What is a Cox model?

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A Cox model is a statistical technique for exploring the relationship between the survival of a patient and several explanatory variables.

Survival analysis is concerned with studying the time between entry to a study and a subsequent event (such as death).

A Cox model provides an estimate of the treatment effect on survival after adjustment for other explanatory variables. In addition, it allows us to estimate the hazard (or risk) of death for an individual, given their prognostic variables.

A Cox model must be fitted using an appropriate computer program (such as SAS, STATA, SPSS or R). The final model from a Cox regression analysis will yield an equation for the hazard as a function of several explanatory variables.

Interpreting the Cox model involves examining the coefficients for each explanatory variable. A positive regression coefficient for an explanatory variable means that the hazard is higher, and thus the prognosis worse. Conversely, a negative regression coefficient implies a better prognosis for patients with higher values of that variable.