Department of Life Sciences, University of Siena, 53100, Siena, Italy.
Department of Medical Sciences, Surgery and Neurosciences, University of Siena, 53100, Siena, Italy.
Neurol Sci. 2020 Feb;41(2):397-402. doi: 10.1007/s10072-019-04090-0. Epub 2019 Nov 6.
An increase of prevalence and incidence of multiple sclerosis (MS) has been reported in several countries, especially taking into account a long-term evaluation. This increasing trend often reflects improved case identification and ascertainment due to the refinement of diagnostic criteria. The aim of this study was to update the prevalence rate of MS in Tuscany (central Italy) as of 2017, and to assess if there has been an increasing trend of prevalence in this Region considering a short period of analysis, from 2014 to 2017.
To capture prevalent cases, a case-finding algorithm based on administrative data, previously created and validated, was used. As data sources, we considered hospital discharge records, drug-dispensing records, disease-specific exemptions from copayment to health care, home and residential long-term care, and inhabitant registry.
As of January 1, 2017, 7809 cases were identified, of which 69.4% were females and 30.6% were males. Considering temporal variation, an increasing trend was observed, with standardized rates rising from 189.2 in 2014 to 208.7 per 100,000 in 2017.
Results confirm that prevalence increases every year, probably mainly due to the difference between incidence and mortality, resulting in an increasing trend. Moreover, administrative data may accurately identify MS patients in a routinary way and monitor this cohort along disease care pathways.
在多个国家,包括长期评估在内,多发性硬化症(MS)的患病率和发病率都有所增加。这种上升趋势通常反映了由于诊断标准的改进,病例识别和确定的改善。本研究的目的是更新截至 2017 年托斯卡纳(意大利中部)的 MS 患病率,并评估在该地区考虑到从 2014 年到 2017 年的短分析期,是否存在患病率上升的趋势。
为了发现现患病例,我们使用了一种基于先前创建和验证的行政数据的病例发现算法。作为数据源,我们考虑了住院记录、药物配药记录、针对特定疾病的医疗保健共付额豁免、家庭和长期居住护理以及居民登记。
截至 2017 年 1 月 1 日,共发现 7809 例病例,其中 69.4%为女性,30.6%为男性。考虑到时间变化,观察到一种上升趋势,标准化率从 2014 年的 189.2 上升到 2017 年的 208.7/100,000。
结果证实患病率每年都在增加,可能主要是由于发病率和死亡率之间的差异,导致上升趋势。此外,行政数据可以以常规方式准确识别 MS 患者,并沿着疾病护理途径监测这一组群。