In biostatistics, survival rate is a part of the survival analysis, indicating the percentage of people in a study or treatment group who are alive for a given period of time after diagnosis. Survival rates are important for prognosis, for example if a type of cancer has a good or bad prognosis can be determined from its survival rate.
Patients with a certain disease can die directly from that disease, or from an unrelated cause such as a car accident. When the precise cause of death is not specified, this is called the overall survival rate or observed survival rate. Doctor's often use mean overall survival rates to estimate the patient's prognosis. This is often expressed over standard time periods, like one, five and ten years. For example, prostate cancer has a much higher one year overall survival rate than pancreatic cancer, and thus has a better prognosis.
When more interested in how survival is affected by the disease, there is also the net survival rate that filters out the effect of mortality from other causes than from the disease. The two main ways to calculate net survival are relative survival and cause specific survival or disease specific survival.
Relative survival is calculated by dividing the overall survival after diagnosis of a disease by the survival as observed in a similar population that was not diagnosed with that disease. A similar population is composed by making at least age and gender similar as in the population diagnosed with the disease.
Cause specific survival is calculated by treating deaths from other causes than the disease as withdrawals from the population that don't lower survival, comparable to patients who are not observed any longer, e.g. due to reaching the end of the study period.
Relative survival has the advantage that it does not depend on accuracy of the reported cause of death, cause specific survival has the advantage that it does not depend on the ability to find a similar population of people without the disease.