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首页> 外文期刊>The journal of clinical psychiatry >Symptom clusters as predictors of late response to antidepressant treatment.
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Symptom clusters as predictors of late response to antidepressant treatment.

机译：症状群是抗抑郁药治疗迟发反应的预测指标。

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OBJECTIVE: While there is some indication from studies in the acute phase of antidepressant treatment that there are differences in the timing of improvement in symptoms, relatively little work has explored the patterns of change for specific symptom clusters and the predictability of these changes to signal eventual response during the acute phase of treatment. This article investigates the use of clusters of symptoms on the 17-item Hamilton Rating Scale for Depression (HAM-D-17) to define the pattern of late response versus nonresponse to antidepressant medication. METHOD: Using principal component analysis, the HAM-D-17 was divided into 4 symptom clusters (mood, sleep/psychic anxiety, appetite, and somatic anxiety/weight). Data for 996 patients with major depressive disorder (DSM-III-R criteria), who participated in a 12-week acute phase study with nefazodone, were subjected to a post hoc analysis of changes in symptom cluster scores. Patients were divided into 3 groups: early responders (< 4 weeks), late responders (4-12 weeks), and nonresponders (> 12 weeks) as defined by < 50% reduction in HAM-D-17 scores from baseline. The late-responder and nonresponder groups were subjected to the principal component analysis. Data were collected from October 1992 to November 1994. RESULTS: There were significant differences in the pattern of symptom change on the mood cluster (weeks 3-4) (p < .0001), the sleep/psychic anxiety cluster (weeks 3-4) (p < .003), and the somatic anxiety/weight cluster (weeks 3-4) (p < .01) for the late responders compared to the nonresponders. Using change scores, a discriminant function analysis correctly assigned 127 of the 182 late responders and 85 of the 133 nonresponders, or 70% of the late responders and 64% of the nonresponders, to their final response groups. CONCLUSION: Monitoring changes in symptom clusters from the HAM-D-17 during this crucial early stage (first 4 weeks) can be used to distinguish late responders (after week 4) from nonresponders. Successful identification of nonresponders based on symptom cluster change in the first 4 weeks would facilitate a shortening of an ineffective treatment trial and allow for necessary changes in treatment strategy, helping physicians more closely follow treatment guidelines.
机译：目的：尽管抗抑郁药治疗的急性期研究表明，症状改善的时间存在差异，但相对较少的工作探索了特定症状群的变化模式以及这些变化的可预测性最终提示在急性期的治疗反应。本文研究了在17个项的汉密尔顿抑郁量表（HAM-D-17）上使用症状簇来定义抗抑郁药物迟发反应与无反应的模式。方法：使用主成分分析法，将HAM-D-17分为4个症状群（情绪，睡眠/精神焦虑，食欲和躯体焦虑/体重）。参加奈法唑酮为期12周的急性期研究的996名重度抑郁症患者（DSM-III-R标准）的数据经过事后分析症状簇评分变化。将患者分为3组：早期应答者（<4周），晚期应答者（4-12周）和无应答者（> 12周），其定义为HAM-D-17得分比基线降低了50％。对后反应者和无反应者组进行主成分分析。从1992年10月至1994年11月收集了数据。结果：在情绪群（第3-4周），睡眠/精神焦虑症（第3-4周）的症状变化模式上存在显着差异。 ）（p <.003），晚期反应者与无反应者相比，躯体焦虑/体重簇（3-4周）（p <.01）。使用变化评分，判别功能分析将182个晚期应答者中的127个和133个非应答者中的85个正确分配了最终应答组，或者将70％的晚期应答者和64％的非应答者正确地分配给了他们的最终应答组。结论：在这个关键的早期阶段（前4周）监测HAM-D-17症状群的变化可用于区分晚期反应者（第4周后）和无反应者。在头4周内根据症状群变化成功识别出无反应者，将有助于缩短无效的治疗试验，并允许必要的治疗策略改变，从而帮助医生更严格地遵循治疗指南。

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