Neurobehavioural predictors of depression relapse

我们的目标是a)确定抗抑郁药物(ADM)停药后复发的高风险神经影像指标；以及b)检查停药对缓解抑郁状态的影响。这是一项努力的一部分，目的是利用行为和神经生物学措施根据治疗结果对现有的临床精神病理实体进行分层。目前的药理学抑郁症治疗方案导致高达70%的患者最终缓解。由于停药后复发的风险很高(6个月内30-60个月)，指南建议在不同的时期继续治疗。然而，医生随后再次面临类似的问题：(I)患者以非常高的比率独立停止精神药物治疗，特别是在获得缓解后；以及(Ii)这些建议没有考虑到个体差异。安全停用ADM的标记物将有助于识别高危患者，在这些患者中，可以基于更有力的、个别有效的理由建议继续或进一步治疗。通过为治疗提供一个客观的终点，这可以增强与治疗的一致性。此外，尽管缓解后情感功能的神经生物学已经被研究过，但ADM的作用仍然很少被理解和描述。我们建议对76名缓解至少6个月并打算停止ADMS的患者进行为期6个月的随访研究，独立于本研究。我们将测试三种神经成像生物标记物在预测早期复发方面的能力，包括来自计算神经科学的新预测指标和已建立的预测指标。前者的几个版本已经确立了预测治疗反应的有效性。后者被认为是抑郁症易感性的一个重要特征。其次，受试者将经历一项既定的计划任务，以衡量令人厌恶的结果对计划的影响。这将被略微修改，以额外量化无助感。所有受试者将接受两次扫描，并被分成两组，大小相等。在1W2组，扫描1在停药前进行，扫描2在停药后5-20个ADM半衰期之间进行。在12W组，两次扫描均在停药前进行：停药前扫描1次，半衰期约5-20次，停药前扫描2次。我们将使用扫描1作为复发的主要预测因子。我们将使用小组之间的互动和扫描来检查停药的效果。在辅助分析中，我们还将使用组1W2中扫描1和扫描2之间的变化来预测复发。在所有情况下，我们都将测试超出临床可用测量的增量预测能力。

We aim to a) identify neuroimaging predictors of a high risk of Major Depressive Disorder (MDD) relapse after antidepressant medication (ADM) discontinuation; and b) examine the effect of medication withdrawal on the remitted depressed state. This is part of an endeavour to use behavioural and neurobiological measures to stratify existing clinical psychopathological entities with respect to treatment outcomes. Current pharmacological depression treatment options lead to eventual remission in up to 70\% of patients. Because the risk of relapse after discontinuation is high (30-60\% in 6 months), guidelines recommend treatment continuation for various periods. However, physicians then face a similar problem again: (i) patients discontinue psychotropic medication independently at very high rates,particularly after achieving remission; and (ii) these recommendations do not take individual variability into account. Markers for safe ADM discontinuation would help identify at-risk patients in whom continuation or further therapy could be recommended on stronger, individually valid, grounds. By providing an objective end-point to treatment this may enhance concordance with treatment. Furthermore, although the neurobiology of affective function after remission has been examined previously, the contribution of ADM remains poorly understood and characterised. We propose a 6-month follow-up study of 76 patients who have been in remission for a minimum of 6 months and intend to discontinue their ADMs independently of this study. We will test the ability of three neuroimaging biomarkers in predicting early relapse, including both novel predictors derived from computational neuroscience, and established ones. Several versions of the former have established validity in predicting response to treatment. The latter has been suggested to be one important characteristic of depression vulnerability. Second, subjects will undergo an established planning task that measures the impact of aversive outcomes on planning. This will be slightly modified to additionally quantify helplessness. All subjects will undergo scanning twice, and will be divided into two groups of equal size. In group 1W2, scan 1 will occur just prior to medication withdrawal, and scan 2 between 5-20 ADM half-lives after withdrawal. In group 12W, both scans will occur before withdrawal: scan 1 approx 5-20 ADM half-lives before, and scan 2 just prior to withdrawal. We will use scan 1 as the main predictor for relapse. We will use the interaction between groups and scans to examine the effect of medication withdrawal. In a subsidiary analysis, we will also use changes between scan 1 and 2 in group 1W2 to predict relapse. In all cases, we will test for incremental predictive power above and beyond clinically available measurements.