title: Predicting restenosis of drug-eluting stents placed in real-world clinical practice: derivation and validation of a risk model from the EVENT registry.
abstract: BACKGROUND
  Prediction of restenosis after percutaneous coronary intervention (PCI) remains challenging, and existing risk assessment algorithms were developed before the widespread adoption of drug-eluting stents (DES).
  
  
  RESULTS
  We used data from the EVENT registry to develop a risk model for predicting target lesion revascularization (TLR) in 8829 unselected patients undergoing DES implantation between 2004 and 2007. Using a split-sample validation technique, predictors of TLR at 1 year were identified from two thirds of the subjects (derivation cohort) using multiple logistic regression. Integer point values were created for each predictor, and the summed risk score (range, 0 to 10) was applied to the remaining sample (validation cohort). At 1 year, TLR occurred in 4.2% of patients, and after excluding stent thrombosis and early mechanical complications, the incidence of late TLR (more likely representing restenosis-related TLR) was 3.6%. Predictors of TLR were age <60, prior PCI, unprotected left main PCI, saphenous vein graft PCI, minimum stent diameter < or =2.5 mm, and total stent length > or =40 mm. Comparison of observed versus predicted rates of TLR according to risk score demonstrated good model fit in the validation set. There was more than a 3-fold difference in TLR rates between the lowest risk category (score=0; TLR rate, 2.2%) and the highest risk category (score > or =5; TLR rate, 7.5%).
  
  
  CONCLUSIONS
  The overall incidence of TLR remains low among unselected patients receiving DES in routine clinical practice. A simple risk model incorporating 6 readily available clinical and angiographic variables helps identify individuals at extremely low (<2%) and modestly increased (>7%) risk of TLR after DES implantation.
authors.affiliation: Saint Luke's Mid America Heart Institute, Kansas City, MO 64111, USA.
authors.forename: Joshua M
authors.initials: JM
authors.lastname: Stolker
authors.forename: Kevin F
authors.initials: KF
authors.lastname: Kennedy
authors.forename: Jason B
authors.initials: JB
authors.lastname: Lindsey
authors.forename: Steven P
authors.initials: SP
authors.lastname: Marso
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Pencina
authors.forename: Donald E
authors.initials: DE
authors.lastname: Cutlip
authors.forename: Laura
authors.initials: L
authors.lastname: Mauri
authors.forename: Neal S
authors.initials: NS
authors.lastname: Kleiman
authors.forename: David J
authors.initials: DJ
authors.lastname: Cohen
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D017130:Angioplasty; D002406:Catheterization, Peripheral; D003324:Coronary Artery Disease / Q000175:diagnosis* / Q000473:pathology / Q000503:physiopathology / Q000628:therapy*; D023903:Coronary Restenosis / Q000209:etiology* / Q000517:prevention & control; D054855:Drug-Eluting Stents / Q000009:adverse effects*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D011183:Postoperative Complications; D011379:Prognosis; D018570:Risk Assessment; D012986:Software Validation