Autor: |
Bo Cao, Yang S. Liu, Alessandro Selvitella, Diego Librenza-Garcia, Ives Cavalcante Passos, Jeffrey Sawalha, Pedro Ballester, Jianshan Chen, Shimiao Dong, Fei Wang, Flavio Kapczinski, Serdar M. Dursun, Xin-Min Li, Russell Greiner, Andrew Greenshaw |
Jazyk: |
angličtina |
Rok vydání: |
2021 |
Předmět: |
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Zdroj: |
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021) |
Druh dokumentu: |
article |
ISSN: |
2045-2322 |
DOI: |
10.1038/s41598-021-99534-z |
Popis: |
Abstract The placebo effect across psychiatric disorders is still not well understood. In the present study, we conducted meta-analyses including meta-regression, and machine learning analyses to investigate whether the power of placebo effect depends on the types of psychiatric disorders. We included 108 clinical trials (32,035 participants) investigating pharmacological intervention effects on major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SCZ). We developed measures based on clinical rating scales and Clinical Global Impression scores to compare placebo effects across these disorders. We performed meta-analysis including meta-regression using sample-size weighted bootstrapping techniques, and machine learning analysis to identify the disorder type included in a trial based on the placebo response. Consistently through multiple measures and analyses, we found differential placebo effects across the three disorders, and found lower placebo effect in SCZ compared to mood disorders. The differential placebo effects could also distinguish the condition involved in each trial between SCZ and mood disorders with machine learning. Our study indicates differential placebo effect across MDD, BD, and SCZ, which is important for future neurobiological studies of placebo effects across psychiatric disorders and may lead to potential therapeutic applications of placebo on disorders more responsive to placebo compared to other conditions. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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