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利用纵向残疾曲线预测复发缓解型多发性硬化症的病程。

Predicting the course of relapsing-remitting MS using longitudinal disability curves.

作者信息

Achiron Anat

机构信息

Multiple Sclerosis, Center Sheba Medical Center (affiliated to Tel-Aviv University, Sackler School of Medicine, Israel), Tel-Hashomer, Israel.

出版信息

J Neurol. 2004 Sep;251 Suppl 5:v65-v68. doi: 10.1007/s00415-004-1510-0.

Abstract

BACKGROUND AND OBJECTIVE

Multiple sclerosis (MS) is a chronic, progressive disease of the central nervous system that generally occurs in adults under the age of 40 years and ultimately leads to severe neurological disability. Following the progression of MS by monitoring changes in disability levels can facilitate treatment decisions taken by physicians. The aim of this review is to present longitudinal disability curves enabling the assessment of disease progression in patients with relapsing-remitting (RR)MS.

METHODS

Patients with a definite diagnosis of MS and an RR disease course were identified using the Multiple Sclerosis Center computerised database. Patients were stratified into major percentile groups based on their Expanded Disability Status Scale (EDSS) score 1 year after disease onset. Model disability curves for each percentile were constructed using mean consecutive EDSS scores for 10 years after disease onset. Model curves were generated by smoothing (parametric and non-parametric regression) and curve approximation (linear regression and moving averages). The predictive ability of model curves was validated by superimposing data from a separate group of patients with RRMS.

RESULTS

Disability curves were constructed using data from 1001 patients. A significant difference between the initial percentile assignment and disability progression was indicated by the log-rank test (p < 0.001). Kaplan-Meier and life table analyses demonstrated the validity of the model in predicting disease progression. The probability of experiencing more severe disability than predicted (i. e. deviating from the initial percentile to a higher percentile over time) ranged from 6.5 % (50th percentile) to 15.4 % (75th percentile), while the probability of experiencing less severe disability than predicted (i. e. deviating from the initially assigned percentile to a lower percentile over time) ranged from 6.9% (50th percentile) to 1.6 % (75th percentile). Both suggest reasonable predictive validity.

CONCLUSION

In MS, longitudinal disability curves can help to assess individual patient disability, map the effects of immunomodulatory treatments over time, and generally build on the overall clinical impression of disease progression. Such models can act as a tool to aid and support the clinical decision-making process. This review is based on the study published in Multiple Sclerosis (2003) 9:486-491.

摘要

背景与目的

多发性硬化症(MS)是一种中枢神经系统的慢性进行性疾病,通常发生在40岁以下的成年人中,最终会导致严重的神经功能残疾。通过监测残疾水平的变化来跟踪MS的进展情况,有助于医生做出治疗决策。本综述的目的是呈现纵向残疾曲线,以便评估复发缓解型(RR)MS患者的疾病进展。

方法

利用多发性硬化症中心的计算机数据库,确定确诊为MS且病程为RR型的患者。根据疾病发作1年后的扩展残疾状态量表(EDSS)评分,将患者分为主要百分位数组。使用疾病发作后10年的连续平均EDSS评分,为每个百分位数构建模型残疾曲线。通过平滑(参数回归和非参数回归)和曲线近似(线性回归和移动平均值)生成模型曲线。通过叠加另一组RRMS患者的数据,验证模型曲线的预测能力。

结果

使用1001例患者的数据构建了残疾曲线。对数秩检验表明初始百分位数分配与残疾进展之间存在显著差异(P<0.001)。Kaplan-Meier分析和生命表分析证明了该模型在预测疾病进展方面的有效性。经历比预测更严重残疾的概率(即随着时间的推移从初始百分位数偏离到更高百分位数)范围为6.5%(第50百分位数)至15.4%(第75百分位数),而经历比预测更轻残疾的概率(即随着时间的推移从最初分配的百分位数偏离到更低百分位数)范围为6.9%(第50百分位数)至1.6%(第75百分位数)。两者均显示出合理的预测有效性。

结论

在MS中,纵向残疾曲线有助于评估个体患者的残疾情况,描绘免疫调节治疗随时间的效果,并总体上基于疾病进展的整体临床印象。此类模型可作为辅助和支持临床决策过程的工具。本综述基于发表于《多发性硬化症》(2003年)第9卷第486 - 491页的研究。

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