Department of Health Sciences, University of Pavia, Pavia, Italy.
Neuroepidemiology. 2012;38(2):100-5. doi: 10.1159/000336002. Epub 2012 Feb 24.
Previous studies have reported a prevalence estimate of myasthenia gravis (MG) from 7.7 to 11.1 per 100,000 inhabitants in Europe. Moreover, the study of the geographical distribution of MG should be useful to generate specific hypotheses. The aims are to estimate MG prevalence and to investigate its geographical variation in a delimited area in Northern Italy.
The primary source of data was the MG database of the Neurological Institute of Pavia and all other sources of case collection in and outside the province. We adopted a Bayesian approach to analyze MG geographical variation within the finest geographical grid.
We identified 119 live MG prevalent cases resident in the province of Pavia on December 31, 2008. The overall crude prevalence was 24 per 100,000 inhabitants. The Bayesian analysis identified a small cluster of higher MG prevalence in the northern area of the province.
The estimated MG prevalence sets the province of Pavia among the high-risk areas. The identification of high/low MG risk areas deserves further investigation of genetic and environmental factors possibly related to a major risk of the disease in that area.
既往研究报道，欧洲每 10 万人中 MG 的患病率估计值为 7.7 至 11.1。此外，研究 MG 的地理分布有助于提出具体假设。本研究旨在评估意大利北部一个限定区域内 MG 的患病率及其地理变异。
本研究的数据来源于帕维亚神经研究所的 MG 数据库以及省内和省外的其他病例采集源。我们采用贝叶斯方法在最细的地理网格内分析 MG 的地理变异。
我们在 2008 年 12 月 31 日确定了居住在帕维亚省的 119 例 MG 现患病例。总粗患病率为 24/10 万。贝叶斯分析确定了该省北部存在 MG 高患病率的小簇。
MG 的估计患病率将帕维亚省置于高危区域之列。高/低 MG 风险区域的识别值得进一步调查与该区域疾病高风险相关的遗传和环境因素。
