Dawson Erica L, Caveney Angela F, Meyers Kortni K, Weisenbach Sara L, Giordani Bruno, Avery Erich T, Schallmo Michael-Paul, Bahadori Armita, Bieliauskas Linas A, Mordhorst Matthew, Marcus Sheila M, Kerber Kevin, Zubieta Jon-Kar, Langenecker Scott A
Department of Psychiatry, University of Michigan Medical Center, Ann Arbor, Michigan, USA.
Department of Psychiatry, The University of Illinois at Chicago, 1601 W Taylor Ave, Chicago, 60612.
Prim Care Companion CNS Disord. 2017 Feb 9;19(1). doi: 10.4088/PCC.16m01949.
Existing cognitive and clinical predictors of treatment response to date are not of sufficient strength to meaningfully impact treatment decision making and are not readily employed in clinical settings. This study investigated whether clinical and cognitive markers used in a tertiary care clinic could predict response to usual treatment over a period of 4 to 6 months in a sample of 75 depressed adults.
Patients (N = 384) were sequentially tested in 2 half-day clinics as part of a quality improvement project at an outpatient tertiary care center between August 2003 and September 2007; additional subjects evaluated in the clinic between 2007 and 2009 were also included. Diagnosis was according to DSM-IV-TR criteria and completed by residents and attending faculty. Test scores obtained at intake visits on a computerized neuropsychological screening battery were the Parametric Go/No-Go task and Facial Emotion Perception Task. Treatment outcome was assessed using 9-item Patient Health Questionnaire (PHQ-9) self-ratings at follow-up (n = 75). Usual treatment included psychotropic medication and psychotherapy. Decline in PHQ-9 scores was predicted on the basis of baseline PHQ-9 score and education, with neuropsychological variables entered in the second step.
PHQ-9 scores declined by 46% at follow-up (56% responders). Using 2-step multiple regression, baseline PHQ-9 score (P ≤ .05) and education (P ≤ .01) were significant step 1 predictors of percent change in PHQ-9 follow-up scores. In step 2 of the model, faster processing speed with interference resolution (go reaction time) independently explained a significant amount of variance over and above variables in step 1 (12% of variance, P < .01), while other cognitive and affective skills did not. This 2-step model accounted for 28% of the variance in treatment change in PHQ-9 scores. Processing speed with interference resolution also accounted for 12% variance in treatment and follow-up attrition.
Use of executive functioning assessments in clinics may help identify individuals with cognitive weaknesses at risk for not responding to standard treatments.
迄今为止,现有的治疗反应认知和临床预测指标的效力不足以对治疗决策产生有意义的影响,且在临床环境中不易应用。本研究调查了在一家三级护理诊所中使用的临床和认知指标能否预测75名成年抑郁症患者在4至6个月期间对常规治疗的反应。
作为2003年8月至2007年9月期间一家门诊三级护理中心质量改进项目的一部分,患者(N = 384)在两个半天的诊所中依次接受测试;2007年至2009年期间在该诊所评估的其他受试者也被纳入。诊断依据DSM-IV-TR标准,由住院医师和主治教员完成。在初次就诊时通过计算机化神经心理筛查电池获得的测试分数为参数化“走/停”任务和面部情绪感知任务。治疗结果在随访时使用9项患者健康问卷(PHQ-9)自评进行评估(n = 75)。常规治疗包括精神药物治疗和心理治疗。基于基线PHQ-9分数和教育程度预测PHQ-9分数的下降,神经心理变量在第二步纳入。
随访时PHQ-9分数下降了46%(56%为反应者)。使用逐步多元回归,基线PHQ-9分数(P≤0.05)和教育程度(P≤0.01)是PHQ-9随访分数变化百分比的显著第一步预测指标。在模型的第二步中,具有干扰解决能力的更快处理速度(执行反应时间)独立解释了超过第一步变量的大量方差(方差的12%,P < 0.01),而其他认知和情感技能则没有。这个两步模型解释了PHQ-9分数治疗变化中方差的28%。具有干扰解决能力的处理速度也解释了治疗和随访损耗中方差的12%。
在诊所中使用执行功能评估可能有助于识别认知功能较弱、有对标准治疗无反应风险的个体。