Estimating the potential survival gains by eliminating socioeconomic and sex inequalities in stage at diagnosis of melanoma View Full Text


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Article Info

DATE

2015-03

AUTHORS

M J Rutherford, L Ironmonger, N Ormiston-Smith, G A Abel, D C Greenberg, G Lyratzopoulos, P C Lambert

ABSTRACT

BACKGROUND: Although inequalities in cancer survival are thought to reflect inequalities in stage at diagnosis, little evidence exists about the size of potential survival gains from eliminating inequalities in stage at diagnosis. METHODS: We used data on patients diagnosed with malignant melanoma in the East of England (2006-2010) to estimate the number of deaths that could be postponed by completely eliminating socioeconomic and sex differences in stage at diagnosis after fitting a flexible parametric excess mortality model. RESULTS: Stage was a strong predictor of survival. There were pronounced socioeconomic and sex inequalities in the proportion of patients diagnosed at stages III-IV (12 and 8% for least deprived men and women and 25 and 18% for most deprived men and women, respectively). For an annual cohort of 1025 incident cases in the East of England, eliminating sex and deprivation differences in stage at diagnosis would postpone approximately 24 deaths to beyond 5 years from diagnosis. Using appropriate weighting, the equivalent estimate for England would be around 215 deaths, representing 11% of all deaths observed within 5 years from diagnosis in this population. CONCLUSIONS: Reducing socioeconomic and sex inequalities in stage at diagnosis would result in substantial reductions in deaths within 5 years of a melanoma diagnosis. More... »

PAGES

s116

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/bjc.2015.50

    DOI

    http://dx.doi.org/10.1038/bjc.2015.50

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1022332021

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/25734390


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    RDF/XML is a standard XML format for linked data.

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