XXXX Inhibitor Usage and the Risk of @entity583 in the General Population.

@entity1 @entity1187 @entity1397 @entity7080 @entity354 @entity583 @entity65
BACKGROUND AND AIMS: @entity7080 inhibitors (PPIs) have been associated with adverse clinical outcomes amongst @entity1397 users after an @entity1187 . Recent pre-clinical results suggest that this risk might extend to subjects without any prior history of @entity65 . We explore this potential risk in the general population via data-mining approaches. METHODS: Using a novel approach for mining clinical data for pharmacovigilance, we queried over 16 million clinical documents on 2.9 million individuals to examine whether PPI usage was associated with cardiovascular risk in the general population. RESULTS: In multiple data sources, we found @entity354 ( @entity354 ) @entity1 exposed to PPIs to have a 1.16 fold increased association (95% CI 1.09-1.24) with @entity583 ( @entity583 ). Survival analysis in a prospective cohort found a two-fold (HR = 2.00; 95% CI 1.07-3.78; P = 0.031) increase in association with @entity65 . We found that this association exists regardless of @entity1397 use. We also found that H2 blockers, an alternate treatment for @entity354 , were not associated with increased cardiovascular risk; had they been in place, such pharmacovigilance algorithms could have flagged this risk as early as the year 2000. CONCLUSIONS: Consistent with our pre-clinical findings that PPIs may adversely impact vascular function, our data-mining study supports the association of PPI exposure with risk for @entity583 in the general population. These data provide an example of how a combination of experimental studies and data-mining approaches can be applied to prioritize drug safety signals for further investigation.
