Marianne Meaidi1, Henrik Støvring2, Klaus Rostgaard3, Christian Torp-Pedersen4, Kristian Hay Kragholm5, Morten Andersen1, Maurizio Sessa6. 1. Department of Drug Design and Pharmacology, University of Copenhagen, Jagtvej 160, 2100, København Ø, Denmark. 2. Department of Public Health, Aarhus University, Aarhus, Denmark. 3. Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark. 4. Department of Clinical Research, Nordsjællands Hospital, Hillerød, Denmark. 5. Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark. 6. Department of Drug Design and Pharmacology, University of Copenhagen, Jagtvej 160, 2100, København Ø, Denmark. maurizio.sessa@sund.ku.dk.
Abstract
PURPOSE: In pharmacoepidemiology, correctly defining the exposure period of pharmacological treatment is a challenging step when information on the time in treatment is missing or incomplete. METHODS: In this review, we describe several methods for defining exposure to pharmacological treatments using secondary data sources that lack such information. RESULTS AND CONCLUSION: Several methods for assessing the duration of redeemed prescriptions and combining them into temporal sequences are available. We present a set of considerations to make researchers aware of the potentials and pitfalls of these methods that may aid in minimizing biases in research using these methods. Additionally, we highlight that, to date, there is no one-size-fits-all solution. Thus, the choice of method should be based on their area of applicability combined with a careful mapping to the research scenario under investigation.
PURPOSE: In pharmacoepidemiology, correctly defining the exposure period of pharmacological treatment is a challenging step when information on the time in treatment is missing or incomplete. METHODS: In this review, we describe several methods for defining exposure to pharmacological treatments using secondary data sources that lack such information. RESULTS AND CONCLUSION: Several methods for assessing the duration of redeemed prescriptions and combining them into temporal sequences are available. We present a set of considerations to make researchers aware of the potentials and pitfalls of these methods that may aid in minimizing biases in research using these methods. Additionally, we highlight that, to date, there is no one-size-fits-all solution. Thus, the choice of method should be based on their area of applicability combined with a careful mapping to the research scenario under investigation.
Authors: B Wettermark; H Zoëga; K Furu; M Korhonen; J Hallas; M Nørgaard; Ab Almarsdottir; M Andersen; K Andersson Sundell; U Bergman; A Helin-Salmivaara; M Hoffmann; H Kieler; Je Martikainen; M Mortensen; M Petzold; H Wallach-Kildemoes; C Wallin; Ht Sørensen Journal: Pharmacoepidemiol Drug Saf Date: 2013-05-23 Impact factor: 2.890
Authors: Laura Pazzagli; Marie Linder; Mingliang Zhang; Emese Vago; Paul Stang; David Myers; Morten Andersen; Shahram Bahmanyar Journal: Pharmacoepidemiol Drug Saf Date: 2017-12-28 Impact factor: 2.890