So sánh phương pháp

	Phân tích sống còn tiến cứu	Phân tích Kaplan-Meier
Lĩnh vực	Dịch tễ học	Dịch tễ học
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1958–1972 (foundational methods); prospective design emphasis formalized by 1980s	1958
Người khởi xướng	Kaplan & Meier (estimator, 1958); Cox (proportional hazards model, 1972); prospective design formalised in modern clinical epidemiology	Edward L. Kaplan and Paul Meier
Loại	Longitudinal observational or experimental study design with time-to-event analysis	Nonparametric survival estimator
Công trình gốc	Kleinbaum, D. G., & Klein, M. (2012). Survival Analysis: A Self-Learning Text (3rd ed.). Springer. ISBN: 978-1441966452	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481.
Tên gọi khác	prospective time-to-event analysis, prospective failure-time analysis, forward-looking survival study, prospective event-time study	KM analysis, KM estimator, product-limit estimator, Kaplan-Meier curve
Liên quan	5	5
Tóm tắt	Prospective survival analysis is a longitudinal study design in which participants are enrolled before the event of interest occurs, followed forward in time under standardised conditions, and analysed using survival-analytic methods to estimate the time until a defined clinical endpoint — such as death, disease recurrence, or treatment failure. Because data are collected prospectively, exposure and covariate information are recorded before outcomes are known, substantially reducing recall and selection bias relative to retrospective approaches.	Kaplan-Meier (KM) analysis is a nonparametric method for estimating the survival function from time-to-event data. Introduced by Kaplan and Meier in 1958, it produces the classic step-function survival curve that shows the probability of surviving beyond each observed event time, correctly accounting for censored observations — participants who left the study or had not yet experienced the event by the end of follow-up. It is one of the most widely used techniques in clinical and epidemiological research.