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Descriptive epidemiology of amyotrophic lateral sclerosis: new evidence and unsolved issues
  1. G Logroscino1,
  2. B J Traynor2,3,
  3. O Hardiman4,
  4. A Chio’5,
  5. P Couratier6,
  6. J D Mitchell7,
  7. R J Swingler8,
  8. E Beghi9,
  9. for EURALS
  1. 1
    Department of Epidemiology HSPH, Harvard University, Boston, Massachusetts, USA
  2. 2
    Section on Developmental Genetic Epidemiology, National Institutes of Health, Bethesda, Maryland, USA
  3. 3
    Department of Neurology, Johns Hopkins University, Baltimore, Maryland, USA
  4. 4
    Department of Neurology, Beaumont Hospital and Royal College of Surgeons in Ireland, Dublin, Ireland
  5. 5
    Dipartimento di Neuroscienze, Universitè di Torino, Torino, Italy
  6. 6
    Service de Neurologie, CHU Limoges, Limoges, France
  7. 7
    ALS Care and Research Centre, Royal Preston Hospital, Preston, UK
  8. 8
    Department of Neurology, Ninewells Hospital, Dundee, UK
  9. 9
    Istituto Ricerche Farmacologiche Mario Negri Milano and Clinica Neurologica, Universitè di Milano-Bicocca, Monza, Italy
  1. Dr G Logroscino, Department of Epidemiology HSPH 3-819 Harvard University, 677 Huntington Avenue, Boston, Massachusetts 02115, USA; glogrosc{at}hsph.harvard.edu

Abstract

Amyotrophic lateral sclerosis (ALS) is a relatively rare disease with a reported population incidence of between 1.5 and 2.5 per 100 000 per year. Over the past 10 years, the design of ALS epidemiological studies has evolved to focus on a prospective, population based methodology, employing the El Escorial criteria and multiple sources of data to ensure complete case ascertainment. Five such studies, based in Europe and North America, have been published and show remarkably consistent incidence figures among their respective Caucasian populations. Population based studies have been useful in defining clinical characteristics and prognostic indicators in ALS. However, many epidemiological questions remain that cannot be resolved by any of the existing population based datasets. The working hypotheses is that ALS, like other chronic diseases, is a complex genetic condition, and the relative contributions of individual environmental and genetic factors are likely to be relatively small. Larger studies are required to characterise risks and identify subpopulations that might be suitable for further study. This current paper outlines the contribution of the various population based registers, identifies the limitations of the existing datasets and proposes a mechanism to improve the future design and output of descriptive epidemiological studies.

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Footnotes

  • Competing interests: None.

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