Background-: Drug-eluting stents (DES) for percutaneous coronary intervention decrease the risk of restenosis compared with bare metal stents. However, they are costlier, require prolonged dual antiplatelet therapy, and provide the most benefit in patients at highest risk for restenosis. To assist physicians in targeting DES use in patients at the highest risk for target vessel revascularization (TVR), we developed and validated a model to predict TVR. Methods and Results-: Preprocedural clinical and angiographic data from 27 107 percutaneous coronary intervention hospitalizations between October 1, 2004, and September 30, 2007, in Massachusetts were used to develop prediction models for TVR at 1 year. Models were developed from a two-thirds random sample and validated in the remaining third. The overall rate of TVR was 7.6% (6.7% with DES, 11% with bare metal stents). Significant predictors of TVR included prior percutaneous coronary intervention, emergency or salvage percutaneous coronary intervention, prior coronary bypass surgery, peripheral vascular disease, diabetes mellitus, and angiographic characteristics. The model was superior to a 3-variable model of diabetes mellitus, stent diameter, and stent length (c statistic, 0.66 versus 0.60; P<0.001) and was well calibrated. The predicted number needed to treat with DES to prevent 1 TVR compared with bare metal stents ranged from 6 (95% confidence interval, 5.4-7.6) to 80 (95% confidence interval, 62.7-116.3), depending on patients' clinical and angiographic factors. Conclusions-: A predictive model using commonly collected variables can identify patients who may derive the greatest benefit in TVR reduction from DES. Whether use of the model improves the safety and cost-effectiveness of DES use should be tested prospectively.
- coronary intervention
- outcome assessment