Randomized controlled trial (RCT) are considered the "gold standard" for evaluating the causal effects of interventions on outcome measures. However, due to high research costs and ethical constraints, conducting RCT in clinical practice, especially in the surgical field, faces numerous challenges such as difficulties in subject recruitment, implementation of blinding, and standardization of interventions. In such cases, using real-world data to perform causal inference under the framework of target trial emulation (TTE), based on the principles of RCT design, helps to identify and reduce biases arising from design flaws in traditional observational studies, such as immortal time bias, confounding, selection bias, or collider bias. This approach can produce high-quality evidence comparable to that of RCT, thereby enhancing the clinical guidance value of real-world data studies. However, TTE has limitations, such as the inability to completely eliminate confounding, high quality requirements for source data, and the current lack of reporting standards. Therefore, researchers should be fully aware of these limitations to avoid making incorrect causal inferences. This article intends to provide an overview of the TTE framework, implementation points, application scope, application cases, and advantages and disadvantages of the framework.
Esophageal cancer remains a persistently high disease burden and marked disparities across high- and low-incidence regions, urban and rural areas, and different tiers of healthcare institutions in China. Conventional care models centered on isolated interventions, such as surgery, chemoradiotherapy or immunotherapy, are insufficient to systematically address inadequate identification of high-risk populations, low screening adherence, heterogeneous diagnostic staging, inconsistent implementation of multidisciplinary team (MDT) decision-making, and discontinuities in rehabilitation, recurrence surveillance and palliative care after discharge. Based on national screening policies, domestic and international guidelines, randomized controlled trials, systematic reviews/meta-analyses, health-economic studies and real-world evidence from China, this article constructs a China-specific whole-course management pathway for esophageal cancer along the logical chain of "disease burden-baseline management gaps-pathway model-quality indicators-data feedback." The proposed pathway follows the main sequence of risk stratification, tiered screening, precision staging, MDT-based decision-making, standardized treatment, rehabilitation and follow-up, palliative care and data feedback. It defines the responsibilities of primary care facilities, regional centers and national centers, as well as referral triggers, key time targets, quality indicators, criteria for priority high-risk populations, and data dictionary and quality-control requirements for a national disease-specific database. A feasible Chinese model should use county-level electronic registration and endoscopic screening of high-risk populations as entry points, regional MDTs and disease-specific information platforms as hubs, and nutrition/prehabilitation, patient-reported outcomes and real-world data as supporting systems, thereby establishing a replicable, evaluable, reimbursable and sustainable closed-loop management system for esophageal cancer.