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      Cohort profile: the Finnish Medication and Alzheimer's disease (MEDALZ) study

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          Abstract

          Purpose

          The aim of the Medicine use and Alzheimer's disease (MEDALZ) study is to investigate the changes in medication and healthcare service use among persons with Alzheimer's disease (AD) and to evaluate the safety and effectiveness of medications in this group. This is important, because the number of persons with AD is rapidly growing and even though they are a particularly vulnerable patient group, the number of representative, large-scale studies with adequate follow-up time is limited.

          Participants

          MEDALZ contains all residents of Finland who received a clinically verified diagnosis of AD between 2005 and 2011 and were community-dwelling at the time of diagnosis (N=70 719). The diagnosis is based on the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCS-ADRDA) and Diagnostic and Statistical Manual Fourth Edition (DSM-IV) criteria for Alzheimer's disease. The cohort contains socioeconomic data (education, occupational status and taxable income, 1972–2012) and causes of death (2005–2012), data from the prescription register (1995–2012), the special reimbursement register (1972–2012) and the hospital discharge register (1972–2012). Future updates are planned.

          The average age was 80.1 years (range 34.5–104.6 years). The majority of cohort (65.2%) was women. Currently, the average length of follow-up after AD diagnosis is 3.1 years and altogether 26 045 (36.8%) persons have died during the follow-up.

          Findings

          Altogether 53% of the cohort had used psychotropic drugs within 1 year after AD diagnoses. The initiation rate of for example, benzodiazepines and related drugs and antidepressants began to increase already before AD diagnosis.

          Future plans

          We are currently assessing if these, and other commonly used medications are related to adverse events such as death, hip fractures, head injuries and pneumonia.

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          Most cited references27

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          Meta-analysis of Alzheimer's disease risk with obesity, diabetes, and related disorders.

          Louis A Profenno, Anton P. Porsteinsson, Stephen V. Faraone (2010)
          Late-onset Alzheimer's disease (AD) is a multifactorial and heterogeneous disorder with major risk factors including advanced age, presence of an apolipoprotein E epsilon4 (APOE4) allele, and family history of AD. Other risk factors may be obesity and diabetes and related disorders, which are highly prevalent. We reviewed longitudinal epidemiological studies of body mass, diabetes, metabolic syndrome, and glucose and insulin levels on risk for AD. We conducted meta-analyses of the results from these studies. For obesity assessed by body mass index, the pooled effect size for AD was 1.59 (95% confidence interval [CI] 1.02-2.5; z = 2.0; p = .042), and for diabetes, the pooled effect size for AD was 1.54 (95% CI 1.33-1.79; z = 5.7; p < .001). Egger's test did not find significant evidence for publication bias in the meta-analysis for obesity (t = -1.4, p = .21) or for diabetes (t = -.86, p = .42). Since these disorders are highly comorbid, we conducted a meta-analysis combining all studies of obesity, diabetes, and abnormal glucose or insulin levels, which yielded a highly significant pooled effect size for AD of 1.63 (95% CI 1.39-1.92; z = 5.9; p < .001). Obesity and diabetes significantly and independently increase risk for AD. Though the level of risk is less than that with the APOE4 allele, the high prevalence of these disorders may result in substantial increases in future incidence of AD. Physiological changes common to obesity and diabetes plausibly promote AD. Published by Elsevier Inc.
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            Age-related changes in pharmacokinetics and pharmacodynamics: basic principles and practical applications.

            Suzanne S. Jackson, Arduino A. Mangoni (2003)
            Advancing age is characterized by impairment in the function of the many regulatory processes that provide functional integration between cells and organs. Therefore, there may be a failure to maintain homeostasis under conditions of physiological stress. The reduced homeostatic ability affects different regulatory systems in different subjects, thus explaining at least partly the increased interindividual variability occurring as people get older. Important pharmacokinetic and pharmacodynamic changes occur with advancing age. Pharmacokinetic changes include a reduction in renal and hepatic clearance and an increase in volume of distribution of lipid soluble drugs (hence prolongation of elimination half-life) whereas pharmacodynamic changes involve altered (usually increased) sensitivity to several classes of drugs such as anticoagulants, cardiovascular and psychotropic drugs. This review focuses on the main age-related physiological changes affecting different organ systems and their implications for pharmacokinetics and pharmacodynamics of drugs.
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              From prescription drug purchases to drug use periods – a second generation method (PRE2DUP)

