So sánh phương pháp

	Phân tích Rủi ro Cạnh tranh 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	1999 (Fine-Gray); extended to multicenter settings throughout 2000s–2010s	Mid-to-late 20th century (widespread adoption 1970s–1990s)
Người khởi xướng	Fine & Gray (subdistribution hazard model); Prentice et al. (cause-specific hazard model)	Developed incrementally through large collaborative epidemiological projects (e.g., Framingham Heart Study consortium expansions, 1948 onward; EPIC study, 1992)
Loại	Survival / time-to-event statistical analysis	Observational longitudinal study
Công trình gốc	Fine, J. P., & Gray, R. J. (1999). A proportional hazards model for the subdistribution of a competing risk. Journal of the American Statistical Association, 94(446), 496–509.	Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641
Tên gọi khác	multicenter CRA, multi-site competing risks, multicenter cumulative incidence analysis, polycentric competing risks study	multisite cohort study, multi-centre cohort, collaborative cohort study, pooled cohort study
Liên quan	4	6
Tóm tắt	Multicenter competing risks analysis is a time-to-event method applied across multiple clinical centers to estimate the probability of a specific event of interest when other mutually exclusive events — competing risks — can preclude its occurrence. By pooling data from diverse sites, it achieves the sample sizes needed to model rare events and enables assessment of center-level variation in cumulative incidence and covariate effects.	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.