A review of the natural history and epidemiology of multiple sclerosis: implications for resource allocation and health economic models.

A review of the natural history and epidemiology of multiple sclerosis: implications for resource allocation and health economic models.
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多发性硬化症的自然史和流行病学回顾:对资源分配和健康经济模型的影响。

DOI:
10.3310/hta6100
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发表时间:
2002
影响因子:
3.6
通讯作者:
P. Tappenden
P. Tappenden
中科院分区:
医学2区
文献类型:
--
作者:
Richardson Rg;F. Sampson;S. Beard;P. Tappenden

文献摘要

被引文献

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背景: 多发性硬化症 (MS) 是一种进行性 具有一定模式的中枢神经系统退行性疾病 取决于疾病类型的症状 以及病变部位。随着伤害的累积, 症状变得更加持久和进展 随之而来的是残疾。 MS 是一种以 患者之间存在很大差异 随着时间的推移,个体 分类困难。 MS 对生活质量有重大影响 大多数患者多年来的生活质量(QoL) 疾病平均持续30年。这种疾病是 女性的发病率是男性的两倍,并且 在经济最富有成效的年份达到顶峰 的生活。 为了规划社会经济 MS 对患者、其家庭和社会的影响 总体而言,对自然有更好的认识 需要该疾病的病史和流行病学。 特别需要准确描述 疾病进展的模式和影响 随着时间的推移。 审查目的: 当前报告有三个主要目标: • 审查现有的自然历史数据 • 审查现有的流行病学数据 • 回顾建模文献并概述 理论模型的结构,可以是 未来开发和使用以反映 就疾病进展而言,多发性硬化症的病程, 不同阶段的健康效用和成本 这种疾病。 方法: 进行文献检索以确定 所有与自然历史相关的论文 MS 的流行病学和 MS 相关模型。 MEDLINE、EMBASE 和科学引文 使用了索引。以下包含 应用标准: • 描述的诊断分类系统 • 描述的案件查明方法 • 在同一地点进行的时间序列 • 地理研究进行了 限期 • 案例定义与观察者一致 随着时间和地点 • 报告了至少100 个病例的研究。 结果: MS 的自然史: 最常引用的身体和认知 该疾病的影响包括:虚弱、疲劳、 共济失调、膀胱不适、肠道问题、 感觉影响和视力障碍。 最受支持的评分工具 MS 的功能效应是(扩展) 残疾状况量表((E)DSS)。规模 范围从 1(最不严重)到 10(死亡 女士)。但规模并不理想,因为 对物理效应存在偏见 疾病(尤其是步行) 而非认知效应。 复发缓解型多发性硬化症的复发率各不相同 对于个人来说,随着时间的推移, 人与人之间,但有一个共同点 更频繁的恶化模式 复发,然后是长期较低的利率。 这使得评估治疗效果 在一个极其有问题的人身上。高 疾病发作时的复发率 对不良预后的预测有限。 MS 的流行病学: 英格兰和威尔士的流行病学研究 已经给出了一系列流行率估计值,但 估计平均每人约 110 名患者 10万人口。有良好的国际化 流行率地理差异的证据, 最好的描述是患病率增加 纬度(赤道以北和以南)。 英格兰和威尔士的数据中没有看到这一点, 但这可能是由于其他原因造成的变化 掩盖有限数据中的任何趋势。如果有这样一个 纬度变化确实适用于英格兰 威尔士,则患病率范围为每 100,000 人 104 至 156(从南到北),表明 资源后果的显着差异。 生存率的提高导致患病率增加。 建模: 关于建模使用的 30 篇论文综述 MS 进展情况,没有提供进展视图 从发病到死亡。加拿大人 对 1000 多名患者的纵向研究提供了 最详细的可用信息。它是 受限于其使用 DSS 作为衡量 进展和发布的详细程度, 但是,结合其他关于实用性的工作 DSS 指出,这些加拿大数据可以使用 准备马尔可夫模型(模型类型很好 适合用于慢性疾病)。 MS 的成本研究: 成本研究表明,普遍支持 患者的成本与 DSS 的增加有关 步骤。最新、最完整的英国研究显示 平均而言,EDSS 1-3.5 的患者会产生费用 每年约 3350 英镑,而 9560 英镑 每年 EDSS 6.5–8。类似公布数据 对健康效用表明时间的健康价值 DSS 状态的支出随着增加而减少 DSS 步骤。 结论: MS 是一种持续时间较长的慢性疾病 广泛的人类功能。短期研究 治疗效果研究无法完全评估 有意义的结果也没有提供信息 卫生经济分析所需的。所有 MS 应在整个过程中更好地监测患者 病程既改善其 照顾并更好地了解自然历史 的疾病。需要开发新方法 用于研究慢性病的治疗方法。 MS进展模型的开发 应纳入有关成本和 疾病不同阶段的生活质量 检查任何项目的长期成本效益 进展中的变化。 研究建议: 以下研究建议 已被识别。 • 多发性硬化症干预试验的时间应该更长 解决发病范围的持续时间 疾病的特征。 • 需要更多关于影响的信息 MS 对生活质量的影响以及与症状相关的费用 和残疾。 • (E)DSS 需要进一步发展 解决其在这种疾病中的缺点。 有关 MS 进展的综合数据 长期的患者,包括症状 经验丰富,复发率和持续时间是 每个 (E)DSS 状态都需要启用准确的 疾病进展影响的建模。
Background: Multiple sclerosis (MS) is a progressive degenerative disease of the CNS with a pattern of symptoms that depends on the type of disease and the site of lesions. As damage accumulates, symptoms become more permanent and progressive disability ensues. MS is a disease characterised by wide variations between patients and for the individual over time, thus making categorisation difficult. MS has a significant impact on the quality of life (QoL) for most patients over many years, with the disease lasting, on average, 30 years. The disease is twice as common in women than in men, and is at its peak in the most economically productive years of life. In order to plan for the social and economic impact of MS on patients, their families and society as a whole, a better understanding of the natural history and epidemiology of the disease is needed. In particular there is a need to describe accurately the patterns and impact of disease progression over time. Aim of the review: There are three main aims to the current report: • to review existing natural history data • to review existing epidemiology data • to review modelling literature and outline the structure of a theoretical model, which could be developed and used in the future to reflect the course of MS in terms of disease progression, health utility and cost at different stages of the disease. Methods: A literature search was conducted to identify all papers relevant to the natural history and epidemiology of MS and to MS-related models. MEDLINE, EMBASE and the Science Citation Index were used. The following inclusion criteria were applied: • diagnostic classification system described • methods of case ascertainment described • time series conducted in the same place • geographical studies conducted over a limited period • case definitions and observers consistent over time and place • studies with at least 100 cases reported. Results: Natural history of MS: The most commonly quoted physical and cognitive effects of the disease include: weakness, fatigue, ataxia, bladder complaints, bowel problems, sensory effects and visual impairment. The most supported tool for the grading of functional effects of MS is the (Expanded) Disability Status Scale ((E)DSS). The scale ranges from 1 (least severe) to 10 (death from MS). However, the scale is not ideal because there is a bias towards the physical effects of the disease (particularly ambulation) rather than the cognitive effects. Relapse rates in relapsing-remitting MS vary considerably over time for an individual and between individuals, but there is a general pattern of exacerbations of more frequent relapses, followed by long periods of lower rates. This makes assessment of the effects of treatments in an individual extremely problematic. High relapse rates at the onset of the disease give a limited prediction of poor prognosis. Epidemiology of MS: Epidemiological studies in England and Wales have given a range of prevalence estimates but the average is estimated at about 110 patients per 100,000 population. There is good international evidence of geographical variation in prevalence, best described by increasing prevalence with latitude (both north and south of the equator). This is not seen in the data for England and Wales, but this may be due to other causes of variation masking any trend in the limited data. If such a latitudinal variation did apply to England and Wales, then the prevalence would range from 104 to 156 per 100,000 (south to north), indicating substantial differences in resource consequences. Improved survival has led to increased prevalence. Modelling: Of 30 papers reviewed on the use of modelling of MS progression, none provide a view of progression from onset to death. A Canadian longitudinal study of over 1000 patients provides the most detailed information available. It is limited by its use of the DSS as a measure of progression and by the level of detail published, but, combined with other work on the utility of DSS states, these Canadian data could be used to prepare a Markov model (a model type well suited to use in a chronic disease). Cost studies of MS: Cost studies suggest that the general support costs for patients are related to increasing DSS step. The latest and most complete UK study shows that, on average, patients at EDSS 1–3.5 incur costs of around £3350 per annum compared with £9560 per annum at EDSS 6.5–8. Similar published data on health utility show that the health value of time spent in DSS states decreases with increasing DSS step. Conclusions: MS is a chronic disease of long duration affecting a wide range of human functions. Short research studies of treatment efficacy cannot fully assess meaningful outcomes nor deliver the information needed for health economic analyses. All MS patients should be better monitored throughout the course of the disease both to improve their care and to better understand the natural history of the disease. New methods need to be developed for researching treatments of chronic diseases. The development of a model of MS progression should incorporate information on costs and QoL at different stages of the disease in order to examine the long-term cost-effectiveness of any changes in progression. Research recommendations: The following research recommendations have been identified. • Trials on interventions for MS should be longer in duration to address the range of morbidity characteristic of the disease. • More information is needed on the effects of MS on QoL and the costs relating to symptoms and disability. • The (E)DSS requires further development to address its shortcomings in this disease. Comprehensive data on the progression of MS patients over the long term, including symptoms experienced and rates and length of relapse, are needed for each (E)DSS state to enable accurate modelling of the impact of disease progression.