What is Real World Evidence - and why do we need it?

It is has been long established that it is essential to conduct randomized controlled studies as part of the drug development process. However, these “high-level evidence” studies are not always sufficient to get approval from the regulatory bodies. Often, additional evidence from so-called “Real World Evidence” studies is required. Our senior consultant Robert Szulkin explains below.

Real world evidence (RWE) – what does it really mean?  As it turns out, currently, there is no consensus in the scientific community on accurate definition of an RWE study. However, I think most people would agree that the RWE studies can be classified as non-interventional as opposed to the randomized clinical trials. In these studies, patients are followed in the real clinical world. More specifically, their health-related data, known as real world data (RWD) appear in different electronically generated health-records registers, such as hospital registers, national healthcare and quality registers, etc.

In other words, RWE studies are observational studies on patients, who are treated according to standard practice guidelines outside of clinical trials. The spectrum of the research questions that are studied within the RWE study is very broad, and spans everything from a drug’s effectiveness and patient profiling to health economics.

Why do we need RWE-studies? 

In particular, RWE studies are used to complement clinical trials, as there is a possibility to answer questions that cannot be answered through clinical trials. How does a drug work in real clinical practice, where many patients switch treatments several times? How does a drug perform in a non-selected patient group? Another big advantage is the possibility to study groups of patients that have been excluded from clinical trials. For example, pregnant patients, elderly, patients with multiple morbidities, or patients that have other ongoing treatments.

 

 

Woman working in clinical trialsRWE and Clinical trials are great complements to each other

RWE studies are great complements to clinical trials

In particular, RWE studies are used to complement clinical trials, as there is a possibility to answer questions that cannot be answered through clinical trials. How does a drug work in real clinical practice, where many patients switch treatments several times? How does a drug perform in a non-selected patient group? Another big advantage is the possibility to study groups of patients that have been excluded from clinical trials. For example, pregnant patients, elderly, patients with multiple morbidities, or patients that have other ongoing treatments.

RWE offers larger study designs and longer follow-up

Which cancer drug is given in the first, second or third line of cancer treatment? Which drug or combination of drugs prolongs overall survival? Which side effects from a treatment occur over a long period of time? When clinical trials are analysed, the follow-up is often limited, and therefore interim outcomes (such as time to disease progression – progression-free survival, PFS) are used instead of actual long-term outcomes, such as overall survival and adverse events. On the other hand, using the real world data that contain longer follow-up periods (10-20 years), it is possible to study long-term outcomes, such as survival and adverse events. Furthermore, to find out whether a drug has any rare side effects, we need to study a large population, which is usually possible within the RWE study.

 

Health economic analysis is also an important component in an RWE study. How much does the entire treatment cost for a care-giver, for society in general? Can a new drug decrease the number of side effects and comorbidities, hence also the amount of hospital admissions and costs? How many high-quality life years can a patient gain with a new drug? And does it bring any reduction in intangible costs for society in terms of fewer sickness absence days and reduce care burden on their loved ones?

 

Robert Szulkin

Senior Consultant in Statistics

We use cookies to ensure that we give you the best experience on our website. Read our cookie policy here.