MethodsToward Causally Interpretable Meta-analysis Transporting Inferences from Multiple Randomized Trials to a New Target PopulationDahabreh, Issa J.a,b,c; Petito, Lucia C.d; Robertson, Sarah E.a; Hernán, Miguel A.c,e,f; Steingrimsson, Jon A.gAuthor Information From the aCenter for Evidence Synthesis in Health and Department of Health Services, Policy & Practice, School of Public Health, Brown University, Providence, RI bDepartment of Epidemiology, School of Public Health, Brown University, Providence, RI cDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA dDepartment of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL eDepartment of Biostatistics, Harvard School of Public Health, Boston, MA fHarvard-MIT Division of Health Sciences and Technology, Boston, MA gDepartment of Biostatistics, School of Public Health, Brown University, Providence, RI. Editor’s Note: A related commentary on this article appears on p. 353. Submitted April 14, 2019; accepted February 6, 2020. This work was supported in part by Patient-Centered Outcomes Research Institute (PCORI) awards ME-1306-03758 and ME-1502-27794 (Dahabreh); National Institutes of Health (NIH) grant R37 AI102634 (Hernán); and Agency for Healthcare Research and Quality (AHRQ) National Research Service Award T32AGHS00001 (Robertson). The content of this paper does not necessarily represent the views of the PCORI, its Board of Governors, the Methodology Committee, the NIH, or AHRQ. The authors report no conflicts of interest. Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com). Computer code: We have provided R code to implement the methods described in this paper. Correspondence: Issa J. Dahabreh, Center for Evidence Synthesis in Health, School of Public Health, Brown University, Box G-S121-8, Providence, RI 02912. E-mail: email@example.com Epidemiology: May 2020 - Volume 31 - Issue 3 - p 334-344 doi: 10.1097/EDE.0000000000001177 Buy SDC Metrics Abstract We take steps toward causally interpretable meta-analysis by describing methods for transporting causal inferences from a collection of randomized trials to a new target population, one trial at a time and pooling all trials. We discuss identifiability conditions for average treatment effects in the target population and provide identification results. We show that the assumptions that allow inferences to be transported from all trials in the collection to the same target population have implications for the law underlying the observed data. We propose average treatment effect estimators that rely on different working models and provide code for their implementation in statistical software. We discuss how to use the data to examine whether transported inferences are homogeneous across the collection of trials, sketch approaches for sensitivity analysis to violations of the identifiability conditions, and describe extensions to address nonadherence in the trials. Last, we illustrate the proposed methods using data from the Hepatitis C Antiviral Long-Term Treatment Against Cirrhosis Trial. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.