Mucociliary clearance as an outcome measure for cystic fibrosis clinical research.

Mucociliary clearance as an outcome measure for cystic fibrosis clinical research.
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DOI:
10.1513/pats.200703-042br
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发表时间:
2007-08-01
期刊:
Proceedings of the American Thoracic Society
影响因子:
--
通讯作者:
Bennett, William D
Bennett, William D
中科院分区:
其他
文献类型:
--
作者:
Donaldson, Scott H;Corcoran, Timothy E;Bennett, William D

文献摘要

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目前囊性纤维化(CF)病理生理学的概念将离子转运异常与气道表面液体(ASL)水化减少和粘液清除受损联系起来。纠正导致ASL脱水的缺陷可能会阻止粘液清除的降解,从而防止CF肺部疾病的发生和/或进展。一些针对疾病发病机制的早期阶段的新型治疗药物目前正在开发中,用于治疗CF肺病。因此,迫切需要开发直接评估这些药物对靶器官潜在病理生理过程影响的方法。粘液纤毛清除率(MCC)的测量是一个高度生物学相关的结果,但需要进一步发展。在这里,我们描述了MCC测量的重要方法方面,以及过去限制其作为结果测量的问题。此外,我们概述了现在正在进行的步骤,并将在未来进行,以提高这些研究在临床试验中的表现。优化和标准化MCC测量的系统方法将大大提高我们在药物开发相对早期阶段评估新疗法的能力。由此产生的数据可以用来选择那些应该迅速推进到更大的临床试验的候选人。
Current concepts of cystic fibrosis (CF) pathophysiology link ion transport abnormalities to reduced airway surface liquid (ASL) hydration and impaired mucus clearance. It is likely that correction of the defects that cause ASL dehydration will prevent degradation of mucus clearance, thereby preventing the initiation and/or progression of CF lung disease. A number of novel therapeutic agents aimed at the earliest steps in disease pathogenesis are now under development for the treatment of CF lung disease. Consequently, there is a tremendous need to develop methods that directly assess the effects of these agents on the underlying pathophysiologic process in the target organ. The measurement of mucociliary clearance (MCC) is a highly biologically relevant outcome, but one that is in need of further development. Here, we describe important methodologic aspects of MCC measurement and issues that have limited its use as an outcome measure in the past. Furthermore, we outline the steps that are being carried out now, and will be carried out in the future, to improve the performance of these studies in clinical trials. A systematic approach to optimizing and standardizing the measurement of MCC should greatly advance our ability to assess novel therapies at a relatively early stage of drug development. The resulting data may then be used to select those candidates that should be rapidly advanced into larger clinical trials.