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      The prevalence of autosomal dominant polycystic kidney disease (ADPKD): A meta-analysis of European literature and prevalence evaluation in the Italian province of Modena suggest that ADPKD is a rare and underdiagnosed condition

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          Abstract

          Background and objectives

          ADPKD is erroneously perceived as a not rare condition, which is mainly due to the repeated citation of a mistaken interpretation of old epidemiological data, as reported in the Dalgaard's work (1957). Even if ADPKD is not a common condition, the correct prevalence of ADPKD in the general population is uncertain, with a wide range of estimations reported by different authors. In this work, we have performed a meta-analysis of available epidemiological data in the European literature. Furthermore we collected the diagnosis and clinical data of ADPKD in a province in the north of Italy (Modena). We describe the point and predicted prevalence of ADPKD, as well as the main clinical characteristics of ADPKD in this region.

          Methods

          We looked at the epidemiological data according to specific parameters and criteria in the Pubmed, CINAHL, Scopus and Web of Science databases. Data were summarized using linear regression analysis. We collected patients’ diagnoses in the Province of Modena according to accepted clinical criteria and/or molecular analysis. Predicted prevalence has been calculated through a logistic regression prediction applied to the at-risk population.

          Results

          The average prevalence of ADPKD, as obtained from 8 epidemiological studies of sufficient quality, is 2.7: 10,000 (CI95 = 0.73–4.67). The point prevalence of ADPKD in the province of Modena is 3.63: 10,000 (CI95 = 3.010–3.758). On the basis of the collected pedigrees and identification of the at-risk subjects, the predicted prevalence in the Province of Modena is 4.76: 10,000 (CI 95% = 4.109–4.918).

          Conclusion

          As identified in our study, point prevalence is comparable with the majority of the studies of literature, while predicted prevalence (4.76: 10,000) generally appears higher than in the previous estimates of the literature, with a few exceptions. Thus, this could suggest that undiagnosed ADPKD subjects, as predicted by our approach, could be relevant and will most likely require more clinical attention. Nevertheless, our estimation, in addition to the averaged ones derived from literature, not exceeding the limit of 5:10,000 inhabitants, are compatible with the definition of rare disease adopted by the European Medicines Agency and Food and Drug Administration.

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          Most cited references38

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          Autosomal dominant polycystic kidney disease.

          Autosomal dominant polycystic kidney disease is the most prevalent, potentially lethal, monogenic disorder. It is associated with large interfamilial and intrafamilial variability, which can be explained to a large extent by its genetic heterogeneity and modifier genes. An increased understanding of the disorder's underlying genetic, molecular, and cellular mechanisms and a better appreciation of its progression and systemic manifestations have laid out the foundation for the development of clinical trials and potentially effective treatments.
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            Unified criteria for ultrasonographic diagnosis of ADPKD.

            Individuals who are at risk for autosomal dominant polycystic kidney disease are often screened by ultrasound using diagnostic criteria derived from individuals with mutations in PKD1. Families with mutations in PKD2 typically have less severe disease, suggesting a potential need for different diagnostic criteria. In this study, 577 and 371 at-risk individuals from 58 PKD1 and 39 PKD2 families, respectively, were assessed by renal ultrasound and molecular genotyping. Using sensitivity data derived from genetically affected individuals and specificity data derived from genetically unaffected individuals, various diagnostic criteria were compared. In addition, data sets were created to simulate the PKD1 and PKD2 case mix expected in practice to evaluate the performance of diagnostic criteria for families of unknown genotype. The diagnostic criteria currently in use performed suboptimally for individuals with mutations in PKD2 as a result of reduced test sensitivity. In families of unknown genotype, the presence of three or more (unilateral or bilateral) renal cysts is sufficient for establishing the diagnosis in individuals aged 15 to 39 y, two or more cysts in each kidney is sufficient for individuals aged 40 to 59 y, and four or more cysts in each kidney is required for individuals > or = 60 yr. Conversely, fewer than two renal cysts in at-risk individuals aged > or = 40 yr is sufficient to exclude the disease. These unified diagnostic criteria will be useful for testing individuals who are at risk for autosomal dominant polycystic kidney disease in the usual clinical setting in which molecular genotyping is seldom performed.
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              Imaging classification of autosomal dominant polycystic kidney disease: a simple model for selecting patients for clinical trials.

