Proceedings of the 2013 annual meeting of the Netherlands Epidemiology Society
Volume 1 Issue S1 Abstract 28
M.C.H. de Groot, Utrecht University, Utrecht, the Netherlands
O.H. Klungel, Utrecht University, Utrecht, the Netherlands
L. van Dijk, NIVEL Institute for Healthcare Research, Utrecht, the Netherlands
D.E. Grobbee, Julius Center, UMC Utrecht, the Netherlands
H.G.M. Leufkens, St. Antonius Hospital, Nieuwegein
E.M.W. van de Garde, Utrecht University, Utrecht, the Netherlands
To enable clinical interpretation of the reported association between community-acquired pneumonia (CAP) and commonly used drugs such as statins, ACE-inhibitors (ACE-I), and proton pump inhibitors (PPI), we explore sources of heterogeneity in pharmacoepidemiological studies by using the same methods in multiple settings.
The TI-PHARMA Mondriaan project provides access to various healthcare databases from hospitals, general practices (GP), and pharmacies. Ten different case-control sets in 5 different populations derived from both GP and hospital data were generated. Patients and controls were matched on age, gender, and index year. Conditional logistic regression was used to calculate odds ratios (OR) for the associations between the drugs of interest and CAP. Crude associations were adjusted on different levels (semi-adjusted, fully adjusted) for comorbidity and drug use.
Data of 38742 cases and 118019 controls were studied. The mean age of the hospitalised patients was 63 years compared to 46 to 61 years for the GP patients. For statin use and pneumonia risk the semi-adjusted OR varied from 0.82 to 1.38. A comparable range was observed for ACE-I and PPI use with ORs of 1.02 to 1.61 and 1.29 to 2.69, respectively. Overall, higher ORs were found for hospitalised CAP patients matched to population controls versus GP CAP patients matched to population controls. Prevalence of drug exposure was higher in dispensing data versus prescription data.
Associations between statin, ACE-I, and PPI use and CAP risk were influenced by sampling population and data source and may explain the large heterogeneity observed between previous observational studies.
Published: 06 Jun, 2013