Measuring the prevalence and incidence of disease serves several important functions. First, each measure enables health planners to estimate the number of existing cases (prevalence) and new cases (incidence) that one would expect to find in a community and hence provide the appropriate health staff required for their care. Second, by comparing age-standardized rates in different populations or over different time periods, one may observe differences, which if not artifactual or merely because of chance, that provide etiological clues and enable the formulation of hypotheses concerning risk factors. Marked changes over time, unless a result of increased disease awareness and hence a greater likelihood of diagnosis, strongly suggest an environmental factor or a genetic environmental interaction. Geographical variations are more complex as they may reflect differences in health services, variations in disease survival if only comparing prevalence rates, methodological differences in study design and/or diagnostic criteria, chance variations, or genuine population differences in genetic and/ or environmental factors.
Current consensus diagnostic criteria for PSP and MSA were only published in 1996 and 1999 respectively (2,3). Prevalence studies prior to these dates relied upon heterogeneous groups of published criteria and some used none (or did not state which were used) at all. This makes any interpre-
From: Current Clinical Neurology: Atypical Parkinsonian Disorders Edited by: I. Litvan © Humana Press Inc., Totowa, NJ
tation of data from such studies even more complex as these different criteria would have had differing sensitivities and specificities (4). Even the current consensus criteria, which at least enable a more standardized approach, have yet to be tested in large-scale representative prognostic cohorts with postmortem-validated diagnoses so their true diagnostic utility remains to be elucidated.
Despite these difficulties, such studies provide the empirical basis for suggesting or testing ideas concerning causal agents.
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