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  • Title: Estimating the effect of current, previous and never use of drugs in studies based on prescription registries.
    Author: Nielsen LH, Løkkegaard E, Andreasen AH, Hundrup YA, Keiding N.
    Journal: Pharmacoepidemiol Drug Saf; 2009 Feb; 18(2):147-53. PubMed ID: 19072775.
    Abstract:
    PURPOSE: Many studies which investigate the effect of drugs categorize the exposure variable into never, current, and previous use of the study drug. When prescription registries are used to make this categorization, the exposure variable possibly gets misclassified since the registries do not carry any information on the time of discontinuation of treatment.In this study, we investigated the amount of misclassification of exposure (never, current, previous use) to hormone therapy (HT) when the exposure variable was based on prescription data. Furthermore, we evaluated the significance of this misclassification for analysing the risk of breast cancer. MATERIALS AND METHODS: Prescription data were obtained from Danish Registry of Medicinal Products Statistics and we applied various methods to approximate treatment episodes. We analysed the duration of HT episodes to study the ability to identify discontinuation of therapy from prescription data. Furthermore, we compared to results based on self-reported duration of HT from the Danish Nurse Cohort.Finally, we analysed the effect of HT exposure on time to breast cancer for the different prescription based exposure variables as well as for self-reported HT use. RESULTS: The results of time to discontinuation varied strongly across the different HT assessments. However, misclassification of HT exposure at baseline was limited and hence analysis of the effect of HT on time to breast cancer showed stability across the different exposure assessments with Hazard Ratios ranging from 1.68 to 1.78 for current use compared to never use. CONCLUSIONS: The findings suggest that it is possible to estimate the effect of never, current and previous use of HT on breast cancer using prescription data.
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