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, Matti Hakama, Ahti Anttila, Amy Ming Fang Yen, Nea Malila, Tytti Sarkeala, Anssi Auvinen, Sherry Yueh Hsia Chiu, Hsiu Hsi Chen

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)553-566
Number of pages14
JournalBreast Cancer Research and Treatment
Volume122
Issue number2
DOIs
Publication statusPublished - Jul 2010

Keywords

  • Attendance rate.
  • Breast cancer service screening
  • Inter-screening interval
  • Markov model
  • Natural history
  • Sensitivity

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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