Escitalopram

About: Escitalopram is a research topic. Over the lifetime, 2385 publications have been published within this topic receiving 58123 citations. The topic is also known as: LU-26-054-0 & S(+)-citalopram.

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6 and CYP2C19 Genotypes and Dosing of Selective Serotonin Reuptake Inhibitors

Abstract: Selective serotonin reuptake inhibitors (SSRIs) are primary treatment options for major depressive and anxiety disorders. CYP2D6 and CYP2C19 polymorphisms can influence the metabolism of SSRIs, thereby affecting drug efficacy and safety. We summarize evidence from the published literature supporting these associations and provide dosing recommendations for fluvoxamine, paroxetine, citalopram, escitalopram, and sertraline based on CYP2D6 and/or CYP2C19 genotype (updates at www.pharmgkb.org).

Commentary concerning treatment of depression in patients with heart failure according to 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice.

Abstract: See the editorial comment for this article ‘Treating depression in patients with heart failure: what is (not) recommended?’, by Christoph Herrmann-Lingen, https://doi.org/10.1093/eurjpc/zwac092. We read with interest ESC guidelines on cardiovascular disease prevention in clinical practice including a new recommendation for not using SSRI, SNRI, and TCA (Class III, Level B).1 The guideline refers to recent metanalysis2 including eight studies, among which there were two randomized controlled trials (RCTs)3,4 and six observational studies. The two analyzed RCTs3,4 have shown safety of sertraline (although this study was not designed to evaluate mortality) and escitalopram, but no benefit over placebo was observed. The metanalytic outcome provides evidence that the use of antidepressants in patients with heart failure (HF) is associated with an increased risk of all-cause death, regardless of whether they had clinical depression or the type of antidepressants they used.3 Such recommendation should be treated with caution as the evidence from randomized studies is limited and the clinical consequences of untreated depression in patients with HF must be taken into consideration. Major depression disorder (MDD) is a chronic and recurrent condition associated with substantial comorbidity of substance use, metabolic disorders, and cognitive impairment which all contribute to the negative prognosis in HF. The pathophysiology of MDD includes dysregulation in hypothalamic–pituitary–adrenal axis, autonomous system overdrive, and low-grade systemic inflammation. Depression appears in 20–30% of HF cases and results in increased mortality and morbidity.5 There is a need for head-to-head randomized studies investigating both, the change in depressive symptom severity and the use of antidepressant. One study in the metanalysis6 was based on the prescription of antidepressants in a National Danish Cohort and did not include data on the clinical diagnosis and the severity of depressive symptoms which is a methodological consideration. Measuring of the severity of depression is necessary to answer if antidepressants are harmful because it is possible that ineffectively treated depression increases mortality and not the antidepressants used. In another study from this metanalysis,7 the correlation with higher mortality risk was observed only in case of fluoxetine, but not with other antidepressants and fluoxetine has specific metabolism and can cause more interactions than other SSRIs. Moreover, 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic HF guideline8 state that adequate conventional treatment of depression should be offered and that there is still no consensus on the best therapy for patients with HF. If it does not recommend pharmacological treatment it can lead to diminishing the significance of this comorbidity in clinical practice. Why bother with diagnosis if the treatment is harmful? The guideline should be placed in context of treatment adherence and rehabilitation of patients with HF.

Toward a Neuroimaging Treatment Selection Biomarker for Major Depressive Disorder

Abstract: Importance Currently, fewer than 40% of patients treated for major depressive disorder achieve remission with initial treatment. Identification of a biological marker that might improve these odds could have significant health and economic impact. Objective To identify a candidate neuroimaging “treatment-specific biomarker” that predicts differential outcome to either medication or psychotherapy. Design Brain glucose metabolism was measured with positron emission tomography prior to treatment randomization to either escitalopram oxalate or cognitive behavior therapy for 12 weeks. Patients who did not remit on completion of their phase 1 treatment were offered enrollment in phase 2 comprising an additional 12 weeks of treatment with combination escitalopram and cognitive behavior therapy. Setting Mood and anxiety disorders research program at an academic medical center. Participants Men and women aged 18 to 60 years with currently untreated major depressive disorder. Intervention Randomized assignment to 12 weeks of treatment with either escitalopram oxalate (10-20 mg/d) or 16 sessions of manual-based cognitive behavior therapy. Main Outcome and Measure Remission, defined as a 17-item Hamilton Depression Rating Scale score of 7 or less at both weeks 10 and 12, as assessed by raters blinded to treatment. Results Positive and negative predictors of remission were identified with a 2-way analysis of variance treatment (escitalopram or cognitive behavior therapy) × outcome (remission or nonresponse) interaction. Of 65 protocol completers, 38 patients with clear outcomes and usable positron emission tomography scans were included in the primary analysis: 12 remitters to cognitive behavior therapy, 11 remitters to escitalopram, 9 nonresponders to cognitive behavior therapy, and 6 nonresponders to escitalopram. Six limbic and cortical regions were identified, with the right anterior insula showing the most robust discriminant properties across groups (effect size = 1.43). Insula hypometabolism (relative to whole-brain mean) was associated with remission to cognitive behavior therapy and poor response to escitalopram, while insula hypermetabolism was associated with remission to escitalopram and poor response to cognitive behavior therapy. Conclusions and Relevance If verified with prospective testing, the insula metabolism-based treatment-specific biomarker defined in this study provides the first objective marker, to our knowledge, to guide initial treatment selection for depression. Trial Registration Registered at clinicaltrials.gov (NCT00367341)