JAMA 2017;318:703. http://dx.doi.org/10.1001/jama.2017.9991
 Zuidgeest MGP, et al. Series: Pragmatic trials and real world evidence: Paper 1. Introduction. J Clin Epidemiol 2017;88:7–13. http://dx.doi.org/10.1016/J.JCLINEPI.2016.12.023
 Eichler HG. Addressing the Efficacy-Effectiveness gap. https://www.ema.europa.eu/documents/presentation/presentation-addressing-efficacy-effectiveness-gap-prof-eichler_en.pdf
 U.S. Food and Drug Administration. Real World Evidence. https://www.fda.gov/scienceresearch/specialtopics/realworldevidence/default.htm
 Sun X, et al. Real world evidence: experience and lessons from China. BMJ 2018;360:j5262. http://dx.doi.org/10.1136/bmj.j5262