BACKGROUND: There is little understanding on how often cardio-vascular events (heart attacks or stroke) happen, and on who is likely to suffer these. This is particularly challenging for patients with osteoporosis/fracture, and in users of anti-osteoporosis (fracture prevention) medications.
PURPOSE: 1.To estimate the risk of cardio-vascular events in patients diagnosed with osteoporosis/fracture, and in users of anti-osteoporosis medication; 2.To determine patient characteristics associated with high cardio-vascular risk; AND 3.To test whether existing models can predict cardio-vascular events in these patients.
DESIGN/METHODS: We will determine people with a diagnosis of osteoporosis/fracture, and users of anti-osteoporosis medication, and follow them to see if they develop cardio-vascular events. We will fit mathematical equations to identify patient characteristics (age, sex, obesity, etc) associated with increased cardiovascular risk. Finally, we will assess whether existing prediction tools are useful to calculate risk in these patients.
POTENTIAL IMPORTANCE: We will inform on the risk of cardio-vascular events in this particular group of patients, and determine key patient characteristics associated with cardio-vascular risk in this population. This research will inform patients and clinicians to target and treat patients at high cardio-vascular risk.
OBJECTIVES
1. To estimate incidence rates of cardio-vascular outcomes and mortality amongst osteoporotic, fractured, and users of anti-osteoporosis medication/s.
2. To test the feasibility and validity of existing cardio-vascular prediction tools
3. To fit multivariable models to identify risk factors associated with cardio-vascular outcomes.
METHODS
- Data sources: CPRD GOLD linked to HES-ONS data.
- Participants: three cohorts: 1.newly diagnosed with osteoporosis, 2.fracture, and 3.new users of anti-osteoporosis medication in 2000-2017, with 1+ year of data available.
- Classic cardio-vascular predictors (age, gender, body mass index, smoking and alcohol, cardiovascular history, type 2 diabetes, thrombo-embolic events, chronic kidney disease, estimated renal function, serum lipids, Charlson co-morbidity, socio-economic status, medications) as well as osteoporosis-specific ones (fracture/s history, diagnosed osteoporosis, steroids, and calcium±D supplements) will be studied.
- Outcomes: (1) myocardial infarction (MI), (2) stroke, (3) CVDeath, (4) Death, (5) MACE1 (first of MI, stroke, CVDeath), (6) MACE2 (first of MI, stroke, death of any cause)
- Follow-up: from first prescription/diagnosis to the earliest of death, transfer-out, or (for the drug user cohort) treatment cessation or switching
ANALYSIS: Incidence rates will be estimated. Multivariable Cox models will be used to identify risk factors. Validity measures for existing tools will be calculated including C statistics (discrimination) and observed/expected plots (calibration). All analyses will be stratified by cohort.
Primary: myocardial infarction (MI), stroke
- Secondary: cardio-vascular death
- MACE1 (first occurrence of cardiovascular death, MI, or stroke)
- All-cause mortality
- MACE2 (first occurrence of all-cause death, MI, or stroke)
Daniel Prieto-Alhambra - Chief Investigator - University of Oxford
Daniel Prieto-Alhambra - Corresponding Applicant - University of Oxford
Antonella Delmestri - Collaborator - University of Oxford
Emese Toth - Collaborator - UCB Biopharma SRL - Belgium Headquarters
Gary Collins - Collaborator - University of Oxford
Sara Khalid - Collaborator - University of Oxford
Victoria Y Strauss - Collaborator - University of Oxford
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation