Survival
analysis is used to study survival duration and the effects of covariates on survival.
Time
is measured as time to death.
The
best zero time is point of randomization. Other zero times are: enrolment, the first visit, first symptoms, diagnosis, and
start of treatment.
A
major problem of survival analysis is censoring. Censoring is loss of information due to withdrawal from the study, study
termination, loss to follow-up, or death due to a competing risk.
Two non-regression methods are used in survival analysis: the life-table and the Kaplan-Maier methods.
The life-table method performs better with large data sets and when the time of occurrence of an event cannot be measured
precisely. The Kaplan-Maier method is best used for small data sets in which the time of event occurrence is measured precisely.
The Proportional hazards method proposed by Sir David Cox in 1972, is the most
popular regression method for survival analysis. It is used on data whose distribution is unknown.
Both the Lifetable and the Kaplan-Maier methods
produce survival curves comparing survival produced by 2 treatments. A test of the hypothesis of no difference between the
2 curves is performed using one of the following methods: Gehan’s
generalized Wilcoxon test, the Cox-Mantel test, the log-rank test, Peto’s generalized Wilcoxon test, the Mantel-Haenszel
test, and Cox’s F test.
