Individual Proton Pump Inhibitors and Outcomes in Patients With Coronary Artery Disease on Dual Antiplatelet Therapy: A Systematic Review.

BACKGROUND: Observational studies evaluating the possible interaction between proton pump inhibitors (PPIs) and clopidogrel have shown mixed results. We conducted a systematic review comparing the safety of individual PPIs in patients with coronary artery disease taking clopidogrel. METHODS AND RESULTS: Studies performed from January 1995 to December 2013 were screened for inclusion. Data were extracted, and study quality was graded for 34 potential studies. For those studies in which follow-up period, outcomes, and multivariable adjustment were comparable, meta-analysis was performed.The adjusted odds or hazard ratios for the composite of cardiovascular or all-cause death, myocardial infarction, and stroke at 1 year were reported in 6 observational studies with data on individual PPIs. Random-effects meta-analyses of the 6 studies revealed an increased risk for adverse cardiovascular events for those taking pantoprazole (hazard ratio 1.38; 95% CI 1.12-1.70), lansoprazole (hazard ratio 1.29; 95% CI 1.09-1.52), or esomeprazole (hazard ratio 1.27; 95% CI 1.02-1.58) compared with patients on no PPI. This association was not significant for omeprazole (hazard ratio 1.16; 95% CI 0.93-1.44). Sensitivity analyses for the coronary artery disease population (acute coronary syndrome versus mixed) and exclusion of a single study due to heterogeneity of reported results did not have significant influence on the effect estimates for any PPIs. CONCLUSIONS: Several frequently used PPIs previously thought to be safe for concomitant use with clopidogrel were associated with greater risk of adverse cardiovascular events. Although the data are observational, they highlight the need for randomized controlled trials to evaluate the safety of concomitant PPI and clopidogrel use in patients with coronary artery disease.

Determinants and Implications of Self-perceived Authenticity: Beliefs About Authenticity and Reactions to Behavioral Incongruence

Although many perspectives suggest that authenticity is important for well-being, people do not always have direct access to the psychological processes that produce their behaviors and, thus, are not able to judge whether they are behaving consistently with their personality, attitudes, values, motives, and goals. Even so, people experience subjective feelings of authenticity and inauthenticity, raising the question of factors that influence people’s judgments of whether they are being authentic. The present studies used descriptive, correlational, experimental, and experience sampling designs to examine possible influences on self-judgments of authenticity, including the congruence between people’s behavior and inner dispositions, the positivity of the behavior, their personal beliefs about authenticity, features of the interaction, and trait authenticity. Studies 1A and 1B examined the role of people’s beliefs about authenticity in self-judgments of authenticity. Studies 2A and 2B investigated the criteria that people use to judge their behavior as authentic versus inauthentic and challenged those criteria to see whether self-perceived authenticity was affected. And, Study 3 used an experience sampling design to study people’s experiences of state authenticity in daily life. Together the studies offer insights into the determinants of self-perceived authenticity and show that many factors that influence people’s feelings of authenticity are peripheral, if not irrelevant, to actual authenticity.

Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.