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首页> 外文期刊>European neuropsychopharmacology: the journal of the European College of Neuropsychopharmacology >The impact of trial characteristics on premature discontinuation of antipsychotics in schizophrenia
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The impact of trial characteristics on premature discontinuation of antipsychotics in schizophrenia

机译:试验特征对精神分裂症中抗精神病药的提前终止的影响

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Patient dropout is common in mental health trials. It is important to understand why patients drop out from trials, so that measures can be taken to minimize its occurrence. This research sought to identify trial characteristics that have an impact on premature discontinuation in antipsychotic trials for schizophrenia. Methods: Poisson regression analysis was applied with dropout rate per patient-week as the dependent variable and trial characteristics as independent variables. Multinomial logistic regression analysis was performed to examine whether the same characteristics predict whether patients drop out without providing any outcome data and whether they drop out with sufficient early data for a 'last observation carried forward' analysis to be performed. Results: trials with adequate allocation concealment, double blinding, placebo as control, higher precision, larger trial size, at least three treatment arms, recent publication, conduct in the United States and enrollment of inpatients were all associated with higher dropout rates. Similar factors were associated with whether a patient was more likely to be evaluated at least once, or be excluded entirely from the analysis. However, blinding status did not predict the former type of dropout, and allocation concealment, higher precision and larger sample size, number of arms, recent publication and recruiting inpatient did not predict the latter type of dropout. Conclusions: high dropout rates in antipsychotic trials can be associated with various characteristics, and appears to be particularly associated with use of placebo and study size.
机译:在心理健康试验中,患者辍学很常见。重要的是要了解为什么患者退出试验,以便可以采取措施以最大程度地减少其发生。这项研究试图确定对精神分裂症抗精神病药物试验中的过早停药有影响的试验特征。方法:采用泊松回归分析,以每患者每周的辍学率作为因变量,以试验特征作为自变量。进行了多项逻辑回归分析,以检查相同的特征是否可以预测患者是否在没有提供任何结果数据的情况下退学,以及他们是否具有足够的早期数据以进行“最后观察结转”分析。结果:隐藏适当分配,双重盲法,以安慰剂为对照的试验,更高的精密度,更大的试验规模,至少三个治疗组,最近发表的文献,在美国的行为和住院患者的入选率均与辍学率较高相关。类似的因素与患者是否更有可能至少被评估一次或完全从分析中排除有关。然而,致盲状态不能预测前者的辍学类型,分配隐匿性,更高的准确度和更大的样本量,臂数,最近的出版物和招募住院病人都不能预测后者的类型。结论:抗精神病药物试验的高辍学率可能与多种特征有关,并且似乎与安慰剂的使用和研究规模特别相关。

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