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      Incidence and prevalence of multiple sclerosis in Hungary based on record linkage of nationwide multiple healthcare administrative data

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          Abstract

          Objectives

          As there were only regional studies in Hungary about the prevalence of multiple sclerosis (MS), we aimed to estimate its epidemiological features using data of Hungary’s single-payer health insurance system.

          Methods

          Pseudonymized database of claims reported by hospitals and outpatient services between 2004–2016 was analyzed and linked with an independent database of outpatient pharmacy refills between 2010–2016. We established an administrative case definition of MS and validated it on medical records of 309 consecutive patients. A subject was defined as MS-patient if received MS diagnosis (International Classification of Diseases, 10th edition, code G35) on three or more occasions at least in 2 calendar years and at least once documented by a neurologist. Patients were counted as incident cases in the year of the first submitted claim for MS. We allowed a 6-year-long run-in period, so only data between 2010–2015 are discussed.

          Results

          Sensitivity of the administrative case definition turned out to be 99%, while specificity was >99%. Crude prevalence of MS has increased from 109.3/100,000 in 2010 to 130.8/100,000 in 2015 ( p-value = 0.000003). Crude incidence declined from 7.1/100,000 (2010) to 5.4/100,000 (2015) ( p-value = 0.018). Direct standardization − based on European standard population and results of nationwide Hungarian census of 2011 − revealed that age standardized prevalence was 105.2/100,000 (2010), which has grown to 127.2/100,000 (2015) ( p-value = 0.000001). Age standardized incidence rate declined from 6.7/100,000 (2010) to 5.1/100,000 (2015) ( p-value = 0.016). The ratio of MS-patients receiving ≥1 prescription for disease modifying treatment increased from 0.19 (2010) to 0.29 (2015) ( p-value = 0.0051). The female/male ratio of prevalent cases remained 2.6.

          Discussion

          The prevalence of MS in Hungary is higher than previously reported, the incidence rate is moderate. The prevalence is rising, the incidence rate shows decline. The proportion of patients receiving disease modifying treatment grows but was still around 30% in 2015.

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          Most cited references39

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          Global, regional, and national burden of multiple sclerosis 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

          Summary Background Multiple sclerosis is the most common inflammatory neurological disease in young adults. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic method of quantifying various effects of a given condition by demographic variables and geography. In this systematic analysis, we quantified the global burden of multiple sclerosis and its relationship with country development level. Methods We assessed the epidemiology of multiple sclerosis from 1990 to 2016. Epidemiological outcomes for multiple sclerosis were modelled with DisMod-MR version 2.1, a Bayesian meta-regression framework widely used in GBD epidemiological modelling. Assessment of multiple sclerosis as the cause of death was based on 13 110 site-years of vital registration data analysed in the GBD's cause of death ensemble modelling module, which is designed to choose the optimum combination of mathematical models and predictive covariates based on out-of-sample predictive validity testing. Data on prevalence and deaths are summarised in the indicator, disability-adjusted life-years (DALYs), which was calculated as the sum of years of life lost (YLLs) and years of life lived with a disability. We used the Socio-demographic Index, a composite indicator of income per person, years of education, and fertility, to assess relations with development level. Findings In 2016, there were 2 221 188 prevalent cases of multiple sclerosis (95% uncertainty interval [UI] 2 033 866–2 436 858) globally, which corresponded to a 10·4% (9·1 to 11·8) increase in the age-standardised prevalence since 1990. The highest age-standardised multiple sclerosis prevalence estimates per 100 000 population were in high-income North America (164·6, 95% UI, 153·2 to 177·1), western Europe (127·0, 115·4 to 139·6), and Australasia (91·1, 81·5 to 101·7), and the lowest were in eastern sub-Saharan Africa (3·3, 2·9–3·8), central sub-Saharan African (2·8, 2·4 to 3·1), and Oceania (2·0, 1·71 to 2·29). There were 18 932 deaths due to multiple sclerosis (95% UI 16 577 to 21 033) and 1 151 478 DALYs (968 605 to 1 345 776) due to multiple sclerosis in 2016. Globally, age-standardised death rates decreased significantly (change −11·5%, 95% UI −35·4 to −4·7), whereas the change in age-standardised DALYs was not significant (−4·2%, −16·4 to 0·8). YLLs due to premature death were greatest in the sixth decade of life (22·05, 95% UI 19·08 to 25·34). Changes in age-standardised DALYs assessed with the Socio-demographic Index between 1990 and 2016 were variable. Interpretation Multiple sclerosis is not common but is a potentially severe cause of neurological disability throughout adult life. Prevalence has increased substantially in many regions since 1990. These findings will be useful for resource allocation and planning in health services. Many regions worldwide have few or no epidemiological data on multiple sclerosis, and more studies are needed to make more accurate estimates. Funding Bill & Melinda Gates Foundation.
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            The contemporary spectrum of multiple sclerosis misdiagnosis

            To characterize patients misdiagnosed with multiple sclerosis (MS).
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              Trends in survival and cause of death in Danish patients with multiple sclerosis.

