Liu C, Li Wan Po A, Blumhardt L D
Division of Clinical Neurology, Faculty of Medicine, University Hospital, Nottingham, UK.
J Neurol Neurosurg Psychiatry. 1998 Jun;64(6):726-9. doi: 10.1136/jnnp.64.6.726.
To review the outcome measures commonly used in phase III treatment trials of relapsing-remitting multiple sclerosis and to introduce a method of data analysis which is clinically appropriate for the often reversible disability in this type of multiple sclerosis.
The conventional end point measures for disability change are inadequate and potentially misleading. Those using the disability difference between study entry and completion do not take into account serial data or disease fluctuations. Rigid definitions of "disease progression" based on two measurements of change in disability several months apart, do not assess worsening after the defined "end point", nor the significant proportion of erroneous "treatment failures" which result from subsequent recovery from relapses that outlast the end point. Assessing attacks merely by counting their frequency ignores the variation in magnitude and duration. These problems can be largely circumvented by integrating the area under a disability-time curve (AUC), a technique which utilises all serial measurements at scheduled visits and during relapses to summarise the total neurological dysfunction experienced by an individual patient on any particular clinical scale during a study period.
The "summary measure" statistic AUC incorporates both transient and progressive disability into an overall estimate of the dysfunction that was experienced by a patient during a period of time. It is statistically more powerful and clinically more meaningful than conventional methods of assessing disability changes, particularly for trials which are too short to expect to disclose major treatment effects on irreversible disability in patients with a fluctuating disease.
回顾复发缓解型多发性硬化症Ⅲ期治疗试验中常用的疗效指标，并介绍一种数据分析方法，该方法在临床上适用于这类多发性硬化症中常为可逆性的残疾情况。
用于评估残疾变化的传统终点指标并不充分，且可能产生误导。那些采用研究入组时与结束时残疾差异的指标，未考虑连续数据或疾病波动情况。基于相隔数月的两次残疾变化测量对“疾病进展”进行的严格定义，既未评估在规定“终点”之后的病情恶化情况，也未考虑因复发后恢复时间超过终点而导致的大量错误“治疗失败”情况。仅通过计算发作次数来评估发作情况，忽略了发作程度和持续时间的差异。通过整合残疾时间曲线下面积（AUC），这些问题在很大程度上可以得到规避，该技术利用在预定访视时以及复发期间的所有连续测量数据，来总结个体患者在研究期间在任何特定临床量表上所经历的总体神经功能障碍。
“汇总指标”统计量AUC将短暂性和进行性残疾都纳入到对患者在一段时间内所经历功能障碍的总体评估中。与评估残疾变化的传统方法相比，它在统计学上更具效力，在临床上更具意义，特别是对于那些因时间过短而无法期望揭示对病情波动患者不可逆残疾产生重大治疗效果的试验而言。
