the total number of deaths (overall number of deaths) minus the expected number of deaths in the general population. If 10 deaths per hundred population occur in a population of cancer patients, but only 1 death occurs per hundred general population, the disease specific number of deaths (excess hazard rate) is 9 deaths per hundred population. The classic equation for the excess hazard rate is as follows: The equation does not define a survival proportion but simply describes the relationships between disease-specific death (excess hazard) rates, background mortality rates (expected death rate) and the overall observed mortality rates. The excess hazard rate is related to relative survival, just as hazard rates are related to overall survival. Cancer survival Relative survival is typically used in the analysis of cancer registry data. Cause-specific survival estimation using the coding of death certificates has considerable inaccuracy and inconsistency and does not permit the comparison of rates across registries. The diagnosis of cause-of-death is varied between practitioners. How does one code for a patient who dies of heart failure after receiving a chemotherapeutic agent with known deleterious cardiac side-effects? In essence, what really matters is not why the population dies but if the rate of death is higher than that of the general population. If all patients are dying of car crashes, perhaps the tumour or treatment predisposes them to have visual or perceptual disturbances, which lead them to be more likely to die in a car crash. In addition, it has been shown that patients coded in a large US cancer registry as suffering from a non-cancer death are 1.37 times as likely to die than does a member of the general population. If the coding was accurate, this figure should approximate 1.0 as the rate of those dying of non-cancer deaths (in a population of cancer sufferers) should approximate that of the general population. Thus, the use of relative survival provides an accurate way to measure survival rates that are associated with the cancer in question. Epidemiology In epidemiology, relative survival (as opposed to overall survival and associated with excess hazard rates) is defined as the ratio of observed survival in a population to the expected or background survival rate. It can be thought of as the kaplan-meier survivor function for a particular year, divided by the expected survival rate in that particular year. That is typically known as the relative survival (RS).