Effects of socioeconomic and geographic variations on survival for adult glioma in England and Wales.
BACKGROUND
To investigate the effects of SES and geographic variations on survival for adult patients with glioma, we analyzed data from 30489 patients from the Cancer Registry in England and Wales.


METHODS
Median survival and CSRs for 8 variables (age, sex, morphology, World Health Organization [WHO] grade, tumor site, SES, geographic regions, and periods of diagnosis) are calculated using the Kaplan-Meier method. Distributions among different variables are compared using chi(2) test. Cox regressions are performed for estimating HRs to death.


RESULTS
The median survival and the 1-, 5-, and 10-year CSR in this population are 0.42 years, 29.1%, 12.0%, and 7.7%, respectively. There is a gradient in SES from the south to the north (chi(2) test, P < .001) and a gradual increment in higher SES from the early to the recent period (chi(2) test, P < .001). Mono- and multivariate analyses reveal that all the 8 variables influenced the survival (P < .05). Age (HR, 1.04 per year from 15 years, P < .001), WHO grade (1.21 per grade from grade I, P < .001), and morphology (HR from 1.23 to 1.89, compared with ependymoma, P < .05) are the most influential factors. However, there are also independent effects from SES (HR, 1.03 per quintile of deprivation, P < .001) and geographic regions (HR, 1.10 for outside southern England; P < .001) on the survival.


CONCLUSIONS
Although age and tumor characteristics (morphology, WHO grade, tumor site) are well-known prognostic factors, SES and geographic variations also play a slight but significant role, and for more cost-effective allocation of health resources, alleviation on these 2 modifiable factors should be considered.
Tseng
Jen-Ho
JH
Department of Surgery, Division of Neurosurgery, National Taiwan University Hospital, Taipei 100, Taiwan.
Merchant
Edwin
E
Tseng
Ming-Yuan
MY
D000328:Adult; D017677:Age Distribution; D000367:Age Factors; D001932:Brain Neoplasms / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D003362:Cost-Benefit Analysis; D004739:England / Q000453:epidemiology; D004806:Ependymoma / Q000175:diagnosis / Q000453:epidemiology / Q000503:physiopathology; D005260:Female; D005843:Geography; D005910:Glioma / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009361:Neoplasm Invasiveness / Q000175:diagnosis / Q000503:physiopathology; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D011379:Prognosis; D012042:Registries / Q000706:statistics & numerical data; D040841:Resource Allocation / Q000639:trends; D017678:Sex Distribution; D012959:Socioeconomic Factors; D013222:State Medicine; D015996:Survival Rate; D014852:Wales / Q000453:epidemiology