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  • Bayesian spatial analysis for the evaluation of breast cancer detection methods

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    Author(s)
    Hsieh, Jeff Ching-Fu
    Cramb, Susanna M
    McGree, James M
    Baade, Peter D
    Dunn, Nathan AM
    Mengersen, Kerrie L
    Griffith University Author(s)
    Baade, Peter D.
    Year published
    2013
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    Abstract
    This study investigated the impact of spatial location on the effectiveness of population-based breast screening in reducing breast cancer mortality compared to other detection methods among Queensland women. The analysis was based on linked population-based datasets from BreastScreen Queensland and the Queensland Cancer Registry for the period of 1997-2008 for women aged less than 90 years at diagnosis. A Bayesian hierarchical regression modelling approach was adopted and posterior estimation was performed using Markov Chain Monte Carlo techniques. This approach accommodated sparse data resulting from rare outcomes in small ...
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    This study investigated the impact of spatial location on the effectiveness of population-based breast screening in reducing breast cancer mortality compared to other detection methods among Queensland women. The analysis was based on linked population-based datasets from BreastScreen Queensland and the Queensland Cancer Registry for the period of 1997-2008 for women aged less than 90 years at diagnosis. A Bayesian hierarchical regression modelling approach was adopted and posterior estimation was performed using Markov Chain Monte Carlo techniques. This approach accommodated sparse data resulting from rare outcomes in small geographic areas, while allowing for spatial correlation and demographic influences to be included. A relative survival model was chosen to evaluate the relative excess risk for each breast cancer related factor. Several models were fitted to examine the influence of demographic information, cancer stage, geographic information and detection method on women's relative survival. Overall, the study demonstrated that including the detection method and geographic information when assessing the relative survival of breast cancer patients helped capture unexplained and spatial variability. The study also found evidence of better survival among women with breast cancer diagnosed in a screening program than those detected otherwise, as well as lower risk for those residing in a more urban or socio-economically advantaged region, even after adjusting for tumour stage, environmental factors and demographics. However, no evidence of dependency between method of detection and geographic location was found. This project provides a sophisticated approach to examining the benefit of a screening program while considering the influence of geographic factors.
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    Journal Title
    Australian and New Zealand Journal of Statistics
    Volume
    55
    Issue
    4
    DOI
    https://doi.org/10.1111/anzs.12059
    Copyright Statement
    © 2014 Australian Statistical Publishing Association. This is the author-manuscript version of the paper. Reproduced in accordance with the copyright policy of the publisher.The definitive version is available at http://onlinelibrary.wiley.com/
    Subject
    Statistics
    Oncology and carcinogenesis not elsewhere classified
    Econometrics
    Publication URI
    http://hdl.handle.net/10072/62391
    Collection
    • Journal articles

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