Estimating the incidence and key risk factors of cardiovascular disease in patients at high risk of imminent fracture using routinely collected real-world data from the UK

The objective of this work was to estimate the incidence rate of cardiovascular disease (CVD) events (myocardial infarction, stroke or CVD-death) at 1 year among 3 cohorts of patients at high risk of fracture (osteoporosis; previous fracture; and anti-osteoporosis medication), and to identify the key risk factors of CVD events in these three cohorts. To do so, this prospective cohort study used data from the Clinical Practice Research Datalink, a primary care database from United Kingdom. MACE events (a composite outcome for the occurrence of either myocardial infarction (MI), stroke or CVD death) were identified in patients aged fifty or over at high or imminent fracture risk identified in three different cohorts (not mutually exclusive): recently diagnosed with osteoporosis (OST, n=65,295), incident fragility fracture (IFX, n=80,587), and starting oral bisphosphonates (OBP, n=145,959). MACE incidence rates (cases/1000 person-years) were: 19.63 (18.54;20.73) in OST, 51.09 (49.39;52.80) in IFX, and 26.26 (25.41;27.12) in OBP cohorts. Candidate risk factors from QRISK tool, and candidates from literature selected by lasso regression, were fitted into prediction models to estimate 1-year risk of MACE for each cohort. OST and OBP models had a discrimination of ≥ 70% and IFX cohort ≥ 60%. Calibration plots showed good internal validity of the models. Generally, models from lasso regression were better than QRISK. Main risk factors common in all MACE models were sex, alcohol, atrial fibrillation, anti-hypertensive medication, age, prior MI/stroke, established CVD, glomerular filtration rate, systolic blood pressure, and number of GP visits and concomitant medicines. Incidence of MACE in the studied populations was 4.35% or lower, with IFX as the cohort with the higher risk. Identified key risk factors highlight the differences of patients at high risk of fracture versus general population. Proposed models could improve prediction of CVD events in patients with osteoporosis in primary care settings.