Elucidating the spatially varying relation between cervical cancer and socio-economic conditions in England.

Background: Geographically weighted Poisson regression (GWPR) was applied to the relation between cervical cancer disease incidence rates in England and socio-economic deprivation, social status and family structure covariates. Local parameters were estimated which describe the spatial variation in the relations between incidence and socio-economic covariates.

Results: A global (stationary) regression model revealed a significant correlation between cervical cancer incidence rates and social status.

Tumour doubling times and the length bias in breast cancer screening programmes.

Screening for early detection of breast cancer is considered to be an important element of preventive medicine. In this paper, we use numerical simulations to examine the length bias in regular interval screening programmes, by computing the doubling times of breast cancer tumours detected through regular mammographies compared to self-detection. Our analysis shows that doubling times of tumours detected by a regular screening programme are longer than doubling times in the original whole population and considerably longer than those self-detected.