A history of at least 6 months was used to develop a logistic regression model to provide a propensity score for each patient and measure the likelihood of receiving a COX-2 inhibitor as a function of demographics (age, sex, and race), clinical indications, and cardiovascular risk factors. Covariates for clinical indications favoring COX-2 inhibitor use were history of GI problems, osteoarthritis, rheumatoid arthritis, back pain, or acute pain. Cardiovascular risk factors included as covariates were a diagnosis for hypertension, hyperlipidemia, obesity, diabetes, renal problems, and alcohol, tobacco, or other drug abuse. A prior occurrence of the primary outcome variable, a cardiovascular event, was also included. All diagnosis data were derived from the first 3 digits of the primary and secondary codes in the International Classifications of Diseases, Ninth Revision (ICD-9) that were recorded in the medical encounter form. The date of diagnosis was taken as the first date of service for the earliest ICD-9 code that qualified the patient as having a given diagnosis (the qualifying ICD-9 codes used for each diagnosis are 531-537, 555-556, 562, 564, 569, and 578 for GI problems; 724-725 for back pain; 714 for rheumatoid arthritis; 715 for osteoarthritis; 716, 719, 726, 727, 729, 844, and 845 for acute pain; 250 for diabetes; 278 for obesity; 272 for hyperlipidemia; 291, 303, and 305 for tobacco, alcohol, or drug abuse; 401-404 for hypertension; and 581-585 for renal problems). Age interactions with each of these variables were also included in the model.