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Imputing the Number of Responders from the Mean and Standard Deviation of CGI-Improvement in Clinical Trials Investigating Medications for Autism Spectrum Disorder

Research output: Contribution to journalArticlepeer-review

Spyridon Siafis, Alessandro Rodolico, Oğulcan Çıray, Declan Murphy, Mara Parellada, Celso Arango, Stefan Leucht

Original languageEnglish
Article number908
JournalBrain Sciences
Issue number7
Published9 Jul 2021

Bibliographical note

Funding Information: This project received funding from the Innovative Medicines Initiative 2 joint undertaking under grant agreement No. 777394 for the project AIMS?2-TRIALS. This joint undertaking received support from the European Union?s Horizon 2020 research and innovation program, EFPIA, AUTISM SPEAKS, Autistica, and SFARI. Acknowledgments: We would like to thank the authors that participated in the completion of the main systematic review and meta-analysis: Hui Wu, Marc Krause, Anna Ceraso, Giacomo Deste, Maximilian Huhn, David Fraguas, Antonia San Jos? C?ceres, Dimitris Mavridis, and Tony Charman. We would like to thank the other contributors to the systematic review: Farhad Sokraneh, information specialist of the Cochrane Schizophrenia Group who conducted the first search in electronic databases, Yikang Zhu for the translation of a Chinese study, and Toshi Furukawa for the translation of a Japanese study. We would like to thank the following authors that kindly contributed to the review by providing additional data or clarifications about their studies: Adi Aran, Kaat Alaerts, Nadir Aliyev, Eugene Arnold, Haim Belmaker, Y?h?zkel Ben-Ari, Leventhal Bennet, Stephen Bent, Helena Brentani, Jan Buitelaar, Ana Maria Castejon, Michael Chez, Torsten Danfors, Paulo Fontoura, Robert Grimaldi, Paul Gringras, Alexander H?ge, Randi J. Hagerman, Antonio Hardan, Robert Hendren, Janet Kern, Bruno Leheup, Wenn Liu, Raquel Martinez, James McCracken, Tali Nir, Deborah Pearson, Laura Politte, Jeanette Ramer, Dan Rossignol, Kevin Sanders, Elisa Santocchi, Renato Scifo, Sarah Shea, Lawrence Scahill, Jeremy Veenstra-Vanderweele Paul Wang, David Wilensky, Hidenori Yamasue, and Lingli Zhang. Funding Information: Funding: This project received funding from the Innovative Medicines Initiative 2 joint undertaking under grant agreement No. 777394 for the project AIMS−2-TRIALS. This joint undertaking received support from the European Union’s Horizon 2020 research and innovation program, EFPIA, AUTISM SPEAKS, Autistica, and SFARI. Funding Information: Conflicts of Interest: In the last 3 years, Stefan Leucht has received honoraria as a consultant and advisor and for lectures from LB Pharma, Otsuka, Lundbeck, Boehringer Ingelheim, LTS 760 Lohmann, Janssen, Johnson & Johnson, TEVA, MSD, Sandoz, SanofiAventis, Angelini, Recordati, Sunovion, and Geodon Richter. Celso Arango has been a consultant to or has received honoraria or grants from Acadia, Angelini, Gedeon Richter, Janssen Cilag, Lundbeck, Otsuka, Roche, Sage, Sanofi, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion, and Takeda. The other authors have nothing to disclose. Mara Parellada has received educational honoraria from Otsuka, research grants from FAK and the Fundación Mutua Madrileña (FMM), Instituto de Salud Carlos III (Spanish Ministry of Science, Innovation and Universities), and European ERANET and H2020 calls, and travel grants from Otsuka and Janssen. As a consultant for Exeltis and Servier. Declan G. Murphy has received consulting fees from Roche. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.


  • brainsci-11-00908

    brainsci_11_00908.pdf, 1.36 MB, application/pdf

    Uploaded date:14 Jul 2021

    Version:Final published version

King's Authors


Introduction: Response to treatment, according to Clinical Global Impression-Improvement (CGI-I) scale, is an easily interpretable outcome in clinical trials of autism spectrum disorder (ASD). Yet, the CGI-I rating is sometimes reported as a continuous outcome, and converting it to dichotomous would allow meta-analysis to incorporate more evidence. Methods: Clinical trials investigating medications for ASD and presenting both dichotomous and continuous CGI-I data were included. The number of patients with at least much improvement (CGI-I ≤ 2) were imputed from the CGI-I scale, assuming an underlying normal distribution of a latent continuous score using a primary threshold θ = 2.5 instead of θ = 2, which is the original cut-off in the CGI-I scale. The original and imputed values were used to calculate responder rates and odds ratios. The performance of the imputation method was investigated with a concordance correlation coefficient (CCC), linear regression, Bland–Altman plots, and subgroup differences of summary estimates obtained from random-effects meta-analysis. Results: Data from 27 studies, 58 arms, and 1428 participants were used. The imputation method using the primary threshold (θ = 2.5) had good performance for the responder rates (CCC = 0.93 95% confidence intervals [0.86, 0.96]; β of linear regression = 1.04 [0.95, 1.13]; bias and limits of agreements = 4.32% [−8.1%, 16.74%]; no subgroup differences χ 2 = 1.24, p-value = 0.266)
and odds ratios (CCC = 0.91 [0.86, 0.96]; β = 0.96 [0.78, 1.14]; bias = 0.09 [−0.87, 1.04]; χ 2 = 0.02, p-value = 0.894). The imputation method had poorer performance when the secondary threshold (θ = 2) was used. Discussion: Assuming a normal distribution of the CGI-I scale, the number of responders could be imputed from the mean and standard deviation and used in meta-analysis. Due to the wide limits of agreement of the imputation method, sensitivity analysis excluding studies with imputed values should be performed.

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