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评估精神分裂症临床试验中的认知功能。

Assessing cognitive function in clinical trials of schizophrenia.

机构信息

Department of Psychiatry, University of Cambridge, Cambridge, UK.

出版信息

Neurosci Biobehav Rev. 2010 Jul;34(8):1161-77. doi: 10.1016/j.neubiorev.2010.01.012. Epub 2010 Jan 25.

DOI:10.1016/j.neubiorev.2010.01.012
PMID:20105440
Abstract

Cognitive dysfunction in schizophrenia is an important target for novel therapies. Effectively measuring the cognitive effects of compounds in clinical trials of schizophrenia could be a major barrier to drug development. The Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) programme produced a consensus cognitive battery which is now widely used, however alternative assessments have advantages and disadvantages when compared with MATRICS. The Cambridge Neuropsychological Test Automated Battery (CANTAB) is a computerised assessment developed from animal behaviour paradigms and human neuropsychology. We review the utility of CANTAB according to MATRICS and CNTRICS recommendations. CANTAB tests have been used in more than 60 studies of psychotic disorders. Their neural bases are well understood through patient and neuroimaging studies and directly equivalent tests in rodents and non-human primates. The tests' sensitivity to pharmacological manipulation is well established. Future studies should collect more data regarding psychometric properties in patients over short time periods, and should continue to study the tests' relationships to functional outcomes. Computerised cognitive assessment may optimise the statistical power of cognitive trials by reducing measurement error and between-site variability and decreasing patient attrition through increased tolerability.

摘要

精神分裂症认知功能障碍是新型治疗方法的一个重要靶点。在精神分裂症临床试验中有效测量化合物对认知的影响可能是药物开发的主要障碍。精神分裂症的测量和治疗研究以改善认知(MATRICS)计划产生了一个共识认知电池,现在被广泛使用,但与 MATRICS 相比,替代评估具有优缺点。剑桥神经心理学测试自动化电池(CANTAB)是一种源自动物行为范式和人类神经心理学的计算机化评估。我们根据 MATRICS 和 CNTRICS 的建议,回顾 CANTAB 的效用。CANTAB 测试已在 60 多项精神疾病研究中使用。通过患者和神经影像学研究以及啮齿动物和非人类灵长类动物中的直接等效测试,已经很好地了解了它们的神经基础。这些测试对药物处理的敏感性得到了很好的证实。未来的研究应该在短时间内收集更多关于患者心理测量特性的数据,并继续研究这些测试与功能结果的关系。计算机化认知评估可以通过降低测量误差和站点间变异性以及通过提高耐受性降低患者流失率,从而优化认知试验的统计功效。

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