Copyright
©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
Subgrouping time-dependent prescribing patterns of first-onset major depressive episodes by psychotropics dissection
Hsi-Chung Chen, Hui-Hsuan Hsu, Mong-Liang Lu, Ming-Chyi Huang, Chun-Hsin Chen, Tzu-Hua Wu, Wei-Chung Mao, Chuhsing K Hsiao, Po-Hsiu Kuo
Hsi-Chung Chen, Department of Psychiatry & Center of Sleep Disorders, National Taiwan University Hospital, Taipei 100, Taiwan
Hui-Hsuan Hsu, Center of Statistical Consultation and Research, National Taiwan University Hospital, Taipei 100, Taiwan
Mong-Liang Lu, Chun-Hsin Chen, Department of Psychiatry, Wan-Fang Hospital & School of Medicine, College of Medicine, Taipei Medical University, Taipei 100, Taiwan
Ming-Chyi Huang, Department of Psychiatry, Taipei City Hospital, Songde Branch, Taipei 100, Taiwan
Tzu-Hua Wu, Department of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University,Taipei 110, Taiwan
Wei-Chung Mao, Department of Psychiatry, Cheng-Hsin General Hospital, Taipei 100, Taiwan
Chuhsing K Hsiao, Po-Hsiu Kuo, Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 100, Taiwan
Author contributions: Chen HC and Hsu HH drafted the manuscript; Kuo PH, Hsiao CK and Chen HC conceived and designed the study, and critically revised the manuscript; Kuo PH owns primary responsibility for the final content; Lu ML, Huang MC, and Chen CH assisted to refer the patients as participants; Lu ML, Huang MC, Chen CH, Wu TH, and Mao WC gave critical opinions on the study design and the manuscript; all authors have read and approve the final manuscript.
Supported by the Ministry of Science and Technology, Taiwan, No. MOST 107-2314-B-002-219 and No. MOST 108-2314-B-002-110-MY2; the National Taiwan University Hospital, No. UN110-021.
Institutional review board statement: This study was approved by the research ethics committees of National Taiwan University Hospital, Taipei Municipal Wanfang Hospital, and Taipei City Hospital, Songde Branch.
Informed consent statement: All study participants provided informed written consent prior to study enrollment.
Conflict-of-interest statement: The authors declare no competing interests.
Data sharing statement: No additional data are available.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
http://creativecommons.org/Licenses/by-nc/4.0/ Corresponding author: Po-Hsiu Kuo, PhD, Professor, Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Rm 521, No. 17, Xuzhou Road, Taipei 100, Taiwan.
phkuo@ntu.edu.tw
Received: July 8, 2021
Peer-review started: July 8, 2021
First decision: July 28, 2021
Revised: August 5, 2021
Accepted: September 22, 2021
Article in press: September 22, 2021
Published online: November 19, 2021
Processing time: 132 Days and 0.3 Hours
ARTICLE HIGHLIGHTS
Research background
Major depressive disorder (MDD) is a common and challenging mental illness. Even though research on the biological substrates of MDD is increasing, the heterogeneity of MDD substantially compromises the applicability of these study findings. Thus, subgrouping MDD into homogeneous clusters, which could be used to investigate specific neurobiological and pathological mechanisms, is a promising solution.
Research motivation
The heterogeneity in MDD is derived from multiple aspects of the disease. There is inadequate evidence to support the existence of symptom-based subtypes. Thus, we intended to develop a novel approach by clustering patients with similar biologically relevant potentials.
Research objectives
We aimed to develop a novel approach to tackle the heterogeneity in drug-naive patients experiencing their first episode of MDD, using detailed prescription patterns of major psychotropic classes during the early disease course.
Research methods
Psychotropic agents prescribed in the first 24 mo following disease onset were recorded monthly and categorized as antidepressants, augmentation agents, and hypnosedatives. Four parameters were used to summarize the time-dependent prescription patterns for each psychotropic agent. A K-means cluster analysis was used to derive subgroups of participants based on these four parameters of psychotropic agents across 24 mo.
Research results
The patients were empirically classified into 4 clusters according to the K-means clustering analysis that dissected the time-dependent prescription pattern over the first 2 years following the onset of the first episode of MDD. The four identified clusters exhibited distinct patterns in terms of the dosage of psychotropic agents, duration of prescription, and the combinations of psychotropic agents used. Additionally, the four clusters also exhibited differences in severity of clinical indicators.
Research conclusions
Our novel parameters successfully captured the reciprocal interaction between physicians' prescriptions and disease status in a real-world setting. This study presents a novel clustering strategy that can be used to generate prescription-based subtypes.
Research perspectives
Machine learning approaches, such as K-means clustering analyses can be used to optimize the subgrouping information. The biological validity, generalizability, and predictive value of this new clustering approach warrant further investigation.
