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      The burden of common variable immunodeficiency disorders: a retrospective analysis of the European Society for Immunodeficiency (ESID) registry data

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          Abstract

          Background

          Common variable immunodeficiency disorders (CVID) are a group of rare innate disorders characterized by specific antibody deficiency and increased rates of infections, comorbidities and mortality. The burden of CVID in Europe has not been previously estimated. We performed a retrospective analysis of the European Society for Immunodeficiencies (ESID) registry data on the subset of patients classified by their immunologist as CVID and treated between 2004 and 2014. The registered deaths and comorbidities were used to calculate the annual average age-standardized rates of Years of Life Lost to premature death (YLL), Years Lost to Disability (YLD) and Disability Adjusted Life Years (DALY=YLL + YLD). These outcomes were expressed as a rate per 10 5 of the CVID cohort (the individual disease burden), and of the general population (the societal disease burden).

          Results

          Data of 2700 patients from 23 countries were analysed. Annual comorbidity rates: bronchiectasis, 21.9%; autoimmunity, 23.2%; digestive disorders, 15.6%; solid cancers, 5.5%; lymphoma, 3.8%, exceeded the prevalence in the general population by a factor of 34.0, 7.6, 8.1, 2.4 and 32.6, respectively. The comorbidities of CVID caused 8722 (6069; 12,363) YLD/10 5 in this cohort, whereas 44% of disability burden was attributable to infections and bronchiectasis. The total individual burden of CVID was 36,785 (33,078, 41,380) DALY/10 5. With estimated CVID prevalence of ~ 1/ 25,000, the societal burden of CVID ensued 1.5 (1.3, 1.7) DALY/10 5 of the general population.

          In exploratory analysis, increased mortality was associated with solid tumor, HR (95% CI): 2.69 (1.10; 6.57) p = 0.030, lymphoma: 5.48 (2.36; 12.71) p < .0001 and granulomatous-lymphocytic interstitial lung disease: 4.85 (1.63; 14.39) p = 0.005. Diagnostic delay (median: 4 years) was associated with a higher risk of death: 1.04 (1.02; 1.06) p = .0003, bronchiectasis: 1.03 (1.01; 1.04) p = .0001, solid tumor: 1.08 (1.04; 1.11) p < .0001 and enteropathy: 1.02 (1.00; 1.05) p = .0447 and stayed unchanged over four decades ( p = .228).

          Conclusions

          While the societal burden of CVID may seem moderate, it is severe to the individual patient. Delay in CVID diagnosis may constitute a modifiable risk factor of serious comorbidities and death but showed no improvement. Tools supporting timely CVID diagnosis should be developed with high priority.

          Electronic supplementary material

          The online version of this article (10.1186/s13023-018-0941-0) contains supplementary material, which is available to authorized users.

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          Most cited references44

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          Global, regional, and national age–sex specific all-cause and cause-specific mortality for 240 causes of death, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

          The Lancet, 385(9963), 117-171
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            Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990–2013: quantifying the epidemiological transition

            The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age-sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development.
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              Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010.

