An Empirical Comparison of Meta- and Mega-Analysis With Data From the ENIGMA Obsessive-Compulsive Disorder Working Group.
Journal: Frontiers in neuroinformatics
Volume: 12
Issue:
Year of Publication:
Affiliated Institutions:
Department of Psychiatry, Amsterdam University Medical Centers (UMC), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands.
Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia.
Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain.
Department of Psychiatry, Faculty of Medicine, The Centre for Addiction and Mental Health, The Margaret and Wallace McCain Centre for Child, Youth and Family Mental Health, Campbell Family Mental Health Research Institute, University of Toronto, Toronto, ON, Canada.
Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States.
Mathison Centre for Mental Health Research and Education, Cumming School of Medicine, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
Departamento de Psiquiatria, Faculdade de Medicina, Instituto de Psiquiatria, Universidade de São Paulo, São Paulo, Brazil.
Division of Neuroscience, Psychiatry and Clinical Psychobiology, Scientific Institute Ospedale San Raffaele, Milan, Italy.
Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.
Obsessive-Compulsive Disorder (OCD) Clinic Department of Psychiatry National Institute of Mental Health and Neurosciences, Bangalore, India.
Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland.
Magnetic Resonance Image Core Facility, IDIBAPS (Institut d'Investigacions Biomèdiques August Pi i Sunyer), Barcelona, Spain.
Centro de Investigación Biomèdica en Red de Salud Mental (CIBERSAM), Barcelona, Spain.
Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Institute of Human Behavioral Medicine, SNU-MRC, Seoul, South Korea.
Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy.
Department of Psychiatry, Amsterdam Neuroscience, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.
Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States.
Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States.
MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa.
Imaging Genetics Center, Keck School of Medicine of the University of Southern California, Mark and Mary Stevens Neuroimaging and Informatics Institute, Marina del Rey, CA, United States.
Shanghai Mental Health Center Shanghai Jiao Tong University School of Medicine, Shanghai, China.
De Bascule, Academic Center for Child and Adolescent Psychiatry, Amsterdam, Netherlands.
Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, South Korea.
Department of Psychiatry, Oxford University, Oxford, United Kingdom.
Department of Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea.
SU/UCT MRC Unit on Anxiety and Stress Disorders, Department of Psychiatry, University of Stellenbosch, Stellenbosch, South Africa.
Columbia University Medical College, Columbia University, New York, NY, United States.
Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden.
Mood Disorders Clinic, St. Joseph's HealthCare, Hamilton, ON, Canada.
Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Center for Mathematics, Computing and Cognition, Universidade Federal do ABC, Santo Andre, Brazil.
Anxiety Treatment and Research Center, St. Joseph's HealthCare, Hamilton, ON, Canada.
Yale University School of Medicine, New Haven, CT, United States.
Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Abstract summary
Brain imaging communities focusing on different diseases have increasingly started to collaborate and to pool data to perform well-powered meta- and mega-analyses. Some methodologists claim that a one-stage individual-participant data (IPD) mega-analysis can be superior to a two-stage aggregated data meta-analysis, since more detailed computations can be performed in a mega-analysis. Before definitive conclusions regarding the performance of either method can be drawn, it is necessary to critically evaluate the methodology of, and results obtained by, meta- and mega-analyses. Here, we compare the inverse variance weighted random-effect meta-analysis model with a multiple linear regression mega-analysis model, as well as with a linear mixed-effects random-intercept mega-analysis model, using data from 38 cohorts including 3,665 participants of the ENIGMA-OCD consortium. We assessed the effect sizes and standard errors, and the fit of the models, to evaluate the performance of the different methods. The mega-analytical models showed lower standard errors and narrower confidence intervals than the meta-analysis. Similar standard errors and confidence intervals were found for the linear regression and linear mixed-effects random-intercept models. Moreover, the linear mixed-effects random-intercept models showed better fit indices compared to linear regression mega-analytical models. Our findings indicate that results obtained by meta- and mega-analysis differ, in favor of the latter. In multi-center studies with a moderate amount of variation between cohorts, a linear mixed-effects random-intercept mega-analytical framework appears to be the better approach to investigate structural neuroimaging data.
Authors & Co-authors:
Boedhoe Premika S W PSW
Heymans Martijn W MW
Schmaal Lianne L
Abe Yoshinari Y
Alonso Pino P
Ameis Stephanie H SH
Anticevic Alan A
Arnold Paul D PD
Batistuzzo Marcelo C MC
Benedetti Francesco F
Beucke Jan C JC
Bollettini Irene I
Bose Anushree A
Brem Silvia S
Calvo Anna A
Calvo Rosa R
Cheng Yuqi Y
Cho Kang Ik K KIK
Ciullo Valentina V
Dallaspezia Sara S
Denys Damiaan D
Feusner Jamie D JD
Fitzgerald Kate D KD
Fouche Jean-Paul JP
Fridgeirsson Egill A EA
Gruner Patricia P
Hanna Gregory L GL
Hibar Derrek P DP
Hoexter Marcelo Q MQ
Hu Hao H
Huyser Chaim C
Jahanshad Neda N
James Anthony A
Kathmann Norbert N
Kaufmann Christian C
Koch Kathrin K
Kwon Jun Soo JS
Lazaro Luisa L
Lochner Christine C
Marsh Rachel R
Martínez-Zalacaín Ignacio I
Mataix-Cols David D
Menchón José M JM
Minuzzi Luciano L
Morer Astrid A
Nakamae Takashi T
Nakao Tomohiro T
Narayanaswamy Janardhanan C JC
Nishida Seiji S
Nurmi Erika L EL
O'Neill Joseph J
Piacentini John J
Piras Fabrizio F
Piras Federica F
Reddy Y C Janardhan YCJ
Reess Tim J TJ
Sakai Yuki Y
Sato Joao R JR
Simpson H Blair HB
Soreni Noam N
Soriano-Mas Carles C
Spalletta Gianfranco G
Stevens Michael C MC
Szeszko Philip R PR
Tolin David F DF
van Wingen Guido A GA
Venkatasubramanian Ganesan G
Walitza Susanne S
Wang Zhen Z
Yun Je-Yeon JY
Thompson Paul M PM
Stein Dan J DJ
van den Heuvel Odile A OA
Twisk Jos W R JWR
Study Outcome
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