Su Yi, Yu Hao, Wang Zhiren, Liu Sha, Zhao Liansheng, Fu Yingmei, Yang Yongfeng, Du Bo, Zhang Fuquan, Zhang Xiangrong, Huang Manli, Hou Cailan, Huang Guoping, Su Zhonghua, Peng Mao, Yan Ran, Zhang Yuyanan, Yan Hao, Wang Lifang, Lu Tianlan, Jia Fujun, Li Keqing, Lv Luxian, Wang Hongxing, Yu Shunying, Wang Qiang, Tan Yunlong, Xu Yong, Zhang Dai, Yue Weihua
Institute of Mental Health, The Sixth Hospital of Peking University, China; and Key Laboratory of Mental Health, Ministry of Health & National Clinical Research Center for Mental Disorders (Peking University), China.
Institute of Mental Health, The Sixth Hospital of Peking University, China; Key Laboratory of Mental Health, Ministry of Health & National Clinical Research Center for Mental Disorders (Peking University), China; and Department of Psychiatry, Jining Medical University, China.
BJPsych Open. 2021 Jun 29;7(4):e121. doi: 10.1192/bjo.2021.945.
Schizophrenia is a severe and complex psychiatric disorder that needs treatment based on extensive experience. Antipsychotic drugs have already become the cornerstone of the treatment for schizophrenia; however, the therapeutic effect is of significant variability among patients, and only around a third of patients with schizophrenia show good efficacy. Meanwhile, drug-induced metabolic syndrome and other side-effects significantly affect treatment adherence and prognosis. Therefore, strategies for drug selection are desperately needed. In this study, we will perform pharmacogenomics research and set up an individualised preferred treatment prediction model.
We aim to create a standard clinical cohort, with multidimensional index assessment of antipsychotic treatment for patients with schizophrenia.
This trial is designed as a randomised clinical trial comparing treatment with different kinds of antipsychotics. A total sample of 2000 patients with schizophrenia will be recruited from in-patient units from five clinical research centres. Using a computer-generated program, the participants will be randomly assigned to four treatment groups: aripiprazole, olanzapine, quetiapine and risperidone. The primary outcomes will be measured as changes in the Positive and Negative Syndrome Scale of schizophrenia, which reflects the efficacy. Secondary outcomes include the measure of side-effects, such as metabolic syndromes. The efficacy evaluation and side-effects assessment will be performed at baseline, 2 weeks, 6 weeks and 3 months.
This trial will assess the efficacy and side effects of antipsychotics and create a standard clinical cohort with a multi-dimensional index assessment of antipsychotic treatment for schizophrenia patients.
This study aims to set up an individualized preferred treatment prediction model through the genetic analysis of patients using different kinds of antipsychotics.
精神分裂症是一种严重且复杂的精神障碍,需要基于丰富经验进行治疗。抗精神病药物已成为精神分裂症治疗的基石;然而,患者之间的治疗效果存在显著差异,只有约三分之一的精神分裂症患者显示出良好疗效。同时,药物引起的代谢综合征和其他副作用显著影响治疗依从性和预后。因此,迫切需要药物选择策略。在本研究中,我们将进行药物基因组学研究并建立个性化的优选治疗预测模型。
我们旨在创建一个标准临床队列,对精神分裂症患者的抗精神病治疗进行多维度指标评估。
本试验设计为一项比较不同种类抗精神病药物治疗的随机临床试验。将从五个临床研究中心的住院部招募2000例精神分裂症患者作为总样本。使用计算机生成的程序,参与者将被随机分配到四个治疗组:阿立哌唑、奥氮平、喹硫平和利培酮。主要结局将以精神分裂症阳性和阴性症状量表的变化来衡量,该量表反映疗效。次要结局包括副作用的测量,如代谢综合征。疗效评估和副作用评估将在基线、2周、6周和3个月时进行。
本试验将评估抗精神病药物的疗效和副作用,并创建一个对精神分裂症患者抗精神病治疗进行多维度指标评估的标准临床队列。
本研究旨在通过对使用不同种类抗精神病药物的患者进行基因分析,建立个性化的优选治疗预测模型。