Influence of alternative mammographic screening scenarios on breast cancer incidence predictions (Finland) View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2006-11

AUTHORS

Johanna Seppänen, Sirpa Heinävaara, Timo Hakulinen

ABSTRACT

BackgroundA population-based early detection programme for breast cancer has been in progress in Finland since 1987. Recently, detailed information about actual screening invitation schemes in 1987–2001 has become available in electronic form, which enables more specific modeling of breast cancer incidence.ObjectivesTo present a methodology for taking into account historical municipality-specific schemes of mass screening when constructing predictions for breast cancer incidence. To provide predictions for numbers of new cancer cases and incidence rates according to alternative future screening policies.MethodsObserved municipality-specific screening invitation schemes in Finland during 1987–2001 were linked together with breast cancer data. The incidence rate during the observation period was analyzed using Poisson regression, and this was done separately for localized and non-localized cancers. For modeling, the screening programme was divided into seven different components. Alternative screening scenarios for future mass-screening practices in Finland were created and an appropriate model for incidence prediction was defined.Results and conclusionExpanding the screening programme would increase the incidence of localized breast cancers; the biggest increase would be obtained by expanding from women aged 50–59 to 50–69. The impacts of changes in the screening practices on predictions for non-localized cancers would be minor. More... »

PAGES

1135-1144

References to SciGraph publications

  • 2005-06-10. Empirical evaluation of prediction intervals for cancer incidence in BMC MEDICAL RESEARCH METHODOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10552-006-0055-1

    DOI

    http://dx.doi.org/10.1007/s10552-006-0055-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1029411209

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/17006719


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