Assessing impact of organised breast screening across small residential areas-development and internal validation of a prediction model

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dc.contributor.authorBuckley, E.
dc.contributor.authorFarshid, G.
dc.contributor.authorGill, G.
dc.contributor.authorKollias, J.
dc.contributor.authorKoczwara, B.
dc.contributor.authorKarapetis, C.
dc.contributor.authorAdams, J.
dc.contributor.authorJoshi, R.
dc.contributor.authorKeefe, D.
dc.contributor.authorNiyonsenga, T.
dc.contributor.authorPowell, K.
dc.contributor.authorFusco, K.
dc.contributor.authorEckert, M.
dc.contributor.authorBeckmann, K.
dc.contributor.authorRoder, D.
dc.date.issued2017
dc.description.abstractMonitoring screening mammography effects in small areas is often limited by small numbers of deaths and delayed effects. We developed a risk score for breast cancer death to circumvent these limitations. Screening, if effective, would increase post-diagnostic survivals through lead-time and related effects, as well as mortality reductions. Linked cancer and BreastScreen data at four hospitals (n = 2,039) were used to investigate whether screened cases had higher recorded survivals in 13 small areas, using breast cancer deaths as the outcome (M1), and a risk of death score derived from TNM stage, grade, histology type, hormone receptor status, and related variables (M2). M1 indicated lower risk of death in screened cases in 12 of the 13 areas, achieving statistical significance (p < .05) in 5. M2 indicated lower risk scores in screened cases in all 13 areas, achieving statistical significance in 12. For cases recently screened at diagnosis (<6 months), statistically significant reductions applied in 8 areas (M1) and all 13 areas (M2). Screening effects are more detectable in small areas using these risk scores than death itself as the outcome variable. An added advantage is the application of risk scores for providing a marker of screening effect soon after diagnosis.
dc.description.statementofresponsibilityE. Buckley G. Farshid, G. Gill, J. Kollias, B. Koczwara, C. Karapetis, J. Adams, R. Joshi, D. Keefe, T. Niyonsenga, K. Powell, K. Fusco, M. Eckert, K. Beckmann, D. Roder
dc.identifier.citationEuropean Journal of Cancer Care, 2017; 26(4):e12673-1-e12673-8
dc.identifier.doi10.1111/ecc.12673
dc.identifier.issn0961-5423
dc.identifier.issn1365-2354
dc.identifier.orcidBuckley, E. [0000-0001-8980-1194]
dc.identifier.orcidFarshid, G. [0000-0002-2056-0561]
dc.identifier.orcidGill, G. [0000-0001-7310-2970]
dc.identifier.orcidJoshi, R. [0000-0003-4607-3937]
dc.identifier.orcidKeefe, D. [0000-0001-9377-431X]
dc.identifier.orcidFusco, K. [0000-0002-5965-1364]
dc.identifier.orcidRoder, D. [0000-0001-6442-4409]
dc.identifier.urihttp://hdl.handle.net/2440/106959
dc.language.isoen
dc.publisherWiley-Blackwell
dc.rights© 2017 John Wiley & Sons Ltd
dc.source.urihttps://doi.org/10.1111/ecc.12673
dc.subjectbreast screening
dc.subjecteffect monitoring
dc.subjectsmall areas
dc.titleAssessing impact of organised breast screening across small residential areas-development and internal validation of a prediction model
dc.typeJournal article
pubs.publication-statusPublished

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