High-dose statin therapy in patients with stable coronary artery disease: treating the right patients based on individualized prediction of treatment effect

Johannes A. N. Dorresteijn, S. Matthijs Boekholdt, Yolanda van der Graaf, John J. P. Kastelein, John C. LaRosa, Terje R. Pedersen, David A. Demicco, Paul M. Ridker, Nancy R. Cook, Frank L. J. Visseren

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Abstract

Clinicians need to identify coronary artery disease patients for whom the benefits of high-dose versus usual-dose statin therapy outweigh potential harm. We therefore aimed to develop and validate a model for prediction of the incremental treatment effect of high-dose statins for individual patients in terms of reduction of 5-year absolute risk for myocardial infarction, stroke, coronary death, or cardiac resuscitation. Based on data from the Treating to New Targets trial (TNT; n=10 001), a Cox proportional hazards model was developed comprising 13 easy-to-measure clinical predictors: age, sex, smoking, diabetes mellitus, total cholesterol, high-density lipoprotein cholesterol, systolic blood pressure, history of myocardial infarction, coronary artery bypass grafting, congestive heart failure or abdominal aortic aneurysm, glomerular filtration rate, and treatment status (ie, atorvastatin 80 mg or 10 mg). External validation in the Incremental Decrease in End Points Through Aggressive Lipid Lowering trial (IDEAL; n=8888) confirmed adequate goodness-of-fit and calibration, but moderate discrimination (C-statistic, 0.63; 95% confidence interval, 0.62-0.65). Still, among participants of both trials combined, the model identified a group of 11.7% whose predicted 5-year number needed to treat was ≤25 and a group of 41.9% whose predicted needed to treat was ≥50. A decision curve shows that making treatment decisions on the basis of predictions using our model may improve net benefit. Estimation of the incremental treatment effect of high-dose versus usual-dose statin therapy in individual coronary artery disease patients enables selection of high-risk patients that benefit most from more aggressive therapy. http://www.clinicaltrials.gov. Unique identifiers: NCT00327691 and NCT00159835
Original languageEnglish
Pages (from-to)2485-2493
JournalCirculation
Volume127
Issue number25
DOIs
Publication statusPublished - 2013

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