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

Jenny Chia-Yun Wu (1) , Matti Hakama (1, 2) , Ahti Anttila (2) , Amy Ming-Fang Yen (3) , Nea Malila (1, 2) , Tytti Sarkeala (1) , Anssi Auvinen (1) , Sherry Yueh-Hsia Chiu (1) , Hsiu-Hsi Chen (1, 4)

1 Tampere School of Public Health
2 Mass Screening Registry
3 Division of Biostatistics, College of Public Health
4 Division of Biostatistics, College of Public Health

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. Computer simulation was implemented to examine the effect of inter-screening interval, sensitivity, and attendance rate on reducing advanced breast cancers. In three-state model, the MST was 2.02 years, and the sensitivity for detecting preclinical breast cancer was 84.83%. In five-state model, the MST was 2.21 years for localized tumor and 0.82 year for non-localized tumor. Annual, biennial, and triennial screening programs can reduce 53, 37, and 28% of advanced cancer. The effectiveness of intensive screening with poor attendance is the same as that of infrequent screening with high attendance rate. We demonstrated how to estimate the natural history parameters using a service screening program and applied these parameters to assess the impact of inter-screening interval, sensitivity, and attendance rate on reducing advanced cancer. The proposed method makes contribution to further cost-effectiveness analysis. However, these findings had better be validated by using a further long-term follow-up data.

Mots clés: Breast cancer service screening; Markov model; Natural history; Sensitivity; Inter-screening interval; Attendance rate

Jenny Chia-Yun Wu, Matti Hakama, Ahti Anttila, Amy Ming-Fang Yen, Nea Malila, et al.. 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. Breast Cancer Research and Treatment, 2010, 122 (2), pp.553-566. ⟨10.1007/s10549-009-0701-x⟩. ⟨hal-00535429⟩