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.
The treatment goal for acromegaly has shifted from just hitting biochemical targets of growth hormone (GH) and insulin-like growth factor-1 (IGF-1) remission to a long-term, comprehensive improvement that also considers hormones, metabolic regulations, tumor, symptoms, comorbidities, and patient experience. The SAGIT? assessment system, as the first multi-dimensional clinician-reported outcome tool, integrates five aspects: signs and symptoms (S), associated comorbidities (A), GH levels (G), IGF-1 levels (I), and tumor profile (T). It enables quantitative scoring and dynamic stratification of disease severity. International prospective validation studies have shown that each SAGIT? dimension has good discriminatory ability for disease control; a 2025 multicenter study indicated that SAGIT? objectively reflects disease activity. This article systematically reviews the limitations of existing assessment tools, explains the design principles and scoring criteria of SAGIT?, and discusses its clinical value in disease staging, treatment decision-making, efficacy prediction, and follow-up management. Furthermore, it explores future directions for improving SAGIT? and other disease rating tools, including artificial intelligence integration, development of dynamic monitoring modules, and validation and application in Chinese patients with acromegaly.