Safety and effectiveness of escitalopram in an 8-week open study in Chinese patients with depression and anxiety

Unraveling the potential of Morinda officinalis oligosaccharides as an adjuvant of escitalopram in depression treatment and exploring the underlying mechanisms

ETHNOPHAMACOLOGICAL RELEVANCE

Morinda officinalis oligosaccharides (MOs) is a mixture of oligosaccharides extracted from the roots of Morinda officinalis (MO). It is approved by Chinese Food and Drug Administration (CFDA) for depression treatment. MOs could improve the antidepressant efficacy of escitalopram in clinic.

AIM OF THE STUDY

We aim to explore the antidepressant activity and potential mechanism of the combination usage of MOs and escitalopram on animal model of depression.

MATERIALS AND METHODS

Depressive animal model was induced by chronic mild stress (CMS). Behavioral tests were conducted to evaluate the antidepressant efficacy of MOs and escitalopram. Serum neurotransmitter levels were detected by High-performance liquid chromatography (HPLC). Quantitative real-time PCR and Western blotting were applied to assay the hippocampus neurotrophic factors' mRNA and protein levels. Peripheral cytokines levels were measured through Enzyme-Linked Immunosorbent Assay (ELISA). Micorglia polization phenotype was assayed by immunofluorescence and flow cytometry.

RESULTS

MOs and escitalopram obviously attenuated depression-like behaviors of CMS mice. Importantly, MOs plus escitalopram exhibited better antidepressant activity on CMS mice than monotherapy. At the same time, MOs combined escitalopram treatment significantly increased hippocampus neurotransmitters and neurotrophic factor levels, stimulated hippocampus neurogenesis and relieved central nervous system (CNS) microglia over-activation of CMS mice. The combination therapy had greater effect on neuroprotection and inflammation attenuation of CMS mice than monotherapy.

CONCLUSION

Our results indicates MOs combined escitalopram might produce antidepressant activity through protecting neuron activity, relieving inflammation and modulating microglia polarization process.

Assessing Pharmacokinetic Correlates of Escitalopram-Related Adverse Drug Reactions

BACKGROUND

To assess the pharmacokinetic correlates of reported adverse drug reactions (ADRs) under antidepressant treatment with escitalopram (ESC) using a large therapeutic drug monitoring database.

METHODS

A large naturalistic sample of inpatients and outpatients prescribed ESC was analyzed. ADRs were classified using the Udvalg for Kliniske Undersogelser side effect rating scale. We compared ESC-treated patients with (n = 35) and without ADRs (n = 273) using ESC plasma concentrations as the primary outcome. We also compared ADR rates in the 2 groups based on 2 cut-off ESC levels reflecting the recommended upper thresholds of the therapeutic reference range of 80 ng/mL, suggested by the consensus therapeutic drug monitoring guidelines, and 40 ng/mL, based on recent meta-analysis data. The effects of age, sex, smoking, daily ESC dose, plasma concentrations, and concentrations corrected for daily dose were included in a binary logistic regression model to predict ADRs.

RESULTS

No differences in clinical, demographic, or pharmacokinetic parameters were observed between patients with and without ADRs ( P > 0.05). Patients with ESC-related ADRs were more frequently diagnosed with psychotic disorders than those without (25% vs. 7.1%, P = 0.004). None of the variables was associated with ADR risk. Overall, ADR rates were not significantly different in patients above versus below thresholds of ESC concentrations (ESC concentrations >40 [n = 59] vs. ≤40 ng/mL [n = 249] and >80 [n = 8] vs. ≤80 ng/mL [n = 300]; P = 0.56 and P = 1.0, respectively).

CONCLUSIONS

No distinct pharmacokinetic patterns underlying ESC-associated ADRs were observed. Further studies with more specific assessments of ADRs in larger cohorts are required to better identify potential underlying patterns.

Development of a model to predict antidepressant treatment response for depression among Veterans

BACKGROUND

Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA).

METHODS

A 2018-2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample.

RESULTS

In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors.

CONCLUSIONS

Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection.

Improvement in quality of life of postmenopausal women with depression with commonly used antidepressants (Escitalopram vs. Desvenlafaxine): A randomized controlled trial in a tertiary care teaching hospital of North India

Introduction:

The postmenopausal symptoms affect the quality of life (QoL) of women. Depression and anxiety too have been associated with diminished QoL. It is known that antidepressants escitalopram and desvenlafaxine are effective in the treatment of depression and anxiety. However, to the best of our knowledge, their comparative effect on the QoL of postmenopausal women with depression and anxiety has not been studied in the Indian setup.

Materials and Methods:

The present study was a randomized, intention to treat, open-label trial undertaken in North India's a tertiary care teaching hospital. Postmenopausal women attending the psychiatry outpatient department and newly diagnosed with depression and anxiety were randomized in two groups to receive Tab. Escitalopram 10–20 mg and Tab. Desvenlafaxine 50–100 mg. Their QoL was assessed using the WHOQOL BREF scale at baseline, 3 weeks and 6 weeks.

Results:

Escitalopram was observed to be statistically better than desvenlafaxine in improving the overall QoL score of the WHOQOL-BREF scale. Individually, escitalopram significantly improved the scores of the physical health domain, psychological and environmental domains except for the social relationship domain. Desvenlafaxine significantly improved scores of all four domains.

Conclusion:

Escitalopram was observed to be significantly better than desvenlafaxine in improving the overall QoL scores. Both the drugs were well tolerated.