🇬🇧 Real world data for real world evidence in cancer

Abstract

Cancer is one of the biggest public health problems of the millennium. Currently, the International Agency for Research on Cancer (IARC) predicts a number of over 35 million new cancer cases for 2050, which represents a 77% increase from the estimated 20 million cases in 2022. The rapidly growing global cancer burden stresses the need for a better understanding of these conditions in order to promote its prevention and improve treatment.

Real World Data (RWD) refers to data related to patient health status and/or the delivery of health care routinely collected from diverse sources, including electronic health records (EHR), medical claims and billing data, and data from product or disease registers. The use of RWD in epidemiology and clinical research has received growing attention in recent years, including in oncology research, as it contain large volume of data from real-world settings and can offer a complementary approach to population surveys and clinical trials. Clinical evidence derived from the analysis of RWD is often referred as real-world evidence (RWE).

The potential value of RWD lies on the large volume data, the collection of information from real-world settings, and the lower cost compared to controlled trials and cohort studies. In this talk, I will describe some initiatives to conduct federated analysis of multiple real-world databases across Europe in order to generate RWE that can inform decision-making.

I will describe the Observational Medical Outcomes Partnership (OMOP) Common Data Model used to perform standardized analytics, the EHDEN initiative, and the DARWIN EU Coordinating Center for the European Medicines Agency with some examples of studies conducted in the field of oncology.