Comparar métodos

	Análisis meta-analítico de Kaplan-Meier	Modelo de Riesgos Proporcionales de Cox
Campo	Epidemiología	Epidemiología
Familia	Process / pipeline	Process / pipeline
Año de origen	2007–2012 (systematic formalization)	1972
Autor original	Building on Kaplan & Meier (1958); meta-analytic extension formalized by Tierney et al. (2007) and Guyot et al. (2012)	Sir David Roxbee Cox
Tipo	Quantitative meta-analytic method	Semi-parametric regression model
Fuente seminal	Guyot, P., Ades, A. E., Ouwens, M. J., & Welton, N. J. (2012). Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves. BMC Medical Research Methodology, 12, 9.	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
Alias	KM meta-analysis, pooled Kaplan-Meier analysis, survival meta-analysis, IPD-KM meta-analysis	Cox regression, Cox PH model, proportional hazards model, CPH
Relacionados	4	5
Resumen	Meta-analytic Kaplan-Meier analysis synthesizes time-to-event data across multiple studies by pooling Kaplan-Meier survival estimates, either from reconstructed individual patient data or from summary statistics extracted from published curves. It produces a pooled survival function with confidence bands and enables formal heterogeneity testing across studies, offering higher statistical power and more generalizable survival estimates than any single study alone.	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.