Expert consensus outlines 17 recommendations for enhancing causal inference using real-world data in clinical studies.
The emulated target trial (TTE) is a real-world data-based research approach that seeks to emulate randomized controlled trials within observational datasets to enable relatively high-quality causal inference. In recent years, with the accumulation of medical big data and real-world cohort data, an increasing number of clinical studies have adopted TTE designs following the principles of randomized controlled trials. However, the methodological rigor and quality of such studies remain uneven. In this context, a multidisciplinary group composed of the Rehabilitation Big Data Working Committee of Chinese Association of Rehabilitation Medicine and experts and scholars from institutions across China-with expertise in clinical medicine, epidemiology and biostatistics, research methodology, evidence-based medicine, and data science-conducted extensive literature reviews and multiple rounds of expert consultation and discussion. This process culminated in the development of the Expert Consensus on the Standardized Application of Emulated Target Trials in Clinical Research (2025 edition). This consensus explicitly proposes 17 recommendations, systematically defining the concept, applicable scenarios, and core components of TTE, and comprehensively addressing key methodological aspects of TTE studies, including selection of data sources, new-user design, determination of time zero, and choice of post-hoc randomization methods. It fills an important gap in China's methodological standards for TTE applications, offering scientific guidance for the rigorous implementation of TTE designs and making a meaningful contribution to the advancement of clinical research.
No takes yet. Share an insight, caveat, or question.
A 2025 study studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: