RESPONSE VARIABILITY IN TREATMENT RESISTANT DEPRESSION

描述（由申请人提供）：这是我们STAR*D项目多位点协作辅助研究的修订，在STAR*D项目中，我们提出研究生物标志物，通过前瞻性识别治疗难治性抑郁症（TRD）患者，可能有助于指导治疗。随机临床试验和自然治疗的初步数据表明，定量脑电图（QEEG）测量的一致性与药物治疗的反应和无反应相关；治疗早期前额叶活动的变化预示着后期的反应。初步数据表明，使用一致性指标的生物标志物模型可以识别(a)对STAR*D方案2级规定的治疗具有耐药性的患者，以及(b)具有初始但非持续的“安慰剂样”反应的患者。这种前瞻性识别将允许医生更早地进行更复杂的治疗方案，并获得更好的临床结果。该提案的修订内容包括：扩展使用一致性生物标志物的基本原理、STAR*D方案的更多细节、额外的试点数据以及为反映最近STAR*D入组数据而进行的受试者流量预测。该项目的三个具体目标是：(1)评估神经生理生物标志物在有效治疗试验环境中的可接受性和成本效益；(2)确定相关指标在前瞻性识别对二级治疗选择产生抵抗的抑郁症患者中的有效性；(3)检查这些指标在识别对治疗没有持续反应的患者中的应用。我们将检验具体的假设：(1)QEEG评估将是可接受的，并在有效治疗试验中提供具有成本效益的指导；(2)在2级治疗的前两周，前额叶皮质的变化可以预测2级患者对特定转换或增强策略的急性治疗反应；(3)治疗两周后前额叶值变化可预测持续治疗反应。将招募72名抑郁症患者，当他们在两个STAR*D站点中的任何一个进入协议的第2级治疗时，分别在加州大学洛杉矶分校神经精神研究所和哈佛大学马萨诸塞州总医院各36名。QEEG数据将在二级开始时和另外两周后记录。治疗临床医生和受试者将不了解生理数据，结果将使用STAR*D方案中不可或缺的仪器进行评估。受试者将在完成第2级后的3个月和6个月进行随访，以评估反应是否持续。比例检验和t检验将用于评估可接受性和成本效益。急性反应的预测将用卡方和线性回归模型进行检验。对两个地点的数据进行独立检查将用于评估一致性生物标志物方法的普遍性。我们的生物标志物与持续反应的关系将通过卡方分析进行检验。二级分析将使用一般线性模型和生长混合模型来检查早期一致性变化与患者和疾病因素以及功能结果的关系。

DESCRIPTION (provided by applicant): This is a revision of our multi-site collaborative Ancillary Study to the STAR*D Project, in which we propose to study biomarkers that may help guide treatment by prospectively identifying patients with treatment resistant depression (TRD). Pilot data from both randomized clinical trials and naturalistic treatment show that a quantitative electroencephalographic (QEEG) measure, cordance, is associated with response and nonresponse to pharmacotherapy; changes in prefrontal activity early in treatment are predictive of later response. Preliminary data suggest that a biomarker model using the cordance indicator can identify (a) patients who will be resistant to treatment prescribed in Level 2 of the STAR*D protocol, and (b) patients who will have an initial but non-sustained, "placebo-like" response. Such prospective identification would allow physicians to undertake more sophisticated regimens earlier and attain improved clinical outcome. The revisions in this proposal include expansion of the rationale for using the cordance biomarker, additional detail about the STAR*D protocol, additional pilot data, and subject flow projections that have been refined to reflect recent STAR*D enrollment figures. The three specific aims of this project are: (1) to evaluate the use of neurophysiologic biomarkers in an effectiveness treatment trial setting for acceptability and cost effectiveness; (2) to ascertain the validity of cordance indicators in prospectively identifying depressed patients who will be resistant to their Level 2 treatment choices; and (3) to examine the use of these indicators in identifying patients who will not have a sustained response to treatment. We will test specific hypotheses: (1) assessment with QEEG will be acceptable and offer cost effective guidance in an effectiveness treatment trial; (2) acute treatment response in Level 2 to specific switching or augmentation strategies will be predicted by changes in prefrontal cordance in the first two weeks of Level 2 treatment; and (3) sustained treatment response will be predicted by changes in prefrontal values after two weeks of treatment. 72 subjects with depression will be recruited when they enter treatment in Level 2 of the protocol at either of two STAR*D sites, 36 each at UCLA's Neuropsychiatric Institute and Harvard's Massachusetts General Hospital. QEEG data will be recorded at the start of Level 2 and after two additional weeks. Treating clinicians and subjects will be blinded to physiologic data, and outcomes will be assessed using the instruments integral to the STAR*D protocol. Subjects will be followed-up at 3 and 6 months after completing Level 2 to assess whether responses are sustained. The test of proportion and t-tests will be used to evaluate acceptability and cost effectiveness. Prediction of acute response will be tested with chi square and linear regression models. Independent examination of the data at the two sites will be used to assess the generalizability of the cordance biomarker method. The relationship of our biomarkers to sustained response will be tested by chi square analyses. Secondary analyses will use general linear models and growth mixture modeling to examine how early cordance changes relate to patient and illness factors and to functional outcomes.