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Survival from cancer or other chronic diseases is often measured using the relative survival rate. This, in turn, is defined as the ratio of the observed survival rate in the patient group under consideration to the expected survival rate in a group taken from the general population. At the beginning of the follow-up period, apart from the disease under study, factors affecting survival (e.g. age and sex) should be similar in the two groups. This paper outlines how a proportional hazards regression model may be adapted to the relative survival rates using GLIM. The method is illustrated by data on lung cancer patients diagnosed in Finland in 1 968-1 970.
Hakulinen et al. (Thu,) studied this question.