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      Short look-back periods in pharmacoepidemiologic studies of new users of antibiotics and asthma medications introduce severe misclassification : SHORT LOOK-BACK PERIODS INTRODUCE SEVERE MISCLASSIFICATION

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          Long-term Persistence in Use of Statin Therapy in Elderly Patients

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            Construction of drug treatment episodes from drug-dispensing histories is influenced by the gap length.

            When constructing drug treatment episodes using drug-dispensing databases, duration and the number of prescriptions belonging to a single treatment episode need to be defined. We investigated how different methods used to construct antidepressant treatment episodes influence their median estimated length. A follow-up study among adult antidepressant drug users, identified from the Dutch PHARMO RLS, starting selective serotonin reuptake inhibitor (SSRI) use in 2001 was conducted. The influence of varying lengths of the prescription overlap and the gap between prescriptions (number of days or percentage of prescription duration) on the median antidepressant treatment episode length were investigated. Of the 16,053 SSRI starters, 65.1% were female and mean age was 45.7 (SD: 17.2) years. Median antidepressant treatment episode length doubled when the gap length was expanded from 0 to 10 days. For short gap lengths the episode interquartile range was 40% to 200% larger when overlap was accounted for and when percentage of prescription duration gap length was used. Differences in median episode length exist between methods that account for or disregard prescription overlap. These differences are of importance for studies that focus on drug exposure-outcome relationships and could have consequences for epidemiological analysis. Copyright 2010. Published by Elsevier Inc.
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              Fracture risk associated with use of antiepileptic drugs.

              To assess fracture risk associated with different antiepileptic drugs (AEDs). An increased fracture risk has been reported in patients with epilepsy. Classical AEDs have been associated with decreased bone mineral density. The effects of newer AEDs are unknown. We undertook a population-based pharmacoepidemiologic case-control study with any fracture as outcome and use of AEDs as exposure variables (124,655 fracture cases and 373,962 controls). All AEDs were associated with an increased fracture risk in an unadjusted analysis. After adjustment for prior fracture, use (ever) of corticosteroids, comorbidity, social variables, and diagnosis of epilepsy, carbamazepine [CBZ; odds ratio (OR), 1.18; 95% confidence interval (CI), 1.10-1.26], [and oxcarbazepine (OXC; 1.14, 1.03-1.26)], clonazepam (CZP; 1.27, 1.15-1.41), phenobarbital (PB; 1.79, 1.64-1.95), and valproate (VPA; 1.15, 1.05-1.26) were statistically significantly associated with risk of any fracture. Ethosuximide (0.75, 0.37-1.52), lamotrigine (1.04, 0.91-1.19), phenytoin (1.20, 1.00-1.43), primidone (1.18, 0.95-1.48), tiagabine (0.75, 0.40-1.41), topiramate (1.39, 0.99-1.96), and vigabatrin (0.93, 0.70-1.22) were not statistically significantly associated with fracture risk after adjustment for confounders. The relative increase was modest and in the same range for the significant and nonsignificant results. CBZ, PB, OXC, and VPA displayed a dose-response relation. Fracture risk was more increased by liver-inducing AEDs (OR, 1.38; 95% CI, 1.31-1.45) than by noninducing AEDs (1.19; 95% CI, 1.11-1.27). A very limited increased fracture risk is present in users of CBZ, CZP, OXC, PB, and VPA. A limited significant increase cannot be excluded for the other AEDs because of the statistical power.
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                Author and article information

                Journal
                Pharmacoepidemiology and Drug Safety
                Pharmacoepidemiol Drug Saf
                Wiley
                10538569
                May 2015
                May 2015
                January 20 2015
                : 24
                : 5
                : 478-485
                Affiliations
                [1 ]Department of Clinical Epidemiology; Aarhus University Hospital; Aarhus N Denmark
                [2 ]Department of Clinical Medicine; Aalborg University; Aalborg Denmark
                [3 ]Department of Epidemiology; University of North Carolina; Chapel Hill NC USA
                [4 ]School of Public Health, Biostatistics; Aarhus University; Aarhus C Denmark
                Article
                10.1002/pds.3738
                9d1c5868-7696-4edd-9028-5580414facb4
                © 2015

                http://doi.wiley.com/10.1002/tdm_license_1.1

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