The 'Data Analysis and Real World Interrogation Network (DARWIN EU)' is an initiative created by the European Medicines Agency (EMA) to generate timely evidence from healthcare data sources from across Europe.
One area of research relates to describing characteristics, such as age and sex, treatment options and mortality of people diagnosed with a condition of interest. The description of the characteristics, treatment options and mortality are important from a regulatory point of view to provide context and help understand how new medicines may add value for patients.
The EMA will request several studies of the same design to assess how common specific conditions are in the population and how many people die from these conditions. This will help the regulators to inform preventative measures that could be introduced to reduce disease spread or disease burden, and subsequently reduce risk for mortality for affected people wherever possible. The first example will focus on a relatively rare bone cancer, "chondrosarcoma", which every year affects between 1 to 5 people for every one million.
Primary care records provide a unique source of data for describing the characteristics of individuals diagnosed with specific diseases at a population-level, their specific drug treatments used in the community, and mortality rates in people affected by these diseases. The “Data Analysis and Real World Interrogation Network (DARWIN EU)” initiative created by the European Medicines Agency (EMA) intends to draw upon such data for regulatory decision making: such studies could help to assess disease burden in the population, understand the impact of measures to reduce mortality in affected patients and, for rare diseases, provide the possibility of faster approval of new, innovative treatments through a different regulatory pathway for orphan medicines. EMA will therefore request several studies assessing the natural history of diseases.
> Study design: Cohort study
> Population: people diagnosed with the disease of regulatory interest in CPRD GOLD or CPRD AURUM. Additional exclusion criteria may apply according to the study objective (including history of specific conditions and minimum follow-up time).
> Diseases of regulatory interest:
- Chondrosarcoma
Additional diseases of regulatory interest will be declared in future protocol amendments upon request by EMA.
> Covariates:
- Age
- Sex
- Calendar period/Time windows (to monitor changes over time)
- Other subgroups (such as specific disease sub-types and/or treatment regimen types)
- Patient specific characteristics in terms of comorbidity and use of concomitant medication at the time of interest.
> Analyses:
1) Summary of characteristics (demographics, comorbidities, comedication) of people diagnosed with the disease of regulatory interest.
2) Description of treatment options and sequences over time among people with new diagnoses of diseases of interest.
3) Estimation of mortality rates in people affected by the disease of regulatory interest, focussing on all-cause mortality or cause-specific mortality related to the respective disease of regulatory interest.
Summary characteristics (demographics, comorbidities, comedication) of people diagnosed with the disease of regulatory interest, treatment options and sequences over time, mortality rates (all-cause or disease-specific).
Daniel Prieto-Alhambra - Chief Investigator - University of Oxford
Marta Pineda Moncusi - Corresponding Applicant - University of Oxford
Albert Prats Uribe - Collaborator - University of Oxford
Annika Jodicke - Collaborator - University of Oxford
Antonella Delmestri - Collaborator - University of Oxford
Edward Burn - Collaborator - University of Oxford
Eng Hooi Tan - Collaborator - University of Oxford
Hezekiah Omulo - Collaborator - University of Oxford
Kim López-Güell - Collaborator - University of Oxford
Mandickel Kamtengeni - Collaborator - University of Oxford
Martí Català Sabaté - Collaborator - University of Oxford
Mike Du - Collaborator - University of Oxford
Wai Yi Man - Collaborator - University of Oxford
Xintong Li - Collaborator - University of Oxford
Yuchen Guo - Collaborator - University of Oxford
HES Admitted Patient Care