Does Thyroid Supplementation Accelerate Tricyclic Antidepressant Response? A Review and Meta-Analysis of the Literature

Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, USA.
American Journal of Psychiatry (Impact Factor: 12.3). 11/2001; 158(10):1617-22. DOI: 10.1176/appi.ajp.158.10.1617
Source: PubMed


The delayed onset of therapeutic response to antidepressants remains a major problem in the treatment of depression. Among the strategies to accelerate response to treatment, the early addition of thyroid hormone to antidepressants has been suggested as a viable method. The authors performed a meta-analysis of the literature on the use of thyroid hormone supplementation to accelerate the treatment of depression to determine whether there is sufficient evidence to support the clinical efficacy of this strategy.
Both a computer-aided search of the National Library of Medicine MEDLINE and an intensive search by hand were conducted to identify all double-blind, placebo-controlled studies assessing the concomitant administration of thyroid hormone and antidepressant to accelerate clinical response in patients with nonrefractory depression.
Six studies were identified. All were conducted with triiodothyronine (T(3)) and a tricyclic antidepressant. Five of the six studies found T(3) to be significantly more effective than placebo in accelerating clinical response. The pooled, weighted effect size index was 0.58, and the average effect was highly significant. Further, the effects of T(3) acceleration were greater as the percentage of women participating in the study increased.
This meta-analysis supports the efficacy of T(3) in accelerating clinical response to tricyclic antidepressants in patients with nonrefractory depression. Furthermore, women may be more likely than men to benefit from this intervention.

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    • "Interestingly, the effects of T3 in patients undergoing AD therapy are particularly remarkable in some subcategories of patients, particularly in women (Altshuler et al., 2001; Agid and Lerer, 2003) and in patients with atypical MDD. Further progress could certainly be achieved in improving AD response by (a) dosing pre-treatment T3 hormones in patients and (b) studying polymorphisms of thyroid function related genes. "
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    ABSTRACT: Depression is one of the most frequent and severe mental disorder. Since the discovery of antidepressant (AD) properties of the imipramine and then after of other tricyclic compounds, several classes of psychotropic drugs have shown be effective in treating major depressive disorder (MDD). However, there is a wide range of variability in response to ADs that might lead to non response or partial response or in increased rate of relapse or recurrence. The mechanisms of response to AD therapy are poorly understood, and few biomarkers are available than can predict response to pharmacotherapy. Here, we will first review markers that can be used to predict response to pharmacotherapy, such as markers of drug metabolism or blood-brain barrier (BBB) function, the activity of specific brain areas or neurotransmitter systems, hormonal dysregulations or plasticity, and related molecular targets. We will describe both clinical and preclinical studies and describe factors that might affect the expression of these markers, including environmental or genetic factors and comorbidities. This information will permit us to suggest practical recommendations and innovative treatment strategies to improve therapeutic outcomes.
    Frontiers in Pharmacology 11/2013; 4:146. DOI:10.3389/fphar.2013.00146 · 3.80 Impact Factor
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    • "The efficacy of both T3 and T4 has been assessed in the treatment of MDD. The majority of studies have assessed the efficacy of T3, and an effect on both the acceleration and the augmentation of mostly tricyclic antidepressants by T3 has been shown (Altshuler et al. 2001; Aronson et al. 1996). A smaller number of studies have examined the use of T4 and found that the augmentation of antidepressant therapy by T4 in supraphysiological doses is effective in roughly 50 % of patients with treatment-resistant depression (Bauer et al. 2005). "
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    ABSTRACT: Thyroid hormones and their interactions with catecholamines play a potentially important role in alterations of mood and cognition. This study aimed to examine the neurobiological effects of catecholamine depletion on thyroid hormones by measuring endocrine and cerebral metabolic function in unmedicated subjects with remitted major depressive disorder (RMDD) and in healthy controls. This was a randomized, placebo-controlled, and double-blind crossover trial that included 15 unmedicated RMDD subjects and 13 healthy control subjects. The participants underwent two 3-day-long sessions at 1-week intervals; each participant was randomly administered oral α-methyl-para-tyrosine in one session (catecholamine depletion) and an identical capsule containing hydrous lactose (sham depletion) in the other session prior to a [(18)F]-fluorodeoxyglucose positron emission tomography scan. Serum concentrations of free T3 (FT3), free T4 (FT4), and TSH were obtained and assessed with respect to their relationship to regional cerebral glucose metabolism. Both serum FT3 (P = 0.002) and FT4 (P = 0.0009) levels were less suppressed after catecholamine depletion compared with placebo treatment in the entire study sample. There was a positive association between both FT3 (P = 0.0005) and FT4 (P = 0.002) and depressive symptoms measured using the Montgomery-Åsberg Depression Rating Scale. The relative elevation in FT3 level was correlated with a decrease in regional glucose metabolism in the right dorsolateral prefrontal cortex (rDLPFC; P < 0.05, corrected). This study provided evidence of an association between a thyroid-catecholamine interaction and mood regulation in the rDLPFC.
    Psychopharmacology 08/2013; 231(2). DOI:10.1007/s00213-013-3250-2 · 3.88 Impact Factor
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    • "However, Papakostas et al. (2009) reviewed five double-blind acceleration studies with T3 and found no statistically significant difference in terms of remission rates or response rates at week 1, week 2, or at endpoint between the SSRI +T3 coinitiation therapy versus SSRI monotherapy in patients with major depression. This observation is in contrast with the significant effect of T3 in accelerating the antidepressant effect of TCAs (Altshuler et al. 2001), and the effect of pindolol in accelerating SSRIs. The median survival time until first response in Portella et al. (2011) meta-analysis was 65% less in the pindolol group (22 days vs. 30 days; P = 0.03). "
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    ABSTRACT: The lack of reliable outcome predictors and the delayed onset of therapeutic response to antidepressants are among the clinical challenges in the treatment of depression. Identifying clinical correlates associated with antidepressant response would reduce symptom severity and morbidity for patients with depression. Twenty-three subjects with major depression were treated with citalopram 20 mg/day in a 6-week open trial and were also simultaneously randomized to either adjunctive triiodothyronine (T3) 25 μg BID (n = 7), pindolol 5 mg BID (n = 8), or placebo (n = 8). Baseline thyroid-stimulating hormone (TSH), FT4, FT3, and TT3 were measured for potential relationships to treatment response across groups. In males only, there was a significant inverse correlation between baseline free T4 and time to response (r = -0.7, P = 0.034). In both males and females across all treatment conditions, as measured by Kaplan-Meier (K-M) maintenance failure time, baseline TSH below the mean (1.5 ng/dL) was associated with a shorter time to response (50% reduction in Montgomery and Asberg Depression Rating Scale [MADRS] score) (χ(2) = 4.53, df = 1, P = 0.03). Patients with baseline TSH above the mean were less likely to reach full remission (MADRS ≤ 7) (χ(2) = 4.38, df = 1, P = 0.03). No significant differences between groups emerged in the mean response time. Baseline thyroid function, as measured by serum free T4 and TSH, may predict a patient's response time to antidepressant treatment with citalopram.
    Brain and Behavior 03/2013; 3(2):89-94. DOI:10.1002/brb3.109 · 2.24 Impact Factor
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