              The Danish Multiple Sclerosis Registry contains information about all Danish patients in whom multiple sclerosis has been diagnosed since 1948. The purpose of this study was to analyse trends in survival and causes of death of these patients and to compare them with those of the general population. The study comprised all patients with onset in the period 1949-1996. All case records were validated and classified according to standardized diagnostic criteria. Data on emigration and death were obtained by record linkage to official registers. The end of follow-up was 1 January 2000 for emigration and death, and 1 January 1999 for cause-specific deaths. Standardized mortality ratios and excess death rates were calculated for various causes of death and periods after multiple sclerosis onset, and time trends in survival probability were analysed by Cox regression. The study comprised 9881 patients, of whom 4254 had died before end of follow-up. The median survival time from onset was approximately 10 years shorter for multiple sclerosis patients than for the age-matched general population, and multiple sclerosis was associated with an almost threefold increase in the risk for death. According to death certificates, more than half (56.4%) of the patients had died from multiple sclerosis. They also had excess mortality rates from other diseases, except cancer, and from accidents and suicide. The probability for survival improved significantly during the observation period. Thus, the 10-year excess mortality was almost halved in comparison with that in the middle of the 1900s.
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                Author and article information

                Contributors
                Role: Formal analysisRole: MethodologyRole: Project administrationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Project administrationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: MethodologyRole: Validation
                Role: Data curationRole: Funding acquisitionRole: SoftwareRole: ValidationRole: Writing – review & editing
                Role: Formal analysis
                Role: Formal analysisRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                27 July 2020
                2020
                : 15
                : 7
                : e0236432
                Affiliations
                [1 ] Department of Neurology, Semmelweis University, Budapest, Hungary
                [2 ] MTA-SE Neuroepidemiological Research Group, Budapest, Hungary
                [3 ] Institute of Experimental Medicine, Budapest, Hungary
                [4 ] Centre for Economic and Regional Studies, Budapest, Hungary
                [5 ] Department of Probability Theory and Statistics, Eötvös Loránd University, Budapest, Hungary
                University of Catania, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-5442-0794
                http://orcid.org/0000-0002-3182-4067
                http://orcid.org/0000-0002-1187-4104
                http://orcid.org/0000-0002-8374-0500
                Article
                PONE-D-20-05867
                10.1371/journal.pone.0236432
                7384662
                32716953
                ccb4196d-9617-44e7-9b99-892aeb30fc88
                © 2020 Iljicsov et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 28 February 2020
                : 6 July 2020
                Page count
                Figures: 0, Tables: 4, Pages: 17
                Funding
                DB, AA and OF were supported by grants from the National Brain Research Program 2017-2-1-NKP-2017-00002 DB and AI by the Higher Education Institutional Excellence Program and the New National Excellence Program (UNKP-17-3) of the Ministry of Human Resources of the Government of Hungary. The Funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Clinical Medicine
                Clinical Immunology
                Autoimmune Diseases
                Multiple Sclerosis
                Biology and Life Sciences
                Immunology
                Clinical Immunology
                Autoimmune Diseases
                Multiple Sclerosis
                Medicine and Health Sciences
                Immunology
                Clinical Immunology
                Autoimmune Diseases
                Multiple Sclerosis
                Medicine and Health Sciences
                Neurology
                Demyelinating Disorders
                Multiple Sclerosis
                Medicine and Health Sciences
                Neurology
                Neurodegenerative Diseases
                Multiple Sclerosis
                Medicine and Health Sciences
                Diagnostic Medicine
                Medicine and Health Sciences
                Health Care
                Patients
                Outpatients
                People and places
                Geographical locations
                Europe
                European Union
                Hungary
                People and Places
                Geographical Locations
                Europe
                Medicine and Health Sciences
                Health Care
                Patients
                Inpatients
                Medicine and Health Sciences
                Pharmaceutics
                Drug Therapy
                Neurological Drug Therapy
                Medicine and Health Sciences
                Epidemiology
                Custom metadata
                All relevant data are within the manuscript and its Supporting Information files.

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