Real-World Evidence (RWE)

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A Real-World Evidence (RWE) is evidence that is based on real-world data.



References

2021

  • (Wikipedia, 2021) ⇒ https://en.wikipedia.org/wiki/Real_world_evidence Retrieved:2021-12-10.
    • Real world evidence (RWE) in medicine means evidence obtained from real world data (RWD), which are observational data obtained outside the context of randomized controlled trials (RCTs) and generated during routine clinical practice. RWE is generated by analyzing data which is stored in electronic health records (EHR), medical claims or billing activities databases, registries, patient-generated data, mobile devices, etc. It may be derived from retrospective or prospective observational studies and observational registries. In the USA the 21st Century Cures Act required the FDA to expand the role of real world evidence.

      Real World Evidence comes into play when clinical trials cannot really account for the entire patient population of a particular disease. Patients suffering from comorbidities or belonging to a distant geographic region or age limit who did not participate in any clinical trial may not respond to the treatment in question as expected. RWE provides answers to these problems and also to analyze effects of drugs over a longer period of time. Pharmaceutical companies and Health Insurance Payers study RWE to understand patient pathways to deliver appropriate care for appropriate individuals and to minimize their own financial risk by investing on drugs that work for patients.

2018

  • (Suvarnaamesh, 2018) ⇒ Viraj R. Suvarnaamesh. (2018). “Real World Evidence (RWE) - Are We (RWE) Ready?. ” Perspectives in Clinical Research, 9(2).
    • QUOTE: ... What is real-world evidence? Obviously, evidence that is generated or exists in the real world. Why is it important? Typically, evidence generated within a randomized controlled clinical trial (RCT) is considered higher than that in the real world. Where hypotheses are generated double blinding and randomization (which ensures every patient has an equal chance of being allocated to treatment A or treatment B) are ways of ensuring that comparable cohorts are created, and bias is minimized to the extent possible. Naturally, a hypothesis can be tested within an RCT. However, there are limitations of an RCT. For example, in an RCT, there are inclusion and exclusion criteria. These eligibility criteria ensure that a homogeneous and representative sample is collected. However, in the real world, can any patient be excluded? Data from an RCT can only be extrapolated to the kind of patients who were eligible for the RCT. Hence, there are limitations of generalizability. Moreover, that is where real-world evidence comes in, to supplement data from RCTs, and hopefully bridge the gap between the controlled environment of an RCT and the harsh realities of the real world. (Nallamothu et al., 2008) ...

      ... In an ideal world, both the RCT and real-world evidence coexist and one can even do large simple studies, where the two elements are blended such that the results do mirror what happens in the real world. Such hybrid, efficacy-effectiveness studies can help in advancing a closer correlation to the real world within a clinical development program. However, real-world studies are fraught with their own limitations. Can one randomize in the real world? What about retrospective analyses of databases (electronic medical records) in the real world or comparative effectiveness research? They have their uses viz., in comparing the cost-effectiveness of two regimens in the real world, beyond the rigors of an RCT. ...