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抗抑郁药和抗精神病药的副作用与个体化处方:系统评价与数字工具开发。

Antidepressant and antipsychotic side-effects and personalised prescribing: a systematic review and digital tool development.

机构信息

Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Imperial College London, London, UK.

Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Imperial College London, London, UK.

出版信息

Lancet Psychiatry. 2023 Nov;10(11):860-876. doi: 10.1016/S2215-0366(23)00262-6. Epub 2023 Sep 26.


DOI:10.1016/S2215-0366(23)00262-6
PMID:37774723
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10878984/
Abstract

BACKGROUND: Side-effects of psychiatric medication impair quality of life and functioning. Furthermore, they contribute to morbidity, mortality, stigma, and poor treatment concordance resulting in relapse of psychiatric illness. Guidelines recommend discussing side-effects with patients when making treatment decisions, but a synthesis of antidepressant and antipsychotic side-effects to guide this process is missing, and considering all side-effects is a complex, multidimensional process. We aimed to create comprehensive databases of antipsychotic and antidepressant side-effects, and a digital tool to support database navigation. METHODS: To create the databases, we did an umbrella review of Embase, PsycINFO, and MEDLINE from database inception to June 26, 2023. We included meta-analyses of randomised controlled trials examining antipsychotic monotherapy in the treatment of schizophrenia or antidepressant monotherapy in the treatment of major depressive disorder. We included meta-analyses in adults (aged ≥18 years) that assessed drugs with a common comparator. The search was complemented by a review of national and international guidelines and consensus statements for the treatment of major depressive disorder and schizophrenia in adults. Effect sizes for antipsychotic and antidepressant side-effects were extracted from meta-analyses examining the largest number of drugs. In cases of incomplete meta-analytic coverage, data were imputed on the basis of guideline-derived ordinal rankings or, if imputation was not possible, ordinal scores were extracted. Both meta-analytic and ordinal outcomes were normalised to provide values between 0 and 1. We then constructed a digital tool, the Psymatik Treatment Optimizer, to combine the side-effect databases with side-effect concerns of an individual user, to enable users to select side-effects of concern and the relative degree of concern for each side-effect. Concern weightings and the side-effect databases are synthesised via a multicriteria decision analysis method (technique for order of preference by similarity to ideal situation, or TOPSIS). FINDINGS: Of 3724 citations, 14 articles containing 68 meta-analyses of individual side-effects met inclusion criteria. After review of 19 guidelines, seven provided ordinal data. Antipsychotic data were extracted from five studies (11 meta-analyses, n=65 594 patients) and four guidelines, and antidepressant data were extracted from three guidelines. The resultant databases included data on 32 antipsychotics (14 side-effects) and 37 antidepressants (nine side-effects). The databases highlighted the clinical dilemma associated with balancing side-effects, with avoidance of one side-effect (eg, weight gain for antipsychotics) increasing the risk of others (eg, akathisia). To aid with this dilemma, the Psymatik Treatment Optimizer synthesises the side-effect databases with individual user-defined concern weights. After computing up to 5851 pairwise comparisons for antidepressants and 5142 pairwise comparisons for antipsychotics, Psymatik ranks treatments in order of preference for the individual user, with the output presented in a heatmap. INTERPRETATION: By facilitating collaborative, personalised, and evidence-based prescribing decisions, the side-effect databases and digital application supports care delivery that is consistent with international regulatory guidance for the treatment of schizophrenia and depression, and it therefore has promise for informing psychiatric practice and improving outcomes. FUNDING: National Institute for Health and Care Research, Maudsley Charity, Wellcome Trust, Medical Research Council.

摘要

背景:精神药物的副作用会降低生活质量和身体机能。此外,这些副作用还会导致发病率、死亡率、耻辱感和较差的治疗依从性,从而导致精神疾病复发。指南建议在做出治疗决策时与患者讨论副作用,但缺乏针对抗抑郁药和抗精神病药副作用的综合指南来指导这一过程,而且考虑所有副作用是一个复杂的多维过程。我们旨在创建抗精神病药和抗抑郁药副作用的综合数据库,并创建一个数字工具来支持数据库导航。

方法:为了创建这些数据库,我们对 Embase、PsycINFO 和 MEDLINE 进行了伞式综述,时间范围为数据库建立到 2023 年 6 月 26 日。我们纳入了抗精神病药单药治疗精神分裂症或抗抑郁药单药治疗重度抑郁症的随机对照试验的荟萃分析。我们纳入了针对成年人(年龄≥18 岁)的荟萃分析,评估了具有常见对照药物的药物。该检索由国家和国际治疗精神分裂症和重度抑郁症的指南和共识声明的综述进行补充。从评估最多药物的荟萃分析中提取抗精神病药和抗抑郁药副作用的效应大小。在不完全的荟萃分析覆盖的情况下,根据指南得出的等级排名进行数据推断,如果推断不可行,则提取等级评分。将两者的汇总结果都归一化,得到介于 0 和 1 之间的值。然后,我们构建了一个数字工具,即 Psymatik 治疗优化器,将副作用数据库与个体用户的副作用问题结合起来,使用户能够选择关注的副作用及其对每个副作用的关注程度。使用多准则决策分析方法(理想情况下的相似性偏好排序技术或 TOPSIS)综合关注权重和副作用数据库。

结果:从 3724 条引文中,有 14 篇文章包含 68 项个体副作用的荟萃分析符合纳入标准。在审查了 19 项指南后,有 7 项提供了等级数据。抗精神病药数据来自 5 项研究(11 项荟萃分析,n=65594 名患者)和 4 项指南,抗抑郁药数据来自 3 项指南。最终的数据库包括 32 种抗精神病药(14 种副作用)和 37 种抗抑郁药(9 种副作用)的数据。这些数据库突出了与平衡副作用相关的临床困境,避免一种副作用(例如抗精神病药的体重增加)会增加其他副作用(例如静坐不能)的风险。为了帮助解决这一困境,Psymatik 治疗优化器将副作用数据库与个体用户定义的关注权重相结合。在为抗抑郁药计算了多达 5851 次成对比较和为抗精神病药计算了 5142 次成对比较后,Psymatik 根据个体用户的偏好对治疗方法进行排序,并以热图的形式呈现输出结果。

解释:通过促进协作、个性化和基于证据的处方决策,副作用数据库和数字应用支持符合国际监管指南的精神分裂症和抑郁症治疗的护理提供,因此有望为精神科实践提供信息并改善结果。

资金来源:英国国家卫生与保健研究院、Maudsley 慈善基金会、威康信托、医学研究理事会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60b3/10878984/fddff7d73737/gr5a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60b3/10878984/571e3949130f/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60b3/10878984/97543873b842/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60b3/10878984/6cfdddbf0e59/gr3a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60b3/10878984/ca5dcbefea34/gr4a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60b3/10878984/fddff7d73737/gr5a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60b3/10878984/571e3949130f/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60b3/10878984/97543873b842/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60b3/10878984/6cfdddbf0e59/gr3a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60b3/10878984/ca5dcbefea34/gr4a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60b3/10878984/fddff7d73737/gr5a.jpg

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