Limits...
Spatial variation in prostate cancer survival in the Northern and Yorkshire region of England using Bayesian relative survival smoothing.

Fairley L, Forman D, West R, Manda S - Br. J. Cancer (2008)

Bottom Line: All covariates had a significant association with excess mortality; men from more deprived areas, older age at diagnosis and diagnosed in 1990-1994 had higher excess mortality.The unadjusted relative excess risks (RER) of death by PCT ranged from 0.75 to 1.66.After adjustment, areas of high and low excess mortality were smoothed towards the mean, and the RERs ranged from 0.74 to 1.49.

View Article: PubMed Central - PubMed

Affiliation: Northern and Yorkshire Cancer Registry and Information Service, St James's Institute of Oncology, St James's University Hospital, Level 6, Bexley Wing, Beckett Street, Leeds LS9 7TF, UK. lesley.fairley@nycris.leedsth.nhs.uk

ABSTRACT
Primary Care Trust (PCT) estimates of survival lack robustness as there are small numbers of deaths per year in each area, even when incidence is high. We assess PCT-level spatial variation in prostate cancer survival using Bayesian spatial models of excess mortality. We extracted data on men diagnosed with prostate cancer between 1990 and 1999 from the Northern and Yorkshire Cancer Registry and Information Service database. Models were adjusted for age at diagnosis, period of diagnosis and deprivation. All covariates had a significant association with excess mortality; men from more deprived areas, older age at diagnosis and diagnosed in 1990-1994 had higher excess mortality. The unadjusted relative excess risks (RER) of death by PCT ranged from 0.75 to 1.66. After adjustment, areas of high and low excess mortality were smoothed towards the mean, and the RERs ranged from 0.74 to 1.49. Using Bayesian smoothing techniques to model cancer survival by geographic area offers many advantages over traditional methods; estimates in areas with small populations or low incidence rates are stabilised and shrunk towards local and global risk estimates improving reliability and precision, complex models are easily handled and adjustment for covariates can be made.

Show MeSH

Related in: MedlinePlus

Map of fully adjusted smoothed PCT spatial effects.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2600701&req=5

fig5: Map of fully adjusted smoothed PCT spatial effects.

Mentions: The maps in Figures 4 and 5 show the unadjusted and fully adjusted spatially smoothed RERs for each PCT. After adjusting for the covariates areas of high and low excess mortality were smoothed towards the mean, the number of PCTs with RER above 1.25 reduced from five to three whereas the number of PCTs with RER under 0.85 reduced from eight to four. After adjusting for the covariates area with higher excess risk of deaths were found in West Cumbria, North Lincolnshire and North East Lincolnshire whereas the areas with low excess risk of death were found in Huddersfield Central, South Huddersfield, Darlington and Wakefield West.


Spatial variation in prostate cancer survival in the Northern and Yorkshire region of England using Bayesian relative survival smoothing.

Fairley L, Forman D, West R, Manda S - Br. J. Cancer (2008)

Map of fully adjusted smoothed PCT spatial effects.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2600701&req=5

fig5: Map of fully adjusted smoothed PCT spatial effects.
Mentions: The maps in Figures 4 and 5 show the unadjusted and fully adjusted spatially smoothed RERs for each PCT. After adjusting for the covariates areas of high and low excess mortality were smoothed towards the mean, the number of PCTs with RER above 1.25 reduced from five to three whereas the number of PCTs with RER under 0.85 reduced from eight to four. After adjusting for the covariates area with higher excess risk of deaths were found in West Cumbria, North Lincolnshire and North East Lincolnshire whereas the areas with low excess risk of death were found in Huddersfield Central, South Huddersfield, Darlington and Wakefield West.

Bottom Line: All covariates had a significant association with excess mortality; men from more deprived areas, older age at diagnosis and diagnosed in 1990-1994 had higher excess mortality.The unadjusted relative excess risks (RER) of death by PCT ranged from 0.75 to 1.66.After adjustment, areas of high and low excess mortality were smoothed towards the mean, and the RERs ranged from 0.74 to 1.49.

View Article: PubMed Central - PubMed

Affiliation: Northern and Yorkshire Cancer Registry and Information Service, St James's Institute of Oncology, St James's University Hospital, Level 6, Bexley Wing, Beckett Street, Leeds LS9 7TF, UK. lesley.fairley@nycris.leedsth.nhs.uk

ABSTRACT
Primary Care Trust (PCT) estimates of survival lack robustness as there are small numbers of deaths per year in each area, even when incidence is high. We assess PCT-level spatial variation in prostate cancer survival using Bayesian spatial models of excess mortality. We extracted data on men diagnosed with prostate cancer between 1990 and 1999 from the Northern and Yorkshire Cancer Registry and Information Service database. Models were adjusted for age at diagnosis, period of diagnosis and deprivation. All covariates had a significant association with excess mortality; men from more deprived areas, older age at diagnosis and diagnosed in 1990-1994 had higher excess mortality. The unadjusted relative excess risks (RER) of death by PCT ranged from 0.75 to 1.66. After adjustment, areas of high and low excess mortality were smoothed towards the mean, and the RERs ranged from 0.74 to 1.49. Using Bayesian smoothing techniques to model cancer survival by geographic area offers many advantages over traditional methods; estimates in areas with small populations or low incidence rates are stabilised and shrunk towards local and global risk estimates improving reliability and precision, complex models are easily handled and adjustment for covariates can be made.

Show MeSH
Related in: MedlinePlus