Risk of restenosis and health status outcomes for patients undergoing percutaneous coronary intervention versus coronary artery bypass graft surgery.

BACKGROUND: Previous comparisons of percutaneous coronary interventions (PCIs) and coronary artery bypass graft (CABG) surgery have demonstrated similar survival but have also generally found better health status outcomes (symptoms, function, and quality of life) with CABG. The principal limitation of PCI has been the occurrence of restenosis. No previous studies comparing the health status outcomes of PCI and CABG have examined differences in these outcomes as a function of patients' preprocedural risk for restenosis. METHODS AND RESULTS: We examined the health status outcomes, using the Seattle Angina Questionnaire (SAQ), among 1459 consecutive patients (1027 treated with PCI and 432, with CABG), stratified by their risk for restenosis. In multivariable-adjusted, linear regression analyses, no differences in 1-year angina or quality of life were observed among the 37.4% of patients at low risk for restenosis. However, among the 46.7% at intermediate risk for restenosis, 1-year health status scores were moderately better after CABG surgery compared with PCI (difference in SAQ angina frequency scores favoring CABG=6.1+/-1.7 points, P=0.0003; difference in SAQ quality of life=5.8+/-1.6 points, P=0.0004). Even larger differences in 1-year outcomes favoring CABG surgery were observed in patients at high risk for restenosis (SAQ angina frequency difference=10.8+/-4.2, P=0.01; SAQ quality of life difference=10.8+/-3.9, P=0.006). CONCLUSIONS: The relative health status benefits of CABG surgery compared with PCI increase as the risk of restenosis increases. Although selecting CABG or PCI is complex, preprocedural restenosis risk should be considered. It should also be tested as a means for considering drug-eluting as opposed to bare metal stents in PCI.

Bringing kinases into focus: efficient drug design through the use of chemogenomic toolkits.

The study of protein target families, as opposed to single targets, has become a very powerful tool in chemogenomics-led drug discovery. By integrating comprehensive chemoinformatics and bioinformatics databases with customised analytical tools, a 'Toolkit' approach for the target family is possible, thus allowing predictions of the ligand class, affinity, selectivity and likely off-target issues to be made for the guidance of the medicinal chemist. In this review, we highlight the development and application of the Toolkit approach to the protein kinase superfamily, drawing on examples from lead optimisation studies and the design of focused libraries for lead discovery.