DARWIN EU(c) is an initiative created by the European Medicines Agency (EMA) to generate timely evidence from real-world healthcare data sources from across Europe. One area of research relates to estimating how common certain conditions are, or how often some events occur. Usual measures of this are called incidence. Regulators are interested to have measures of incidence of conditions known to be caused by medicines, also known as designated medical events, as these can be used to monitor the safety of new medicines and/or vaccines.
Our objective is therefore to calculate the incidence of designated medical events. We will first create algorithms to identify people who suffer a designated medical event based on codes recorded in GP records, and describe the characteristics of the people affected. We will then calculate incidence of designated medical events in the general population as the number of people newly diagnosed with these conditions in a specific time period. We will calculate these in specific populations of interest based on age and sex groups, and over calendar years to look at trends over time
Designated medical events (DMEs) are serious adverse events that are often causally associated with medications. We aim to create algorithms to define DMEs, and to estimate background incidence rates of 49 DMEs for regulatory purposes.
Study design
Population-based cohort study
Population
All people in CPRD GOLD or CPRD AURUM with >=1 year of prior history will be eligible, with sensitivity analyses using different prior history requirements.
Variables
Study outcomes will include the DMEs defined by the EMA as of June 2020. DMEs will be defined based on pre-specified diagnosis or other codes.
Outcomes
DMEs of interest have been published by the EMA, and include: Acute Hepatic Failure, Acute Kidney Injury, Agranulocytosis, Anaphylaxis, Angioedema, Aplastic anaemia, Autoimmune haemolytic anaemia, Autoimmune hepatitis, Autoimmune pancreatitis, Azotaemia, Blindness, Bone marrow failure, Deafness, Exfoliative dermatitis, Drug reaction with eosinophilia and systemic symptoms, Drug-induced liver injury, Erythema multiforme, Febrile neutropenia, Granulocytopenia, Haemolysis, Haemolytic anaemia, Hepatic failure, Hepatic infarction, Hepatitis fulminant, Immune thrombocytopenia, Intestinal perforation, Neutropenic colitis, Neutropenic infection, Optic ischemic neuropathy, Pancreatitis, Acute pancreatitis, Pancytopenia, Progressive multifocal leukoencephalopathy, Pulmonary arterial hypertension, Pulmonary fibrosis, Pulmonary hypertension, Red cell aplasia, Renal failure, Reye’s syndrome, Rhabdomyolysis, Stevens-Johnson syndrome, Sudden cardiac death, Sudden hearing loss, Sudden visual loss, Thrombotic thrombocytopenic purpura, Toxic epidermal necrolysis, Toxic optic neuropathy, Torsade de Pointes, Ventricular fibrillation
Analyses
We will first establish the algorithms to define DMEs in CPRD data by conducting literature reviews and utilizing the existing webtools to obtain relevant codes. We then will apply the algorithms to CPRD datasets to compare and evaluate the performance by reviewing the clinical features of the patients and consulting with clinicians. Incidence rates will be estimated for all the DMEs, using a pre-specified 1-year washout period. Analyses will be stratified by age, sex, and calendar year.
The outcomes of interest are DME’s as defined by the European Medicines Agency (EMA) as of June 2020 (the list can be consulted at https://www.ema.europa.eu/en/documents/other/designated-medical-event-d…) The following outcomes will be studied, although additional outcomes might be studied with subsequent amendments including new DME’s as proposed by EMA:
1. Acute Hepatic Failure
2. Acute Kidney Injury
3. Agranulocytosis
4. Anaphylaxis
5. Angioedema
6. Aplastic anaemia
7. Autoimmune haemolytic anaemia
8. Autoimmune hepatitis
9. Autoimmune pancreatitis
10. Azotaemia
11. Blindness
12. Bone marrow failure
13. Deafness
14. Exfoliative dermatitis
15. Drug reaction with eosinophilia and systemic symptoms
16. Drug-induced liver injury
17. Erythema multiforme
18. Febrile neutropenia
19. Granulocytopenia
20. Haemolysis
21. Haemolytic anaemia
22. Hepatic failure
23. Hepatic infarction
24. Hepatitis fulminant
25. Immune thrombocytopenia
26. Intestinal perforation
27. Neutropenic colitis
28. Neutropenic infection
29. Optic ischemic neuropathy
30. Pancreatitis
31. Acute pancreatitis
32. Pancytopenia
33. Progressive multifocal leukoencephalopathy
34. Pulmonary arterial hypertension
35. Pulmonary fibrosis
36. Pulmonary hypertension
37. Red cell aplasia
38. Renal failure
39. Reye’s syndrome
40. Rhabdomyolysis
41. Stevens-Johnson syndrome
42. Sudden cardiac death
43. Sudden hearing loss
44. Sudden visual loss
45. Thrombotic thrombocytopenic purpura
46. Toxic epidermal necrolysis
47. Toxic optic neuropathy
48. Torsade de Pointes
49. Ventricular fibrillation
A list of proposed codes to identify the outcomes can be found in the Appendix.
We will use the following characteristics of the participants for stratified analyses: sex, age, observation time prior to their index date, and index year.
Daniel Prieto-Alhambra - Chief Investigator - University of Oxford
Daniel Prieto-Alhambra - Corresponding Applicant - University of Oxford
Albert Prats Uribe - Collaborator - University of Oxford
Annika Jodicke - Collaborator - University of Oxford
Antonella Delmestri - Collaborator - University of Oxford
Daniel Dedman - Collaborator - CPRD
Edward Burn - Collaborator - University of Oxford
Junqing Xie - Collaborator - University of Oxford
Martí Català Sabaté - Collaborator - University of Oxford
Xintong Li - Collaborator - University of Oxford
Zara Cuccu - Collaborator - CPRD
HES Admitted Patient Care