Estimation of natural history parameters of breast cancer based on non-randomized organized screening data: subsidiary analysis of effects of inter-screening interval, sensitivity, and attendance rate on reduction of advanced cancer.

Estimating the natural history parameters of breast cancer not only elucidates the disease progression but also make contributions to assessing the impact of inter-screening interval, sensitivity, and attendance rate on reducing advanced breast cancer. We applied three-state and five-state Markov models to data on a two-yearly routine mammography screening in Finland between 1988 and 2000. The mean sojourn time (MST) was computed from estimated transition parameters.

Evaluation of breast cancer service screening programme with a Bayesian approach: mortality analysis in a Finnish region.

Evaluation of long-term effectiveness of population-based breast cancer service screening program in a small geographic area may suffer from self-selection bias and small samples. Under a prospective cohort design with exposed and non-exposed groups classified by whether women attended the screen upon invitation, we proposed a Bayesian acyclic graphic model for correcting self-selection bias with or without incorporation of prior information derived from previous studies with an identical screening program in Sweden by chronological order and applied it to an organized breast cancer service screening program in Pirkanmaa center of Finland. The relative mortality rate of breast cancer was 0.