title: Choosing the relative survival method for cancer survival estimation.
abstract: BACKGROUND
  The methods on how to calculate cumulative relative survival have been ambiguous and have given differences in empirical results.
  
  
  METHODS
  The gold standard for the cumulative relative survival ratio is the weighted average of age-specific cumulative relative survival ratios, with weights proportional to numbers of patients at diagnosis. Mathematics and representative empirical materials from the population-based Finnish Cancer Registry were studied for the different relative survival methods and compared with the gold standard.
  
  
  RESULTS
  The theoretical and empirical results show a good agreement between the method suggested in 1959 by Ederer and Heise (the so-called Ederer II method) and the gold standard. This result is in part due the fact that as follow-up time increases the conditional (annual) relative survival ratios become increasingly more independent of age. Moreover, the dependence between the excess mortality due to cancer and the baseline general mortality does not introduce an important enough selection in practice to cause a notable bias.
  
  
  CONCLUSIONS
  The use of the method by Ederer and Heise, multiplication of the annual relative survival ratios, instead of direct standardisation, should be considered in future applications. This would be particularly important for the long-term follow-up when age-specific relative survival is not available in the oldest age categories.
authors.affiliation: Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Pieni Roobertinkatu 9, FI-00130 Helsinki, Finland. timo.hakulinen@cancer.fi
authors.forename: Timo
authors.initials: T
authors.lastname: Hakulinen
authors.forename: Karri
authors.initials: K
authors.lastname: Seppä
authors.forename: Paul C
authors.initials: PC
authors.lastname: Lambert
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002423:Cause of Death; D002648:Child; D002675:Child, Preschool; D003627:Data Interpretation, Statistical; D005260:Female; D005387:Finland; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009369:Neoplasms / Q000401:mortality*; D012042:Registries; D016019:Survival Analysis; D055815:Young Adult