Abstract：
OBJECTIVE: Identifying biomarkers that predict treatment response in early psychosis (EP) is a priority for psychiatry research. Previous work suggests that resting-state connectivity biomarkers may have promise as predictive measures, although prior results vary considerably in direction and magnitude. Here, we evaluated the relationship between intrinsic functional connectivity of the attention, default mode, and salience resting-state networks and 12-month clinical improvement in EP.
METHODS: Fifty-eight individuals with EP (less than 2 years from illness onset, 35 males, average age 20 years) had baseline and follow-up clinical data and were included in the final sample. Of these, 30 EPs showed greater than 20% improvement in Brief Psychiatric Rating Scale (BPRS) total score at follow-up and were classified as \"Improvers.\"
RESULTS: The overall logistic regression predicting Improver status was significant (χ2 = 23.66, Nagelkerke\'s R2 = 0.45, P < .001, with 85% concordance). Significant individual predictors of Improver status included higher default mode within-network connectivity, higher attention-default mode between-network connectivity, and higher attention-salience between-network connectivity. Including baseline BPRS as a predictor increased model significance and concordance to 92%, and the model was not significantly influenced by the dose of antipsychotic medication (chlorpromazine equivalents). Linear regression models predicting percent change in BPRS were also significant.
CONCLUSIONS: Overall, these results suggest that resting-state functional magnetic resonance imaging connectivity may serve as a useful biomarker of clinical outcomes in recent-onset psychosis.
METHODS: Fifty-eight individuals with EP (less than 2 years from illness onset, 35 males, average age 20 years) had baseline and follow-up clinical data and were included in the final sample. Of these, 30 EPs showed greater than 20% improvement in Brief Psychiatric Rating Scale (BPRS) total score at follow-up and were classified as \"Improvers.\"
RESULTS: The overall logistic regression predicting Improver status was significant (χ2 = 23.66, Nagelkerke\'s R2 = 0.45, P < .001, with 85% concordance). Significant individual predictors of Improver status included higher default mode within-network connectivity, higher attention-default mode between-network connectivity, and higher attention-salience between-network connectivity. Including baseline BPRS as a predictor increased model significance and concordance to 92%, and the model was not significantly influenced by the dose of antipsychotic medication (chlorpromazine equivalents). Linear regression models predicting percent change in BPRS were also significant.
CONCLUSIONS: Overall, these results suggest that resting-state functional magnetic resonance imaging connectivity may serve as a useful biomarker of clinical outcomes in recent-onset psychosis.
摘要：
目的：确定预测早期精神病（EP）治疗反应的生物标志物是精神病学研究的重点。以前的工作表明，静息状态连通性生物标志物可能有希望作为预测措施，尽管先前的结果在方向和幅度上差异很大。这里,我们评估了注意力的内在功能连通性之间的关系，默认模式,和显着性静息状态网络以及EP的12个月临床改善。
方法：58例EP患者（发病后不到2年，35名男性，平均年龄20岁)有基线和随访临床数据，并纳入最终样本。其中,30例EP在随访时显示简短精神病学评定量表（BPRS）总分改善超过20％，并被归类为“改善者”。\"
结果：预测改善者状态的总体逻辑回归是显着的（χ2=23.66，Nagelkerke的R2=0.45，P<.001，一致性为85％）。改善者状态的重要预测因素包括较高的默认网络内模式，更高的注意力-默认模式之间的网络连接，和更高的注意力-显著性之间的网络连接。包括基线BPRS作为预测因子，将模型显著性和一致性提高到92%，抗精神病药物（氯丙嗪当量）的剂量对模型没有显着影响。预测BPRS变化百分比的线性回归模型也很重要。
结论：总体而言，这些结果提示,静息态功能磁共振成像连接可能作为近期发病精神病临床结局的有用生物标志物.
方法：58例EP患者（发病后不到2年，35名男性，平均年龄20岁)有基线和随访临床数据，并纳入最终样本。其中,30例EP在随访时显示简短精神病学评定量表（BPRS）总分改善超过20％，并被归类为“改善者”。\"
结果：预测改善者状态的总体逻辑回归是显着的（χ2=23.66，Nagelkerke的R2=0.45，P<.001，一致性为85％）。改善者状态的重要预测因素包括较高的默认网络内模式，更高的注意力-默认模式之间的网络连接，和更高的注意力-显著性之间的网络连接。包括基线BPRS作为预测因子，将模型显著性和一致性提高到92%，抗精神病药物（氯丙嗪当量）的剂量对模型没有显着影响。预测BPRS变化百分比的线性回归模型也很重要。
结论：总体而言，这些结果提示,静息态功能磁共振成像连接可能作为近期发病精神病临床结局的有用生物标志物.
