Data analysis strategies for the Accelerating Medicines Partnership® Schizophrenia Program

The Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ) project assesses a large sample of individuals at clinical high-risk for developing psychosis (CHR) and community controls. Subjects are enrolled in 43 sites across 5 continents. The assessments include domains similar to those acquired in previous CHR studies along with novel domains that are collected longitudinally across a period of 2 years. In parallel with the data acquisition, multidisciplinary teams of experts have been working to formulate the data analysis strategy for the AMP SCZ project. Here, we describe the key principles for the data analysis. The primary AMP SCZ analysis aim is to use baseline clinical assessments and multimodal biomarkers to predict clinical endpoints of CHR individuals. These endpoints are defined for the AMP SCZ study as transition to psychosis (i.e., conversion), remission from CHR syndrome, and persistent CHR syndrome (non-conversion/non-remission) obtained at one year and two years after baseline assessment. The secondary aim is to use longitudinal clinical assessments and multimodal biomarkers from all time points to identify clinical trajectories that differentiate subgroups of CHR individuals. The design of the analysis plan is informed by reviewing legacy data and the analytic approaches from similar international CHR studies. In addition, we consider properties of the newly acquired data that are distinct from the available legacy data. Legacy data are used to assist analysis pipeline building, perform benchmark experiments, quantify clinical concepts and to make design decisions meant to overcome the challenges encountered in previous studies. We present the analytic design of the AMP SCZ project, mitigation strategies to address challenges related to the analysis plan, provide rationales for key decisions, and present examples of how the legacy data have been used to support design decisions for the analysis of the multimodal and longitudinal data. Watch Prof. Ofer Pasternak discuss his work and this article: https://vimeo.com/1023394132?share=copy#t=0 .

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Publication Details

Journal
Schizophrenia
Published
2025-04-03
DOI
https://doi.org/10.1038/s41537-025-00561-w
Citations
3
Primary Topic
Health Systems, Economic Evaluations, Quality of Life
Type
article
Field-Weighted Citation Impact
9.39

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article

Data analysis strategies for the Accelerating Medicines Partnership® Schizophrenia Program

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Health Systems, Economic Evaluations, Quality of Life
9.39
article

Data analysis strategies for the Accelerating Medicines Partnership® Schizophrenia Program

Phillip Wolff, Sylvain Bouix, Celso Arango, Alan Anticevic, John M. Kane, Diana O. Perkins, Nora Penzel, Jai L. Shah, Carrie E. Bearden, Sophia Frangou, Jijun Wang, Daniel H. Mathalon, Anastasia Haidar, John Blake Torous, Jun Soo Kwon, Dominic Dwyer, Sinéad Kelly, René S. Kahn, Tashrif Billah, Michael P. Harms, Robert J. Glynn, Márk Vangel, Andrew Potter, Ofer Pasternak, Qingqin S. Li, Beier Yao, Barnaby Nelson, Gahan Pandina, Jean Addington, Cheryl M. Corcoran, Valentina Mantua, William S. Stone, Patrick D. McGorry, Jenna Reinen, Kathryn E. Lewandowski, Paolo Fusar‐Poli, Guillermo Cecchi, Monica E. Calkins, Pablo I. Polosecki, Michael Coleman, Scott W. Woods, Michael Sand, Eduardo Castro, Johanna Seitz‐Holland, Srinivasan Venkataraman, Martha E. Shenton, Daniel H. Wolf, Grace R. Jacobs, Abraham Reichenberg, Joseph Kambeitz, Spero Nicholas, Vijay Anand Mittal, Ameneh Asgari-Targhi, Tyrone D. Cannon, Nikolaos Koutsouleris, Tina Kapur, Kang Ik K. Cho, Hao Zhu, D. Campbell, Agrima Srivastava, K. R. Abhinandan, Saryet Kucukemiroglu
article en
3 citations

Abstract

The Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ) project assesses a large sample of individuals at clinical high-risk for developing psychosis (CHR) and community controls. Subjects are enrolled in 43 sites across 5 continents. The assessments include domains similar to those acquired in previous CHR studies along with novel domains that are collected longitudinally across a period of 2 years. In parallel with the data acquisition, multidisciplinary teams of experts have been working to formulate the data analysis strategy for the AMP SCZ project. Here, we describe the key principles for the data analysis. The primary AMP SCZ analysis aim is to use baseline clinical assessments and multimodal biomarkers to predict clinical endpoints of CHR individuals. These endpoints are defined for the AMP SCZ study as transition to psychosis (i.e., conversion), remission from CHR syndrome, and persistent CHR syndrome (non-conversion/non-remission) obtained at one year and two years after baseline assessment. The secondary aim is to use longitudinal clinical assessments and multimodal biomarkers from all time points to identify clinical trajectories that differentiate subgroups of CHR individuals. The design of the analysis plan is informed by reviewing legacy data and the analytic approaches from similar international CHR studies. In addition, we consider properties of the newly acquired data that are distinct from the available legacy data. Legacy data are used to assist analysis pipeline building, perform benchmark experiments, quantify clinical concepts and to make design decisions meant to overcome the challenges encountered in previous studies. We present the analytic design of the AMP SCZ project, mitigation strategies to address challenges related to the analysis plan, provide rationales for key decisions, and present examples of how the legacy data have been used to support design decisions for the analysis of the multimodal and longitudinal data. Watch Prof. Ofer Pasternak discuss his work and this article: https://vimeo.com/1023394132?share=copy#t=0 .

SchizophreniaVol. 11(1)
Northwestern University (US), University of North Carolina at Chapel Hill (US), Institute of Physics (GB), Brigham and Women's Hospital (US), Northwell Health (US), Beth Israel Deaconess Medical Center (US), United States Food and Drug Administration (US), Feinstein Institute for Medical Research (US), Johnson & Johnson (United States) (US), Center for Drug Evaluation and Research (US), Center for Devices and Radiological Health (US), Harvard University (US), Seoul National University (KR), University of British Columbia (CA), Emory University (US), University of California, Los Angeles (US), The University of Melbourne (AU), University of Calgary (CA), Douglas College (CA), University of California, San Francisco (US), University of Cologne (DE), King's College London (GB), Washington University in St. Louis (US), University of Pavia (IT), McLean Hospital (US), Instituto de Salud Carlos III (ES), Shanghai Mental Health Center (CN), Seoul National University Hospital (KR), Hospital General Universitario Gregorio Marañón (ES), Yale University (US), Otsuka (United States) (US), Massachusetts General Hospital (US), Centro de Investigación Biomédica en Red de Salud Mental (ES), Donald & Barbara Zucker School of Medicine at Hofstra/Northwell (US), Orygen (AU), IBM Research - Thomas J. Watson Research Center (US), King's College School (GB), Otsuka Pharmaceutical (Spain) (ES), San Francisco VA Health Care System (US), Janssen (United States) (US), University Hospital Cologne (DE), Connecticut Mental Health Center (US), Northern California Institute for Research and Education (US), Hotchkiss Brain Institute (CA), McGill University (CA), University of Pennsylvania (US), Ludwig-Maximilians-Universität München (DE), École de Technologie Supérieure (CA), Icahn School of Medicine at Mount Sinai (US)
National Institutes of Health, National Institute of Mental Health
Partnerships for the goals
Openalex Percentile: Top 3%
Health Systems, Economic Evaluations, Quality of Life
9.39
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