Meta-analysis of Clinical Efficacy of Commonly Used Therapeutic Drugs for Depression

Youran Huang

doi:10.54254/2753-8818/2025.AU27804

Theoretical and Natural ScienceOpen access

Meta-analysis of Clinical Efficacy of Commonly Used Therapeutic Drugs for Depression

Research Article

Open Access

Meta-analysis of Clinical Efficacy of Commonly Used Therapeutic Drugs for Depression

Youran Huang ^1*

¹ Suzhou Dulwich International High School

^*Corresponding author: 15821220450@163.com

Published on 14 October 2025

TNS Vol.141

ISSN (Print): 2753-8826

ISSN (Online): 2753-8818

ISBN (Print): 978-1-80590-395-6

ISBN (Online): 978-1-80590-396-3

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Abstract

The incidence of depression has been on a continuous rise, which emerges as a major mental illness of concern in the global public health domain. As a primary intervention for moderate to severe depression, pharmacological treatment holds significant importance. Currently, commonly used clinical antidepressants include SSRIs, SNRIs and NaSSAs. However, notable differences exist among these drugs in terms of efficacy, safety, onset time, and patient compliance. How to scientifically select and optimize treatment regimens has thus become a key challenge in clinical practice. In recent years, evidence-based medical approaches like meta-analyses have been widely applied. Network meta-analysis enables indirect comparisons of different antidepressants by integrating data from multiple randomized controlled trials, which provides more comprehensive evidence for clinical medication choices. This article provides a review of depression’s pathological mechanisms, which include neural plasticity impairment, neurotrophic factor deficiency, the monoamine hypothalamic-pituitary-adrenal (HPA) axis axis dysfunction, and the monoamine neurotransmitter hypothesis. It also examines the efficacy, safety, and related research progress of three main classes of antidepressants such as SSRIs, SNRIs, and NaSSAs, to provide references for clinical medication selection.

Keywords:

depression, SSRIs, SNRIs, meta-analysis

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References

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References

[1]. Maier, A., Riedel-Heller, S.G., Pabst, A. and Luppa, M. (2021) Risk factors and protective factors of depression in older people 65+. A systematic review. PLoS One, 16(5), e0251326.

[2]. Monroe, S.M. and Harkness, K.L. (2022) Major Depression and Its Recurrences: Life Course Matters. Annu Rev Clin Psychol, 18, 329-357.

[4]. Beurel, É., Toups, M. and Nemeroff, C.B. (2020) The Bidirectional Relationship of Depression and Inflammation: Double Trouble. Neuron, 107(2), 234-256.

[5]. Han, Y., Gu, S., Li, Y., Qian, X., Wang, F. and Huang, J.H. (2023) Neuroendocrine pathogenesis of perimenopausal depression. Front Psychiatry, 14, 1162501.

[6]. Oyola, M.G. and Handa, R.J. (2017) Hypothalamic-pituitary-adrenal and hypothalamic-pituitary-gonadal axes: sex differences in regulation of stress responsivity. Stress, 20(5), 476-494.

[8]. Montgomery, S., Hansen, T. and Kasper, S. (2011) Efficacy of escitalopram compared to citalopram: a meta-analysis. Int J Neuropsychopharmacol, 14(2), 261-268.

[12]. Hetrick, S.E.(2021) New generation antidepressants for depression in children and adolescents: a network meta-analysis. Cochrane Database Syst Rev. 5(5): p. Cd013674.

Cite this article

Huang,Y. (2025). Meta-analysis of Clinical Efficacy of Commonly Used Therapeutic Drugs for Depression. Theoretical and Natural Science,141,46-50.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICBioMed 2025 Symposium: AI for Healthcare: Advanced Medical Data Analytics and Smart Rehabilitation

ISBN: 978-1-80590-395-6(Print) / 978-1-80590-396-3(Online)

Editor: Alan Wang

Conference website: https://2025.icbiomed.org/auckland.html

Conference date: 17 October 2025

Series: Theoretical and Natural Science

Volume number: Vol.141

ISSN: 2753-8818(Print) / 2753-8826(Online)

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