Abstract
Ignoring competing risks in time-to-event analyses can lead to biased risk estimates, particularly for elderly patients with multimorbidity. We aimed to demonstrate the impact of considering competing risks when estimating the cumulative incidence and risk of stroke among elderly atrial fibrillation patients. Using linked administrative databases, we identified patients with atrial fibrillation aged ≥66 years discharged from hospital in ON, Canada between January 1, 2007, and March 31, 2011. We estimated the cumulative incidence of stroke hospitalization using the complement of the Kaplan-Meier function and the cumulative incidence function. This was repeated after stratifying the cohort by presence of prespecified comorbidities: chronic kidney disease, chronic obstructive pulmonary disease, cancer, or dementia. The full cohort was used to regress components of the CHA2DS2VASc (congestive heart failure, hypertension, age, diabetes mellitus, stroke, vascular disease, sex) score on the hazard of stroke hospitalization using the Fine-Gray and Cox methods. These models were subsequently used to predict the 5-year risk of stroke hospitalization. Among 136 156 patients, the median CHA2DS2VASc score was 4 and 84 728 patients (62.2%) h...Continue Reading
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