Emory University School of Medicine, Atlanta, GA, United States.
Department of Psychiatry and Health Behavior, Augusta University, Augusta, GA, United States.
Brain Behav Immun. 2023 Nov;114:154-162. doi: 10.1016/j.bbi.2023.08.001. Epub 2023 Aug 20.
Given evidence pointing toward a role for immune dysregulation in the pathogenesis of schizophrenia, anti-inflammatory agents are promising adjunctive treatments that have potential to support a causal relationship for inflammation and psychopathology and lead to novel treatments for individuals. Indeed, previous meta-analyses have demonstrated small-to-medium effect sizes (ES) in favor of various anti-inflammatory agents, though there is significant heterogeneity and challenges in the interpretation of this literature. Identifying predictors, including sociodemographic variables, trial duration, and/or symptoms themselves, of successful anti-inflammatory trials may help identify which patients who might benefit from these compounds. We performed a meta-regression analysis of 63 adjunctive anti-inflammatory trial arms (2232 patients randomized to adjunctive anti-inflammatory agents and 2207 patients randomized to placebo).Potential predictors of effect size estimates for changes in psychopathology scores from baseline to endpoint included geography, trial duration, sample size, age, sex, race, smoking, body mass index, illness duration, age of onset of psychosis, study quality score and psychopathology scores (total and subscale) at baseline. Geography (β = 0.31, p = 0.011), smaller sample size (β = 0.33, p = 0.009), and higher study quality score (β = 0.44, p < 0.001) were significant predictors of larger ES estimates for change in total psychopathology in favor of anti-inflammatory agents. Smaller sample size (β = 0.37, p = 0.034) and higher study quality score (β = 0.55, p = 0.003) were significant predictors of larger ES estimates for change in negative psychopathology in favor of anti-inflammatory agents. Higher study quality score (β = 0.46, p = 0.019) was a significant predictor of larger ES estimates for change in general psychopathology in favor of anti-inflammatory agents. These findings should be interpreted with caution given concerns of publication bias regarding the geographic differences and small study effects. The lack of an association with other demographic variables should be seen as a primary limitation of the literature that needs to be considered in future studies. The association with study quality score suggests that future anti-inflammatory trials must consider demographic variables known to be associated with inflammation (e.g., BMI and smoking) and evidence of increased baseline inflammation should be incorporated in study design. Moreover, evidence of target engagement and endpoints thoughts to be associated with increased inflammation should be considered as well.
鉴于免疫失调在精神分裂症发病机制中的作用的证据，抗炎药物是很有前途的辅助治疗方法，有可能支持炎症与精神病理学之间的因果关系，并为个体带来新的治疗方法。事实上，以前的荟萃分析已经证明了各种抗炎药物的小到中等效应大小（ES），尽管在解释这些文献方面存在很大的异质性和挑战。确定成功的抗炎试验的预测因素，包括社会人口统计学变量、试验持续时间和/或自身症状，可能有助于确定哪些患者可能从这些化合物中受益。我们对 63 个辅助抗炎试验臂（2232 名随机分配至辅助抗炎药物的患者和 2207 名随机分配至安慰剂的患者）进行了荟萃回归分析。从基线到终点时心理病理学评分变化的效应大小估计值的潜在预测因素包括地理位置、试验持续时间、样本量、年龄、性别、种族、吸烟、体重指数、疾病持续时间、精神病发病年龄、研究质量评分以及基线时的心理病理学评分（总分和子量表）。地理位置（β=0.31，p=0.011）、较小的样本量（β=0.33，p=0.009）和较高的研究质量评分（β=0.44，p<0.001）是抗炎药物治疗有利于改善总心理病理学的 ES 估计值较大的显著预测因素。较小的样本量（β=0.37，p=0.034）和较高的研究质量评分（β=0.55，p=0.003）是抗炎药物治疗有利于改善阴性心理病理学的 ES 估计值较大的显著预测因素。较高的研究质量评分（β=0.46，p=0.019）是抗炎药物治疗有利于改善一般心理病理学的 ES 估计值较大的显著预测因素。鉴于地理位置差异和小研究效应的发表偏倚问题，这些发现应谨慎解释。与其他人口统计学变量之间缺乏关联应被视为文献的主要局限性，需要在未来的研究中考虑。与研究质量评分的关联表明，未来的抗炎试验必须考虑已知与炎症相关的人口统计学变量（例如，BMI 和吸烟），并应在研究设计中纳入基线炎症增加的证据。此外，还应考虑与炎症增加相关的目标参与和终点思想的证据。
