s-1743 and rofecoxib

Reducing mucosal cyclo-oxygenase-2 and prostaglandin E(2) production and suppressing intraoesophageal acid may be effective chemopreventive strategies in patients with Barrett's oesophagus.. To compare the effects of aspirin and rofecoxib when administered with esomeprazole on prostaglandin E(2) production, cyclo-oxygenase-2 expression and proliferating cell nuclear antigen expression in patients with Barrett's oesophagus.. This exploratory, multicentre, randomized, open-label, four-way crossover study in 45 patients with Barrett's oesophagus evaluated prostaglandin E(2) content, proliferating cell nuclear antigen expression, and cyclo-oxygenase-2 expression after 10 days of sequential treatments with: esomeprazole 40 mg twice daily plus aspirin 325 mg once daily (E40 b.d. + A325); E40 b.d. plus rofecoxib 25 mg once daily (E40 b.d. + R25); E40 b.d.; and rofecoxib 25 mg once daily (R25).. Prostaglandin E(2) content reduction in Barrett's oesophagus tissue was significantly greater with E40 b.d. + A325 compared with E40 b.d. + R25, E40 b.d. or R25 (P < 0.05). All treatments containing E40 b.d. significantly decreased proliferating cell nuclear antigen expression from baseline (P < 0.05). None of the treatments significantly reduced cyclo-oxygenase-2 expression.. The combined treatment of esomeprazole 40 mg b.d. and aspirin 325 mg significantly decreased mucosal prostaglandin E(2) content and all treatments containing esomeprazole significantly reduced proliferating cell nuclear antigen expression in patients with Barrett's oesophagus.

Topics: Adult; Aged; Aspirin; Barrett Esophagus; Cross-Over Studies; Cyclooxygenase 2; Cyclooxygenase 2 Inhibitors; Cyclooxygenase Inhibitors; Dinoprostone; Drug Therapy, Combination; Enzyme Inhibitors; Esomeprazole; Esophagitis; Esophagus; Female; Humans; Lactones; Male; Middle Aged; Proliferating Cell Nuclear Antigen; Prospective Studies; Sulfones

A primary objective in the application of postmarketing drug safety surveillance is to ascertain the relationship between time-varying drug exposures and recurrent adverse events (AEs) related to health outcomes. The self-controlled case series (SCCS) method is one approach to analysis in this context. It is based on a conditional Poisson regression model, which assumes that events at different time points are conditionally independent given the covariate process. This requirement is problematic when the occurrence of an event can alter the future event risk. In a clinical setting, for example, patients who have a first myocardial infarction (MI) may be at higher subsequent risk for a second. In this work, we propose the positive dependence self-controlled case series (PD-SCCS) method: a generalization of SCCS that allows the occurrence of an event to increase the future event risk, yet maintains the advantages of the original model by controlling for fixed baseline covariates and relying solely on data from cases. As in the SCCS model, individual-level baseline parameters drop out of the PD-SCCS likelihood. Data sources used for postmarketing surveillance can contain tens of millions of people, so in this situation it is particularly advantageous that PD-SCCS avoids doing a costly estimation of individual parameters. We develop expressions for large sample inference and optimization for PD-SCCS and compare the results of our generalized model with the more restrictive SCCS approach.

Topics: Computer Simulation; Esomeprazole; Humans; Lactones; Models, Statistical; Myocardial Infarction; Omeprazole; Product Surveillance, Postmarketing; Research Design; Sulfones