提高我们对精神疾病体内模型的理解:一项系统回顾和荟萃分析的方案。

Evidence-based preclinical medicine Pub Date : 2016-12-01 Epub Date: 2017-03-17 DOI:10.1002/ebm2.22
Zsanett Bahor, Cristina Nunes-Fonseca, Lindsay D G Thomson, Emily S Sena, Malcolm R Macleod
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引用次数: 2

摘要

精神病代表了一组症状,目前可用的治疗方法并非普遍有效,而且经常伴有不良副作用。随着对潜在生物学的更深入了解,以及随后引入新的治疗方法,临床管理可能会得到改善。由于许多临床候选药物是通过体内建模确定的,因此对临床前领域的更深入了解可能有助于我们理解为什么迄今为止将动物模型的结果转化为心理健康临床实践的效果很弱。我们打算用系统回顾和荟萃分析对精神障碍的体内模型进行一个浅层的、但广泛的、无偏见的实验综述。本协议描述了我们建议遵循的确切方法,以便定量回顾模型特征研究和调查新治疗方案效果的实验。我们感兴趣的是评估减少偏倚风险的措施报告的流行程度,以及用于验证这些模型的动物模型和结果测量的内部和外部有效性。这一代强有力的经验证据有可能确定需要改进的领域,为未来的研究途径提出建议,并最终告知我们所知道的,以改善目前精神病研究中实验室和床边之间的流失率。这样的审查还将支持减少研究中使用的动物数量和改进实验,以最大限度地发挥其在为该领域提供信息方面的价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving our understanding of the in vivo modelling of psychotic disorders: A protocol for a systematic review and meta-analysis.

Psychosis represents a set of symptoms against which current available treatments are not universally effective and are often accompanied by adverse side effects. Clinical management could potentially be improved with a greater understanding of the underlying biology and subsequently with the introduction of novel treatments. Since many clinical drug candidates are identified through in vivo modelling, a deeper understanding of the pre-clinical field, might help us understand why translation of results from animal models to inform mental health clinical practice has so far been weak. We set out to give a shallow, but broad unbiased overview of experiments looking at the in vivo modelling of psychotic disorders using a systematic review and meta-analysis. This protocol describes the exact methodology we propose to follow in order to quantitatively review both studies characterizing a model and those experiments that investigate the effects of novel therapeutic options. We are interested in assessing the prevalence of the reporting of measures to reduce risk of bias, and the internal and external validity of the animal models and outcome measures used to validate these models. This generation of strong empirical evidence has the potential to identify areas for improvement, make suggestions for future research avenues, and ultimately inform what we think we know to improve the current attrition rate between bench and bedside in psychosis research. A review like this will also support the reduction of animal numbers used in research and the refinement of experiments to maximize their value in informing the field.

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