Evidence map›Paper›PMID 34168454›Full record

ArticleNeuropsychiatric disease and treatment2021

Visualizing Patterns of Medication Switching Among Major Depressive Patients with Various Stability and Difficulty to Treatments.

Yu-Chun Hung, Hsi-Chung Chen, Po-Hsiu Kuo, Mong-Liang Lu, Ming-Chyi Huang, Chun-Hsin Chen, Sabrina Wang, Wei-Chung Mao, Chang-Shiann Wu, Tzu-Hua Wu

Abstract read
In one paragraph

Article in Neuropsychiatric disease and treatment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yu-Chun HungDivision of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, 110, Taiwan.
Hsi-Chung ChenDepartment of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan.ORCID 0000-0003-3191-0093
Po-Hsiu KuoDepartment of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan.ORCID 0000-0003-0365-3587
Mong-Liang LuDepartment of Psychiatry, Wan Fang Hospital & School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.ORCID 0000-0003-3184-6554
Ming-Chyi HuangDepartment of Psychiatry, Taipei City Hospital, Songde Branch, Taipei, Taiwan.
Chun-Hsin ChenDepartment of Psychiatry, Wan Fang Hospital & School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
Sabrina WangInstitute of Anatomy and Cell Biology, School of Medicine, National Yang-Ming University, Taipei, Taiwan.
Wei-Chung MaoDepartment of Psychiatry, Cheng-Hsin General Hospital, Taipei, Taiwan.
Chang-Shiann WuDepartment of Information Management, College of Management, National Formosa University, Huwei Township, Yunlin County, Taiwan.
Tzu-Hua WuDivision of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, 110, Taiwan.ORCID 0000-0002-3631-6248

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionEfforts have been made in assessing efficacy and tolerability to various antidepressants, but understanding personalized chances of stability to medication switching sequence is still inconclusive. This study aimed to identify naturalistic switching patterns of medication in stratifying MDD patients.

methodsMDD patients were stratified based on treatment difficulty evaluated with the "Treatment Resistance to Antidepressants Evaluation Scale for Unipolar Depression" (TRADES). The duration of the time of diagnoses until the final switch to another class of antidepressants was used as prediction of unstable to drug therapy. ROC analysis was used to determine the cutoff values. A continuous temporal events function from the visual analytic tool was employed to perform patterns of switching between distinct pharmacological class such as selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs).

resultsTRADES scores of 4.5 and not-switching times of 12.5 months were used as cutoff values to divide patients into four subgroups: stable/easy-to-treat (SE), unstable/easy-to-treat (UE), stable/difficult-to-treat (SD) and unstable/difficult-to-treat (UD). A total of 80% and 76.9% of patients initially treated with the SSRIs paroxetine or fluoxetine, respectively, were predicted to be stable to drug therapy. Approximately 70%, 44.8% and 41.4% of patients initially treated with the SNRIs fluvoxamine, sertraline and venlafaxine, respectively, were predicted to be UD, and 60% of patients using duloxetine were predicted to be stable to drug therapy. Analysis of the switching phenomenon showed that SSRIs were the first prescribed medications and mostly taken by the stable subgroups, and SNRIs were the preferentially chosen switching alternative. Medication switching patterns in unstable MDD patients are discussed.

conclusionParoxetine, fluoxetine and duloxetine users were mostly stable among MDD patients in Taiwan with various stability and difficulty to treatments. Although responsiveness to specific medication sequence is likely required for clinical application, the results provide a baseline for such studies.

Indexed as

antidepressantsmajor depressive disorderpatterns of medication switchingstabilityvisualization

Identifiers

PMID34168454
PMCPMC8217841

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.