              Antti Tanskanen, Heidi Taipale, Marjaana Koponen … (2015)
              Background Databases of prescription drug purchases are now widely used in pharmacoepidemiologic studies. Several methods have been used to generate drug use periods from drug purchases to investigate various aspects; e.g., to study associations between exposure and outcome. Typically, such methods have been fairly simplistic, with fixed assumptions of drug use pattern and or dose (for example, the assumed usage of 1 tablet per day). This paper describes a novel PRE2DUP method that constructs drug use periods from purchase histories, and verified by a validation based on an expert evaluation of the drug use periods generated by the method. Methods The PRE2DUP method is a novel approach based on mathematical modelling of personal drug purchasing behaviors. The method uses a decision procedure that includes each person’s purchase history for each ATC code, processed in a chronological order. The method constructs exposure time periods and estimates the dose used during the period by considering the purchased amount in Defined Daily Doses (DDDs), which is recorded in the prescription register database. This method takes account of stockpiling of drugs, personal purchasing pattern; i.e., regularity of the purchases, and periods of hospital or nursing home care where drug use is not recorded in the prescription register. The method can be applied to a variety of drug classes with different doses and use patterns by controlling restriction parameters for each ATC class, or even each drug package. In the presented example, the PRE2DUP method was applied to a register-based MEDALZ-2005 study cohort. All drug purchases (3,793,085) recorded in the Finnish prescription register between 2002 and 2009 for persons with Alzheimer’s disease (28,093) were included. Results Results of the expert-opinion based validation indicate that PRE2DUP method creates drug use periods with a relatively high correctness. Drugs with varying patterns of use and drugs used on a short-term basis only require more precise parameters. Conclusions PRE2DUP method gives highly accurate drug use periods for most drug classes, especially those meant for long-term use.
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                Author and article information

                Journal
                Journal ID (nlm-ta): BMJ Open
                Journal ID (iso-abbrev): BMJ Open
                Journal ID (hwp): bmjopen
                Journal ID (publisher-id): bmjopen
                Title: BMJ Open
                Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                ISSN (Electronic): 2044-6055
                Publication date Collection: 2016
                Publication date (Electronic): 13 July 2016
                Volume: 6
                Issue: 7
                Electronic Location Identifier: e012100
                Affiliations
                [1 ]School of Pharmacy, University of Eastern Finland , Kuopio, Finland
                [2 ]Research Center for Comparative Effectiveness and Patient Safety, University of Eastern Finland , Kuopio, Finland
                [3 ]Kuopio Research Center for Geriatric Care, School of Pharmacy, University of Eastern Finland , Kuopio, Finland
                [4 ]Department of Forensic Psychiatry, Niuvanniemi Hospital, University of Eastern Finland , Kuopio, Finland
                [5 ]National Institute for Health and Welfare , Helsinki, Finland
                [6 ]Department of Clinical Neuroscience, Karolinska Institutet , Stockholm, Sweden
                [7 ]Department of Psychiatry, Kuopio University Hospital , Kuopio, Finland
                Author notes
                [Correspondence to ] Dr Anna-Maija Tolppanen; anna-maija.tolppanen@ 123456uef.fi
                Article
                Publisher ID: bmjopen-2016-012100
                DOI: 10.1136/bmjopen-2016-012100
                PMC ID: 4947779
                PubMed ID: 27412109
                SO-VID: 6f7aa3c6-a2d1-4f79-87a7-e549b179fac9
                Copyright © Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
                License:

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                Date received : 31 March 2016
                Date revision received : 16 June 2016
                Date accepted : 17 June 2016
                Categories
                Subject: Pharmacology and Therapeutics
                Subject: Cohort Profile
                Subject: 1506
                Subject: 1723
                Subject: 1692
                Subject: 1713

                ScienceOpen disciplines: Medicine
                Keywords: alzheimer's disease,medication,healthcare service use,comorbidities
                Data availability:
                ScienceOpen disciplines: Medicine
                Keywords: alzheimer's disease, medication, healthcare service use, comorbidities

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