Observational Study
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Psychiatr. Nov 19, 2021; 11(11): 1116-1128
Published online Nov 19, 2021. doi: 10.5498/wjp.v11.i11.1116
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
Core Tip

Core Tip: This study evaluated the time-dependent prescription patterns in drug-naive patients experiencing their first major depressive episode with data collected over the first 2 years after disease onset. The K-means clustering analysis was performed, along with the evaluation of four input parameters to generate data-based subgroups. Four feature-based clusters were identified, differentiated by the time-dependent prescription profiles and burden of the disease. 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.