Comparer des méthodes

	Régression de Cox à risques proportionnels ajustés sur le risque	Test du Log-Rank pour la Comparaison des Courbes de Survie
Domaine	Épidémiologie	Analyse de survie
Famille	Process / pipeline	Survival analysis
Année d'origine	1972 (Cox model); risk adjustment widespread from 1980s	1966
Auteur d'origine	D. R. Cox (base model); risk-adjustment as routine practice formalised through clinical epidemiology literature from the 1980s onward	Mantel, N.
Type	Multivariable survival regression	Non-parametric hypothesis test
Source fondatrice	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.	Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170.
Alias	adjusted Cox regression, multivariable Cox model, covariate-adjusted survival analysis, risk-adjusted survival model	Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi
Apparentées	5	2
Résumé	Risk-adjusted Cox proportional hazards regression extends the classical Cox (1972) survival model by simultaneously entering known confounders — age, sex, comorbidities, disease severity — into the model alongside the exposure of primary interest. This adjustment isolates the independent effect of the exposure on the hazard of an event, producing hazard ratios (HRs) that are not distorted by baseline differences between comparison groups. It is the most widely used method for multivariable survival analysis in clinical and epidemiological research.	The log-rank test, developed by Nathan Mantel in 1966, is a non-parametric hypothesis test that compares the overall survival experience of two or more groups throughout the entire follow-up period. It is the standard companion to Kaplan-Meier curves and determines whether observed differences between curves are statistically meaningful.