# Cox model

- A
**Cox model**is a well-recognised 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).**Censored**survival times occur if the event of interest does not occur for a patient during the study period.- A Cox model provides an
**estimate of the treatment effect on survival**after adjustment for other explanatory variables. It allows us to estimate the hazard (or risk) of death, or other event of interest, for individuals, given their prognostic variables. - Even if the treatment groups are similar with respect to the variables known to effect survival, using the Cox model with these prognostic variables may produce a more precise estimate of the treatment effect (for example, by narrowing the confidence interval).
- Interpreting a 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, for higher values. Conversely, a negative regression coefficient implies a better prognosis for patients with higher values
- of that variable.

Bandolier has available a longer essay on Cox models - What is a Cox model?