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      Period analysis for 'up-to-date' cancer survival data: theory, empirical evaluation, computational realisation and applications.

      European Journal of Cancer
      Cohort Studies, Computer Simulation, Demography, Disease-Free Survival, Humans, Neoplasms, mortality, Prognosis, Registries, Survival Analysis, Survival Rate

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          Abstract

          Long-term survival rates are the most commonly used outcome measures for patients with cancer. However, traditional long-term survival statistics, which are derived by cohort-based types of analysis, essentially reflect the survival expectations of patients diagnosed many years ago. They are therefore often severely outdated at the time they become available. A couple of years ago, a new method of survival analysis, denoted period analysis, has been introduced to derive more 'up-to-date' estimates of long-term survival rates. We give a comprehensive review of the new methodology, its statistical background, empirical evaluation, computational realisation and applications. We conclude that period analysis is a powerful tool to provide more 'up-to-date' cancer survival rates. More widespread use by cancer registries should help to increase the use of cancer survival statistics for patients, clinicians, and public health authorities.

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          Journal
          14746849
          10.1016/j.ejca.2003.10.013

          Chemistry
          Cohort Studies,Computer Simulation,Demography,Disease-Free Survival,Humans,Neoplasms,mortality,Prognosis,Registries,Survival Analysis,Survival Rate

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