Estimation of sojourn time in chronic disease screening without data on interval cases

Tony H.H. Chen, H. S. Kuo, M. F. Yen, M. S. Lai, L. Tabar, S. W. Duffy

Research output: Contribution to journalArticlepeer-review

75 Citations (Scopus)


Estimation of the sojourn time on the preclinical detectable period in disease screening or transition rates for the natural history of chronic disease usually rely on interval cases (diagnosed between screens). However, to ascertain such cases might be difficult in developing countries due to incomplete registration systems and difficulties in follow-up. To overcome this problem, we propose three Markov models to estimate parameters without using interval cases. A three-state Markov model, a five-state Markov model related to regional lymph node spread, and a five-state Markov model pertaining to tumor size are applied to data on breast cancer screening in female relatives of breast cancer cases in Taiwan. Results based on a three- state Markov model give mean sojourn time (MST) 1.90 (95% CI: 1.18-4.86) years for this high-risk group. Validation of these models on the basis of data on breast cancer screening in the age groups 50-59 and 60-69 years from the Swedish Two-County Trial shows the estimates from a three-state Markov model that does not use interval cases are very close to those from previous Markov models taking interval cancers into account. For the five-state Markov model, a reparameterized procedure using auxiliary information on clinically detected cancers is performed to estimate relevant parameters. A good fit of internal and external validation demonstrates the feasibility of using these models to estimate parameters that have previously required interval cancers. This method can be applied to other screening data in which there are no data on interval cases.

Original languageEnglish
Pages (from-to)167-172
Number of pages6
Issue number1
Publication statusPublished - Mar 2000
Externally publishedYes


  • Breast cancer
  • Chronic disease
  • Interval cases
  • Markov model
  • Screening
  • Sojourn time

ASJC Scopus subject areas

  • General Immunology and Microbiology
  • Applied Mathematics
  • General Biochemistry,Genetics and Molecular Biology
  • General Agricultural and Biological Sciences
  • Statistics and Probability


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