2.5 Statistical analysis
The chi-square test and t-test were used to examine the differences in
patients’ characteristics between the case group and control group. We
performed conditional logistic regression models to estimate the odds
ratio (OR) and 95% confidence interval (CI) for UGIB in users of each
SSRI, with non-users of that individual SSRI as the reference. The
models were adjusted for age, sex, comorbidities, and medications used
in order to control the potential confounders. The comorbidities
included diabetes, hypertension, dyslipidemia, coronary artery disease,
chronic obstructive lung disease, chronic kidney disease, end-stage
renal disease, liver cirrhosis, and cancer (Table S1). Previous
medications used included antiplatelet agents, oral anticoagulant
medications, and nonsteroidal anti-inflammatory drugs (NSAIDs) (Table
S2). Regression models were performed repeatedly, using cDDD as the
independent variable for each generic SSRI. Same models were also
applied using the time between last prescription for SSRIs and the index
date as the independent variable, to assess the UGIB risk related to
current and recent exposures. All analyses were performed using SAS 9.4
version. Two-sided tests were used to determine the significance at the
5% level.
RESULTS