A primer on Real-World Evidence (RWE) and Real-World Data (RWD)
Nancy Banoub?? RPh BSc pharm, MSCS, CPGx
Multiple sclerosis certified specialist|Speaker| specialty pharmacist | pharmacy podcast top 50 most influential pharmacy leaders| pharmacogenomics|oncology| mentor| digital writer|content creator |KOL| thought leader
Randomized controlled clinical trials (RCTs) have been the gold standard for demonstrating the efficacy and safety of drugs. In RCTs drugs are administered to carefully selected patients who are closely monitored for both drug efficacy and safety . Once approved the drug then reaches a much more diverse patient population, e.g., patients of different races or ethnicities, a wider age range and with different co-morbidities. This broader use generates new data “real world data” (RWD) and insights “real world evidence” (RWE) about drug efficacy and adverse events that were not apparent in the selected RCT group.
Data collection is a routine procedure during drug development. However, structured data collection from the real-world usage of the drug post marketing approval is largely restricted to regulatory safety data collection in the form of pharmacovigilance. The collection of date about efficacy and safety is crucial to help improve the healthcare decision making. Hence, RWD.
Definitions :
Real-world data (RWD) are data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources.
Real-world evidence (RWE) is the clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD, that is not part of randomized control trials (RCTs)”
To tie them together,
Real-world evidence (RWE) is clinical evidence on a medication’s safety and efficacy that is generated using real-world data (RWD) resulting from routine healthcare delivery.
With the rapid increase in the use of technology, such as biosensors, and healthcare wearable devices , has led to the accumulation of large amounts of RWD. Which have been used in research for post marketing surveillance in addition to monitoring disease progression through natural disease history studies.
Some Sources of RWD may include :
? Medical and billing claims.
? Clinical studies.
? Laboratory test.
? Electronic health records.
? Pharmacy prescription data.
? Social media.
? Adverse events reporting.
The hierarchy of evidence:
Advantages of RWE:
? No strict eligibility criteria, and thus fewer chances of no exclusions based on concomitant medications and comorbidities.
? Quicker, cost-effective: less time required for patient recruitment/enrolment and completing the research.
? RWE studies can be used to support patient outcomes and health economics
? RWE studies can be used to understand current health-care services
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? Rapid and more straightforward retrieval of and access to data.
Limitations of RWE:
? Inconsistency or inadequate clinical information.
? Increased bias due to non-randomized design.
? Possible Underreporting.
? Lack of patients’ genetics, socioeconomic status, health habits and lifestyle.
RWE complements the RCTs to understand observations and events in patients in routine clinical practice, and help to fill in the missing gaps in the complete knowledge about the intervention.
Comparison of evidence generated from randomized controlled trials (RCT) and real-world evidence:
conclusion :
Data obtained from real-world studies have an integral role in evidence-based medicine, serving as an essential source of safety information and a complement to efficacy data from RCTs. RWE is particularly useful for expanding the evidence base to encompass populations of patients who are not well represented in RCTs but who may benefit from the interventions in question. RWE is also critical in the setting of complex or rapidly evolving treatments, where RCT design cannot answer all the relevant questions. While RWE has many uses, it also has many limitations. Efforts are being made by regulators and other groups to develop best practices for the mitigation of common biases in the design of real-world studies.
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