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Baseline cognitive functioning can predict the trajectory of acute treatment in first-episode major depressive disorder

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European Archives of Psychiatry and Clinical Neuroscience Aims and scope Submit manuscript

Abstract

Objective

This study aims to investigate the role of cognitive function in the efficacy prediction of selective serotonin reuptake inhibitors (SSRIs) for depression patients and to further the understanding of the relationship between baseline cognitive function and depression trajectory.

Methods

This was part of a multicenter study for major depressive disorder. The study included 172 first-episode depression patients and 93 recurrent depression patients who had their cognitive function assessed at baseline and followed up for 8 weeks of SSRI treatment.

Results

After constructing a 2-level hierarchical linear model with depression change- and cognitive function-level variables, the processing speed at baseline was the best predictor for the improvement of depression at each follow-up in first-episode patients (G11 = 0.03, P = 0.042). The treatment prediction model slope varied across patients depending on the processing speed scores at baseline. With the receiver operating characteristic curve, the combination of sociodemographic characteristics, sedative hypnotics, baseline 17-item Hamilton Rating Scale for Depression (HAMD17), and cognitive function showed the highest predictive power in major depressive disorder remission, resulting in a classification accuracy of 71.5%, a sensitivity of 82.5%, and a specificity of 55.1% (AUC = 0.713; P < 0.001).

Conclusion

Baseline cognitive function could help clinicians to better understand the trajectory of first-episode depression patients during acute treatment with SSRIs.

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Acknowledgements

We appreciate the support from the National Key Basic Research Program(2013CB531305); Shanxi Provincial Department of Education University Science and technology innovation plan project (202010203); Shanxi Provincial Science and technology innovation team of multidisciplinary diagnosis and treatment of cognitive impairment (201705D131027).

Funding

National Basic Research Program of China (973 Program), 2013CB531305, Xin Yu, Shanxi Science and Technology Department, 202010203, Sha Liu, 201705D131027, Sha Liu.

Author information

Author notes

  1. Sha Liu and Yujie Tong have contributed equally to this work.

Authors and Affiliations

  1. Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, 030001, China

    Sha Liu, Yujie Tong, Xiao Wang & Yong Xu

  2. Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, 030001, China

    Sha Liu, Yujie Tong & Xiao Wang

  3. Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China

    Xin Yu

  4. Shanxi Provincial Key Laboratory of Brain Science and Neuropsychiatric Diseases, Shanxi Medical University, Taiyuan, 030001, China

    Yong Xu

  5. Department of Mental Health, Shanxi Medical University, Taiyuan, 030001, China

    Yong Xu

Authors
  1. Sha Liu
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  2. Yujie Tong
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  3. Xiao Wang
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  4. Xin Yu
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Contributions

YX and XY conceived this study; SL made the investigation and data collection; YJT drafted the manuscript; SL, YJT, and XW made the statistical analysis. All authors contributed to drafting and revising the manuscript and approved its final version.

Corresponding authors

Correspondence to Xin Yu or Yong Xu.

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Conflict of interest

The authors declare that they do not have any competing interests.

Ethical approval

The study has been approved by the appropriate ethics committee and has been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. All of the participants provided informed consent prior to their inclusion in the study.

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Liu, S., Tong, Y., Wang, X. et al. Baseline cognitive functioning can predict the trajectory of acute treatment in first-episode major depressive disorder. Eur Arch Psychiatry Clin Neurosci 273, 1129–1137 (2023). https://doi.org/10.1007/s00406-022-01475-9

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  • DOI: https://doi.org/10.1007/s00406-022-01475-9

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