PROJECTING LIFE-YEARS GAINED FROM DIRECT-TO-CONSUMER ADVERTISING OF STATIN THERAPY

Purpose: To quantify the clinical benefits for the U.S. population associated with direct-to-consumer advertising (DTCA) of cholesterol testing and treatment.

Method: We developed a population model to project life-years gained over a 10-year time horizon. The U.S. population aged 35 to 84 was apportioned into 400 risk cells defined by low-density lipoprotein cholesterol (<100, 100-129, 130-159, 160-189, 190+ mg/dL), hypertension (yes or no), diabetes mellitus (yes or no), smoking status (yes or no), gender and ten-year age ranges. The probability of receiving statin therapy, conditional on DTCA status (yes or no), coronary artery disease status (yes or no), and other risk factors, was estimated from the Practice Partner Research Network data. These data described monthly diagnosis and treatment behavior for approximately 400,000 patients over an 8-year period. The effect of statin advertising, conditional upon demographic and clinical characteristics, was estimated via discrete time hazard models. Disease and risk factor prevalence was based on national surveys, and incidence and prognosis of coronary artery disease was based on the published literature. We integrated statins’ primary and secondary prevention on coronary artery disease event in our model on the basis of randomized trial results.

Result: We found that statin advertising increases statin utilization among relatively high-risk individuals. We projected that there would be 125,533 life-years gained over 10 years (baseline population is 138 million using the US Census 2000 data) with DTCA, compared to without DTCA. The results correspond to 0.0009 life-years gained per person. Stratified by age group, the life-years gained per person were 0.0003, 0.0009, 0.0015, 0.0021, and 0.0018 for men ages 35-44, 45-54, 55-64, 65-74, and 75-84, and 0.0001, 0.0005, 0.0014, 0.0019, and 0.0013 for women, respectively.

Conclusion: Life-years gained associated with DTCA vary with age, sex, and the presence or absence of additional risk factors. Although advertisements are beneficial, targeting on those high-risk groups will be more cost-effective.