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Personalise antidepressant treatment for unipolar depression combining individual choices risks and big data (PETRUSHKA): rationale and protocol

机译:结合个人选择风险和大数据个性化针对单相抑郁的抗抑郁药治疗(PETRUSHKA):原理和方案

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摘要

Matching treatment to specific patients is too often a matter of trial and error, while treatment efficacy should be optimised by limiting risks and costs and by incorporating patients’ preferences. Factors influencing an individual’s drug response in major depressive disorder may include a number of clinical variables (such as previous treatments, severity of illness, concomitant anxiety etc) as well demographics (for instance, age, weight, social support and family history). Our project, funded by the National Institute of Health Research, is aimed at developing and subsequently testing a precision medicine approach to the pharmacological treatment of major depressive disorder in adults, which can be used in everyday clinical settings.
机译:将治疗与特定患者相匹配通常是一个反复试验的问题,而应该通过限制风险和成本并结合患者的喜好来优化治疗效果。影响个人在重度抑郁症中的药物反应的因素可能包括许多临床变量(例如以前的治疗方法,疾病的严重程度,伴随的焦虑症等)以及人口统计资料(例如年龄,体重,社会支持和家族史)。我们的项目由美国国立卫生研究院(National Institute of Health Research)资助,旨在开发并随后测试一种精确的医学方法,用于治疗成年人的重性抑郁症,并可以在日常临床中使用。

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