              Measurement of the global burden of disease with disability-adjusted life-years (DALYs) requires disability weights that quantify health losses for all non-fatal consequences of disease and injury. There has been extensive debate about a range of conceptual and methodological issues concerning the definition and measurement of these weights. Our primary objective was a comprehensive re-estimation of disability weights for the Global Burden of Disease Study 2010 through a large-scale empirical investigation in which judgments about health losses associated with many causes of disease and injury were elicited from the general public in diverse communities through a new, standardised approach. We surveyed respondents in two ways: household surveys of adults aged 18 years or older (face-to-face interviews in Bangladesh, Indonesia, Peru, and Tanzania; telephone interviews in the USA) between Oct 28, 2009, and June 23, 2010; and an open-access web-based survey between July 26, 2010, and May 16, 2011. The surveys used paired comparison questions, in which respondents considered two hypothetical individuals with different, randomly selected health states and indicated which person they regarded as healthier. The web survey added questions about population health equivalence, which compared the overall health benefits of different life-saving or disease-prevention programmes. We analysed paired comparison responses with probit regression analysis on all 220 unique states in the study. We used results from the population health equivalence responses to anchor the results from the paired comparisons on the disability weight scale from 0 (implying no loss of health) to 1 (implying a health loss equivalent to death). Additionally, we compared new disability weights with those used in WHO's most recent update of the Global Burden of Disease Study for 2004. 13,902 individuals participated in household surveys and 16,328 in the web survey. Analysis of paired comparison responses indicated a high degree of consistency across surveys: correlations between individual survey results and results from analysis of the pooled dataset were 0·9 or higher in all surveys except in Bangladesh (r=0·75). Most of the 220 disability weights were located on the mild end of the severity scale, with 58 (26%) having weights below 0·05. Five (11%) states had weights below 0·01, such as mild anaemia, mild hearing or vision loss, and secondary infertility. The health states with the highest disability weights were acute schizophrenia (0·76) and severe multiple sclerosis (0·71). We identified a broad pattern of agreement between the old and new weights (r=0·70), particularly in the moderate-to-severe range. However, in the mild range below 0·2, many states had significantly lower weights in our study than previously. This study represents the most extensive empirical effort as yet to measure disability weights. By contrast with the popular hypothesis that disability assessments vary widely across samples with different cultural environments, we have reported strong evidence of highly consistent results. Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                irina.v.odnoletkova@gmail.com
                gerhard.kindle@uniklinik-freiburg.de
                Isabella.quinti@uniroma1.it
                bodo.grimbacher@uniklinik-freiburg.de
                VivianeKnerr@gmx.de
                benjamin.gathmann@gmail.com
                stephan.ehl@uniklinik-freiburg.de
                nizar.mahlaoui@nck.aphp.fr
                philippe.van.wilder@ulb.ac.b
                Kris.bogaerts@kuleuven.be
                esther.devries@etz.nl , e.devries@tilburguniversity.edu
                Journal
                Orphanet J Rare Dis
                Orphanet J Rare Dis
                Orphanet Journal of Rare Diseases
                BioMed Central (London )
                1750-1172
                12 November 2018
                12 November 2018
                2018
                : 13
                : 201
                Affiliations
                [1 ]Plasma Protein Therapeutics Association, Boulevard Brand Whitlock 114b4, 1200 Brussels, Belgium
                [2 ]ISNI 0000 0001 2069 7798, GRID grid.5342.0, Faculty of Medicine and Health Sciences, , Ghent University, ; C. Heymanslaan 10, 9000 Ghent, Belgium
                [3 ]The ESID Registry Working Party, https://esid.org/Working-Parties/Registry
                [4 ]GRID grid.5963.9, Center for Chronic Immunodeficiency, Medical Center – University of Freiburg, Faculty of Medicine, , University of Freiburg, ; Freiburg, Germany
                [5 ]GRID grid.7841.a, Department of Molecular Medicine, , Sapienza University of Rome, ; Rome, Italy
                [6 ]GRID grid.417007.5, University Hospital Policlinico Umberto I, ; Rome, Italy
                [7 ]ISNI 0000000121901201, GRID grid.83440.3b, Institute of Immunology and Transplantation, Royal Free Hospital, , University College London, ; London, UK
                [8 ]ISNI 0000 0001 2175 4109, GRID grid.50550.35, French National Reference Center for Primary Immune Deficiencies (CEREDIH) and Pediatric Immuno-Haematology and Rheumatology Unit Necker-Enfants Malades University Hospital, Assistance Publique-Hôpitaux de Paris, ; Paris, France
                [9 ]ISNI 0000 0001 2188 0914, GRID grid.10992.33, Paris Descartes University, Sorbonne Paris Cité, Imagine Institute, ; Paris, France
                [10 ]ISNI 0000000121866389, GRID grid.7429.8, INSERM UMR 1163, Laboratory of Human Genetics of Infectious Diseases, Necker Branch, ; Paris, France
                [11 ]ISNI 0000 0001 2290 8069, GRID grid.8767.e, Centre de recherche en Economie de la Santé, Gestion des Institutions de Soins et Sciences Infirmières, Ecole de Santé Publique, , University of Brussels (ULB), ; Brussels, Belgium
                [12 ]ISNI 0000 0001 0668 7884, GRID grid.5596.f, Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), , KU Leuven – University of Leuven, I-BioStat, ; 3000 Leuven, Belgium
                [13 ]ISNI 0000 0001 0604 5662, GRID grid.12155.32, University Hasselt, I-BioStat, ; 3500 Hasselt, Belgium
                [14 ]ISNI 0000 0001 0943 3265, GRID grid.12295.3d, Department Tranzo, , Tilburg University, ; PO Box 90153 (RP219), 5000 LE Tilburg, the Netherlands
                [15 ]ISNI 0000 0004 1756 4611, GRID grid.416415.3, Laboratory for Microbiology and Immunology, Elisabeth Tweesteden Hospital, ; PO Box 90151 (route 90), 5000LC Tilburg, the Netherlands
                Article
                941
                10.1186/s13023-018-0941-0
                6233554
                30419968
                bdc3ddb9-bbba-4ae2-a427-3b1e63e7af9a
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 19 June 2018
                : 22 October 2018
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                Infectious disease & Microbiology
                primary immunodeficiency,primary antibody deficiency,common variable immunodeficiency,burden of disease,daly,health economics,diagnostic delay

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