Estimating regional variation in cancer survival: a tool for improving cancer care.
OBJECTIVE
To improve estimation of regional variation in cancer survival and identify cancers to which priority might be given to increase survival.


METHODS
Survival measures were calculated for 25 major cancer types diagnosed in each of 17 health service regions in New South Wales, Australia, from 1991 to 1998. Region-specific risks of excess death due to cancer were estimated adjusting for age, sex, and extent of disease at, and years since, diagnosis. Empirical Bayes (EB) methods were used to shrink the estimates. The additional numbers of patients who would survive beyond five years were estimated by shifting the State average risk to the 20th centile.


RESULTS
Statistically significant regional variation in the shrunken estimates of risk of excess death was found for nine of the 25 cancer types. The lives of 2903 people (6.4%) out of the 45,047 whose deaths within 5 years were attributable to cancer could be extended with the highest number being for lung cancer (791).


CONCLUSIONS
The EB approach gives more precise estimates of region-specific risk of excess death and is preferable to standard methods for identifying cancer sites where gains in survival might be made. The estimated number of lives that could be extended can assist health authorities in prioritising investigation of and attention to causes of regional variation in survival.
Yu
Xue Q
XQ
Cancer Epidemiology Research Unit, The Cancer Council New South Wales, P. O. Box 572, Kings Cross, NSW, 1340, Australia. xueqiny@nswcc.org.au
O'Connell
Dianne L
DL
Gibberd
Robert W
RW
Smith
David P
DP
Dickman
Paul W
PW
Armstrong
Bruce K
BK
D000293:Adolescent; D000328:Adult; D000368:Aged; D001499:Bayes Theorem; D002648:Child; D002675:Child, Preschool; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D009026:Mortality / Q000639:trends*; D009369:Neoplasms / Q000401:mortality* / Q000628:therapy*; D009517:New South Wales / Q000453:epidemiology; D011379:Prognosis; D012042:Registries / Q000706:statistics & numerical data*; D016019:Survival Analysis