San Francisco VA Health Care System, University of California San Francisco, San Francisco, California; Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, California.
San Francisco VA Health Care System, University of California San Francisco, San Francisco, California; Northern California Institute for Research and Education, San Francisco, California.
Biol Psychiatry Cogn Neurosci Neuroimaging. 2021 Feb;6(2):178-187. doi: 10.1016/j.bpsc.2020.10.010. Epub 2020 Oct 24.
Clinical outcomes vary for individuals at clinical high risk (CHR) for psychosis, ranging from conversion to a psychotic disorder to full remission from the risk syndrome. Given that most CHR individuals do not convert to psychosis, recent research efforts have turned toward identifying specific predictors of CHR remission, a task that is conceptually and empirically dissociable from the identification of predictors of conversion to psychosis, and one that may reveal specific biological characteristics that confer resilience to psychosis and provide further insights into the mechanisms associated with the pathogenesis of schizophrenia and those underlying a transient CHR syndrome. Such biomarkers may ultimately facilitate the development of novel early interventions and support the optimization of individualized care. In this review, we focus on two event-related brain potential measures, mismatch negativity and P300, that have attracted interest as predictors of future psychosis among CHR individuals. We describe several recent studies examining whether mismatch negativity and P300 predict subsequent CHR remission and suggest that intact mismatch negativity and P300 may reflect the integrity of specific neurocognitive processes that confer resilience against the persistence of the CHR syndrome and its associated risk for future transition to psychosis. We also highlight several major methodological concerns associated with these studies that apply to the broader literature examining predictors of CHR remission. Among them is the concern that studies that predict dichotomous remission versus nonremission and/or dichotomous conversion versus nonconversion outcomes potentially confound remission and conversion effects, a phenomenon we demonstrate with a data simulation.
临床高风险(CHR)人群的个体在精神病学方面的临床结局存在差异,从向精神病转变到完全缓解风险综合征。鉴于大多数 CHR 个体不会转变为精神病,最近的研究工作已经转向确定 CHR 缓解的具体预测因素,这一任务在概念上和经验上与预测向精神病转变的因素是分开的,并且可能揭示出赋予对精神病的抵抗力的特定生物学特征,并提供对与精神分裂症发病机制相关的机制的进一步了解以及导致短暂 CHR 综合征的机制。这些生物标志物最终可能有助于开发新的早期干预措施,并支持优化个体化护理。在这篇综述中,我们专注于两种事件相关脑电位测量,失匹配负波和 P300,它们作为 CHR 个体未来精神病的预测指标引起了关注。我们描述了几项最近的研究,这些研究检验了失匹配负波和 P300 是否可以预测随后的 CHR 缓解,并表明失匹配负波和 P300 的完整性可能反映了特定神经认知过程的完整性,这些过程赋予了对 CHR 综合征的持续性及其未来向精神病转变的风险的抵抗力。我们还强调了与这些研究相关的几个主要方法学问题,这些问题适用于检查 CHR 缓解预测因素的更广泛文献。其中之一是,预测二分类缓解与非缓解和/或二分类转变与非转变结局的研究可能会混淆缓解和转变的影响,我们通过数据模拟证明了这一现象。