              The rate of renal disease progression varies widely among patients with autosomal dominant polycystic kidney disease (ADPKD), necessitating optimal patient selection for enrollment into clinical trials. Patients from the Mayo Clinic Translational PKD Center with ADPKD (n=590) with computed tomography/magnetic resonance images and three or more eGFR measurements over ≥6 months were classified radiologically as typical (n=538) or atypical (n=52). Total kidney volume (TKV) was measured using stereology (TKVs) and ellipsoid equation (TKVe). Typical patients were randomly partitioned into development and internal validation sets and subclassified according to height-adjusted TKV (HtTKV) ranges for age (1A-1E, in increasing order). Consortium for Radiologic Imaging Study of PKD (CRISP) participants (n=173) were used for external validation. TKVe correlated strongly with TKVs, without systematic underestimation or overestimation. A longitudinal mixed regression model to predict eGFR decline showed that log2HtTKV and age significantly interacted with time in typical patients, but not in atypical patients. When 1A-1E classifications were used instead of log2HtTKV, eGFR slopes were significantly different among subclasses and, except for 1A, different from those in healthy kidney donors. The equation derived from the development set predicted eGFR in both validation sets. The frequency of ESRD at 10 years increased from subclass 1A (2.4%) to 1E (66.9%) in the Mayo cohort and from 1C (2.2%) to 1E (22.3%) in the younger CRISP cohort. Class and subclass designations were stable. An easily applied classification of ADPKD based on HtTKV and age should optimize patient selection for enrollment into clinical trials and for treatment when one becomes available.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: InvestigationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Investigation
                Role: Data curationRole: Investigation
                Role: Data curation
                Role: Data curationRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Data curation
                Role: Data curationRole: Formal analysis
                Role: Data curation
                Role: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                16 January 2018
                2018
                : 13
                : 1
                : e0190430
                Affiliations
                [1 ] Dipartimento Chirurgico, Medico, Odontoiatrico e di Scienze Morfologiche con Interesse Trapiantologico, Oncologico e di Medicina Rigenerativa, Università degli Studi di Modena e Reggio Emilia, Modena, Italy
                [2 ] UO Nefrologia, Dialisi e Trapianto, Dipartimento di Medicina Specialistica, Diagnostica e Sperimentale, Ospedale Sant'Orsola-Malpighi, Alma Mater Studiorum Università di Bologna, Bologna, Italy
                [3 ] Divisione di Nefrologia Dialisi e Trapianto Renale, Dipartimento interaziendale ad attività integrata Malattie Nefrologiche, Cardiache e Vascolari, Azienda Ospedaliero Universitaria di Modena, Modena, Italy
                [4 ] Division of Genetics and Cell Biology, Unit of Genomics for human disease diagnosis, and Laboratory of Clinical Molecular Genetics, San Raffaele Scientific Institute, Milan, Italy
                [5 ] Università Vita e Salute San Raffaele, Milan, Italy
                Istituto Di Ricerche Farmacologiche Mario Negri, ITALY
                Author notes

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

                Author information
                http://orcid.org/0000-0002-3319-0248
                Article
                PONE-D-17-31569
                10.1371/journal.pone.0190430
                5770025
                29338003
                14775186-d71c-40a1-af3f-d5b41573fbe8
                © 2018 Solazzo 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 August 2017
                : 14 December 2017
                Page count
                Figures: 5, Tables: 5, Pages: 20
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100003196, Ministero della Salute;
                Award ID: RF-2013-02356802
                Award Recipient :
                This study was partially funded by a grant provided by the Italian Ministry of Health (Ricerca Finalizzata Protocol RF-2013-02356802). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The remaining funding of this work was covered by the Institute's internal resources of the last author. There was no additional external funding received for this study.
                Categories
                Research Article
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Medicine and Health Sciences
                Epidemiology
                Biology and Life Sciences
                Anatomy
                Renal System
                Kidneys
                Medicine and Health Sciences
                Anatomy
                Renal System
                Kidneys
                Medicine and Health Sciences
                Clinical Genetics
                Genetic Diseases
                Autosomal Dominant Diseases
                Polycystic Kidney Disease
                People and Places
                Geographical Locations
                Europe
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Regression Analysis
                Linear Regression Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Regression Analysis
                Linear Regression Analysis
                Medicine and Health Sciences
                Vascular Medicine
                Vascular Diseases
                Aneurysms
                Custom metadata
                Dataset used for prevalence calculation and clinical description of the cohort are within the paper's Supporting Information files. All genetic and phenotypic data have been anonymized are available at the LOVD3.0 platform (24, 25) here: https://databases.lovd.nl/shared/genes/PKD1/ and here: https://databases.lovd.nl/shared/genes/PKD2/.

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