A mixed linear model controlling for case underascertainment across multiple cancer registries estimated time trends in survival

  • Stefan Dahm
    Correspondence
    Corresponding author. Tel.: +49-30-18754-3761; fax: +49-30-18754-3349.
    Affiliations
    German Center for Cancer Registry Data, Department for Epidemiology and Health Reporting, Robert Koch-Institute, General-Pape-Str. 62-66, D-12101 Berlin, Germany
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  • Joachim Bertz
    Affiliations
    German Center for Cancer Registry Data, Department for Epidemiology and Health Reporting, Robert Koch-Institute, General-Pape-Str. 62-66, D-12101 Berlin, Germany
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  • Benjamin Barnes
    Affiliations
    German Center for Cancer Registry Data, Department for Epidemiology and Health Reporting, Robert Koch-Institute, General-Pape-Str. 62-66, D-12101 Berlin, Germany
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  • Klaus Kraywinkel
    Affiliations
    German Center for Cancer Registry Data, Department for Epidemiology and Health Reporting, Robert Koch-Institute, General-Pape-Str. 62-66, D-12101 Berlin, Germany
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      Abstract

      Objectives

      Large temporal and geographical variation in survival rates estimated from epidemiological cancer registries coupled with heterogeneity in death certificate only (DCO) notifications makes it difficult to interpret trends in survival. The aim of our study is to introduce a method for estimating such trends while accounting for heterogeneity in DCO notifications in a cancer site-specific manner.

      Study Design and Setting

      We used the data of 4.0 million cancer cases notified in 14 German epidemiological cancer registries. Annual 5-year relative survival rates from 2002 through 2013 were estimated, and proportions of DCO notifications were recorded. “DCO-excluded” survival rates were regressed on DCO proportions and calendar years using a mixed linear model with cancer registry as a random effect. Based on this model, trends in survival rates were estimated for Germany at 0% DCO.

      Results

      For most cancer sites and age groups, we estimated significant positive trends in survival. Age-standardized survival for all cancers combined increased by 7.1% units for women and 10.8% units for men.

      Conclusion

      The described method could be used to estimate trends in cancer survival based on the data from epidemiological cancer registries with differing DCO proportions and with changing DCO proportions over time.

      Keywords

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