So sánh phương pháp

	Hồi quy Cox Tỷ lệ Tử vong Tỷ lệ Tăng dần Đa trung tâm	Nghiên cứu đoàn hệ đa trung tâm
Lĩnh vực	Dịch tễ học	Dịch tễ học
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1972 (Cox model); multicenter applications formalized 1980s–1990s	Mid-to-late 20th century (widespread adoption 1970s–1990s)
Người khởi xướng	D. R. Cox (Cox PH model); multicenter extension developed through collaborative trial methodology	Developed incrementally through large collaborative epidemiological projects (e.g., Framingham Heart Study consortium expansions, 1948 onward; EPIC study, 1992)
Loại	Semi-parametric survival regression for clustered data	Observational longitudinal study
Công trình gốc	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.	Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641
Tên gọi khác	multicenter Cox regression, multisite Cox PH model, stratified Cox model across centers, multicenter survival regression	multisite cohort study, multi-centre cohort, collaborative cohort study, pooled cohort study
Liên quan	4	6
Tóm tắt	Multicenter Cox proportional hazards regression extends the classic Cox PH model to studies conducted at two or more clinical sites or centers. It estimates the effect of predictors on time-to-event outcomes while explicitly accounting for clustering within centers, between-center heterogeneity, and potential differences in baseline hazard across sites. This design is standard practice in large multicenter RCTs and observational cohort studies in oncology, cardiology, and other clinical fields.	A multicenter cohort study follows defined groups of participants at two or more geographically or institutionally distinct sites over time to estimate incidence, identify risk factors, and quantify associations between exposures and outcomes. By pooling data from multiple centers, it achieves statistical power and population diversity that single-site designs cannot match, making it the workhorse of large-scale epidemiological and clinical research.