Cargando…
Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study
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 cl...
Autores principales: | , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8556377/ https://www.ncbi.nlm.nih.gov/pubmed/34716400 http://dx.doi.org/10.1038/s41598-021-99534-z |
_version_ | 1784592163527458816 |
---|---|
author | Cao, Bo Liu, Yang S. Selvitella, Alessandro Librenza-Garcia, Diego Passos, Ives Cavalcante Sawalha, Jeffrey Ballester, Pedro Chen, Jianshan Dong, Shimiao Wang, Fei Kapczinski, Flavio Dursun, Serdar M. Li, Xin-Min Greiner, Russell Greenshaw, Andrew |
author_facet | Cao, Bo Liu, Yang S. Selvitella, Alessandro Librenza-Garcia, Diego Passos, Ives Cavalcante Sawalha, Jeffrey Ballester, Pedro Chen, Jianshan Dong, Shimiao Wang, Fei Kapczinski, Flavio Dursun, Serdar M. Li, Xin-Min Greiner, Russell Greenshaw, Andrew |
author_sort | Cao, Bo |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8556377 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-85563772021-11-03 Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study Cao, Bo Liu, Yang S. Selvitella, Alessandro Librenza-Garcia, Diego Passos, Ives Cavalcante Sawalha, Jeffrey Ballester, Pedro Chen, Jianshan Dong, Shimiao Wang, Fei Kapczinski, Flavio Dursun, Serdar M. Li, Xin-Min Greiner, Russell Greenshaw, Andrew Sci Rep Article 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. Nature Publishing Group UK 2021-10-29 /pmc/articles/PMC8556377/ /pubmed/34716400 http://dx.doi.org/10.1038/s41598-021-99534-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Cao, Bo Liu, Yang S. Selvitella, Alessandro Librenza-Garcia, Diego Passos, Ives Cavalcante Sawalha, Jeffrey Ballester, Pedro Chen, Jianshan Dong, Shimiao Wang, Fei Kapczinski, Flavio Dursun, Serdar M. Li, Xin-Min Greiner, Russell Greenshaw, Andrew Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study |
title | Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study |
title_full | Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study |
title_fullStr | Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study |
title_full_unstemmed | Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study |
title_short | Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study |
title_sort | differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8556377/ https://www.ncbi.nlm.nih.gov/pubmed/34716400 http://dx.doi.org/10.1038/s41598-021-99534-z |
work_keys_str_mv | AT caobo differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT liuyangs differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT selvitellaalessandro differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT librenzagarciadiego differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT passosivescavalcante differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT sawalhajeffrey differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT ballesterpedro differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT chenjianshan differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT dongshimiao differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT wangfei differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT kapczinskiflavio differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT dursunserdarm differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT lixinmin differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT greinerrussell differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy AT greenshawandrew differentialpowerofplaceboacrossmajorpsychiatricdisordersapreliminarymetaanalysisandmachinelearningstudy |