Comparar métodos

	Análise Kaplan-Meier Retrospectiva	Cox Proportional Hazards
Área	Epidemiologia	Epidemiologia
Família	Process / pipeline	Process / pipeline
Ano de origem	1958 (method); retrospective application standard in clinical research since 1970s–1980s)	1972
Autor original	Edward L. Kaplan and Paul Meier	Sir David Roxbee Cox
Tipo	Non-parametric survival analysis applied to historical data	Semi-parametric regression model
Fonte seminal	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481.	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
Outros nomes	retrospective KM analysis, retrospective survival curve estimation, historical Kaplan-Meier, retrospective KM estimator	Cox regression, Cox PH model, proportional hazards model, CPH
Relacionados	5	5
Resumo	Retrospective Kaplan-Meier analysis applies the Kaplan-Meier product-limit estimator to time-to-event data drawn from existing records — medical charts, registries, or administrative databases — rather than from a prospectively followed cohort. The method estimates the probability of surviving (or remaining event-free) beyond any given time point while accounting for participants whose follow-up ended before the event occurred (censored observations). It is among the most commonly reported analyses in clinical oncology, cardiology, and surgery.	The Cox proportional hazards model is a semi-parametric regression method that estimates the effect of one or more covariates on the hazard — the instantaneous rate of an event such as death, relapse, or failure — while making no assumption about the shape of the baseline hazard function. Introduced by David Cox in 1972, it is the dominant tool for multivariable survival analysis in clinical and epidemiological research.