Vöhringer Paul A, Barroilhet Sergio A, Palma Bárbara A, Perlis Roy H
Departamento de Psiquiatría y Salud Mental, Hospital Clínico Universidad de Chile, Santiago, Chile.
Facultad Medicina Universidad de Chile, Santiago, Chile.
Acta Psychiatr Scand. 2025 Sep;152(3):228-235. doi: 10.1111/acps.13822. Epub 2025 May 14.
Antidepressants remain among the most widely used class of drugs in treating bipolar disorder, despite their minimal efficacy in randomized clinical trials and concern for association with manic episodes. This study sought to evaluate the outcomes of antidepressant treatment in bipolar depression in a large naturalistic cohort study, STEP-BD, in terms of symptomatic remission as well as emergence of mania, using a propensity score (PS) analysis to reduce indication bias.
Propensity scores were developed to estimate the probability of antidepressant exposure using multivariate logistic regression models; these scores were then used to match antidepressant-exposed and non-exposed individuals. Cox regression models were used to estimate hazard ratios for manic switch and time to remission, adjusted for these scores in the matched population.
Total sample included 2166 individuals, of whom 1085 were exposed to AD and 1081 were unexposed to AD; mean follow-up duration was 182.5 (SD: 44.6) days (median = 126, ICR: 87.4). Cox regression models for manic switch with antidepressant exposure versus non-exposure yielded an unadjusted hazard ratio (HR) of 0.93 (95% CI 0.67-1.14) and PS-adjusted HR of 0.77 (95% CI 0.51-1.08), neither of which was statistically significantly different from 1. Probability of symptomatic remission was also not significantly associated with antidepressant exposure, with unadjusted and PS-adjusted HR of 1.15 (95% CI 0.97-1.37) and 1.02 (95% CI 0.87-1.23), respectively.
With PS adjustment, there was no evidence of increased likelihood of manic switch or achievement of symptomatic remission associated with antidepressant use in bipolar depression. Our results underscore the ongoing need to identify alternative strategies for effective treatment of bipolar depression.
尽管抗抑郁药在随机临床试验中的疗效甚微,且人们担心其与躁狂发作有关联,但它们仍是治疗双相情感障碍最广泛使用的药物类别之一。本研究旨在通过一项大型自然队列研究(STEP - BD),采用倾向评分(PS)分析以减少指征偏倚,来评估双相抑郁患者接受抗抑郁药治疗的症状缓解及躁狂发作情况。
使用多变量逻辑回归模型生成倾向评分,以估计接受抗抑郁药治疗的概率;然后用这些评分匹配接受和未接受抗抑郁药治疗的个体。在匹配人群中,使用Cox回归模型估计躁狂转换的风险比和缓解时间,并根据这些评分进行调整。
总样本包括2166名个体,其中1085名接受了抗抑郁药治疗,1081名未接受抗抑郁药治疗;平均随访时间为182.5(标准差:44.6)天(中位数 = 126,四分位间距:87.4)。抗抑郁药治疗组与未治疗组的躁狂转换Cox回归模型得出未调整的风险比(HR)为0.93(95%置信区间0.67 - 1.14),倾向评分调整后的HR为0.77(95%置信区间0.51 - 1.08),两者均与1无统计学显著差异。症状缓解概率也与抗抑郁药治疗无显著关联,未调整和倾向评分调整后的HR分别为1.15(95%置信区间0.97 - 1.37)和1.02(95%置信区间0.87 - 1.23)。
经过倾向评分调整后,没有证据表明双相抑郁患者使用抗抑郁药会增加躁狂转换的可能性或实现症状缓解。我们的结果强调了持续需要确定有效治疗双相抑郁的替代策略。