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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.

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Related in: MedlinePlus

Kaplan–Meier Survival curves by each covariate.
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fig1: Kaplan–Meier Survival curves by each covariate.

Mentions: Table 1 shows the distribution of the demographic variables in the study population, with the corresponding 5-year survival and Figure 1 shows the Kaplan–Meier survival curves up to 5 years of follow up by each of the demographic variables. Over 90% of the men were aged 60 and over at diagnosis with 43% of them aged 70–79 years. There were more men from the more deprived areas than the most affluent areas (15% of men were in the most affluent deprivation quintile compared with 24% of men in the most deprived quintile). Slightly more men were diagnosed in the later time period (56%) than in the earlier time period (44%). The overall Kaplan–Meier 5-year survival rate for men diagnosed with prostate cancer in the NYCRIS region was 41% (95% CI 41–42). Survival decreased as age at diagnosis increased; men aged 15–59 years at diagnosis had a 5-year survival rate of 62% whereas it was only 19% for men aged 80 and over at diagnosis. There was a difference of about 8 percentage points in the 5-year survival of men from the most affluent areas compared with those from the most deprived (46 and 38% respectively). The 5-year survival rate of men diagnosed between 1990 and 1994 was significantly lower than for men diagnosed between 1995 and 1999 (35 and 46% respectively).


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)

Kaplan–Meier Survival curves by each covariate.
© Copyright Policy
Related In: Results  -  Collection

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

fig1: Kaplan–Meier Survival curves by each covariate.
Mentions: Table 1 shows the distribution of the demographic variables in the study population, with the corresponding 5-year survival and Figure 1 shows the Kaplan–Meier survival curves up to 5 years of follow up by each of the demographic variables. Over 90% of the men were aged 60 and over at diagnosis with 43% of them aged 70–79 years. There were more men from the more deprived areas than the most affluent areas (15% of men were in the most affluent deprivation quintile compared with 24% of men in the most deprived quintile). Slightly more men were diagnosed in the later time period (56%) than in the earlier time period (44%). The overall Kaplan–Meier 5-year survival rate for men diagnosed with prostate cancer in the NYCRIS region was 41% (95% CI 41–42). Survival decreased as age at diagnosis increased; men aged 15–59 years at diagnosis had a 5-year survival rate of 62% whereas it was only 19% for men aged 80 and over at diagnosis. There was a difference of about 8 percentage points in the 5-year survival of men from the most affluent areas compared with those from the most deprived (46 and 38% respectively). The 5-year survival rate of men diagnosed between 1990 and 1994 was significantly lower than for men diagnosed between 1995 and 1999 (35 and 46% respectively).

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