title: Cancer mortality trends in the EU and acceding countries up to 2015.
abstract: BACKGROUND
  Examination of trends in cancer mortality in Europe over the past 30 years has shown that, after long-term rises, age-standardised mortality from most common cancer sites has fallen in the EU since the late 1980s. This study aimed to examine trends in the age-specific and age-standardised cancer mortality rates and numbers of cancer deaths up to 2020 for all cancers and various specific sites for all 15 EU countries, the 10 acceding countries, Bulgaria and Romania (currently applicant countries, along with Turkey), and Iceland, Norway and Switzerland of the four EEA countries.
  
  
  METHODS
  Mortality rates were modelled as a function of age, calendar period and birth cohort. Birth cohort was calculated as age subtracted from calendar period.
  
  
  RESULTS
  As a consequence of the generally decreasing trends in the age-standardised rates, the best estimate is that there will be approximately 1.25 million cancer deaths in 2015, which is almost 130,000 (11%) more deaths than in 2000, but 155,000 (11%) fewer deaths than the 1.4 million projected in 2015 on the basis of demographic changes alone. The increases in the forecast numbers of cancer deaths in 2015 are proportionally larger in males than in females (13% and 10%, respectively) and proportionally larger in the acceding countries than in the current EU member countries (14% and 11%, respectively).
  
  
  CONCLUSIONS
  Our forecasts are conservative best estimates of future cancer mortality. There is clearly scope for large improvements in survival, and hence reductions in cancer mortality, in some countries, through eliminating these differences using existing knowledge and treatment regimes.
authors.affiliation: National Cancer Intelligence Centre, Office for National Statistics, London, UK. mike.quinn@ons.gsi.gov.uk
authors.forename: M J
authors.initials: MJ
authors.lastname: Quinn
authors.forename: A
authors.initials: A
authors.lastname: d'Onofrio
authors.forename: B
authors.initials: B
authors.lastname: Møller
authors.forename: R
authors.initials: R
authors.lastname: Black
authors.forename: C
authors.initials: C
authors.lastname: Martinez-Garcia
authors.forename: H
authors.initials: H
authors.lastname: Møller
authors.forename: M
authors.initials: M
authors.lastname: Rahu
authors.forename: C
authors.initials: C
authors.lastname: Robertson
authors.forename: L J
authors.initials: LJ
authors.lastname: Schouten
authors.forename: C
authors.initials: C
authors.lastname: La Vecchia
authors.forename: P
authors.initials: P
authors.lastname: Boyle
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D005060:Europe / Q000453:epidemiology; D005260:Female; D005544:Forecasting; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D009026:Mortality / Q000639:trends*; D009369:Neoplasms / Q000401:mortality*