Clarifying differences in natural history between models of screening: The case of colorectal cancer

Marjolein Van Ballegooijen, Carolyn M. Rutter, Amy B. Knudsen, Ann G. Zauber, James E. Savarino, Iris Lansdorp-Vogelaar, Rob Boer, Eric J. Feuer, J. Dik F. Habbema, Karen M. Kuntz

Research output: Contribution to journalReview articlepeer-review

42 Scopus citations


Background. Microsimulation models are important decision support tools for screening. However, their complexity makes them difficult to understand and limits realization of their full potential. Therefore, it is important to develop documentation that clarifies their structure and assumptions. The authors demonstrate this problem and explore a solution for natural history using 3 independently developed colorectal cancer screening models. Methods. The authors first project effectiveness and cost-effectiveness of colonoscopy screening for the 3 models (CRC-SPIN, SimCRC, and MISCAN). Next, they provide a conventional presentation of each model, including information on structure and parameter values. Finally, they report the simulated reduction in clinical cancer incidence following a one-time complete removal of adenomas and preclinical cancers for each model. They call this new measure the maximum clinical incidence reduction (MCLIR). Results. Projected effectiveness varies widely across models. For example, estimated mortality reduction for colonoscopy screening every 10 years from age 50 to 80 years, with surveillance in adenoma patients, ranges from 65% to 92%. Given only conventional information, it is difficult to explain these differences, largely because differences in structure make parameter values incomparable. In contrast, the MCLIR clearly shows the impact of model differences on the key feature of natural history, the dwell time of preclinical disease. Dwell times vary from 8 to 25 years across models and help explain differences in projected screening effectiveness. Conclusions. The authors propose a new measure, the MCLIR, which summarizes the implications for predicted screening effectiveness of differences in natural history assumptions. Including the MCLIR in the standard description of a screening model would improve the transparency of these models.

Original languageEnglish (US)
Pages (from-to)540-549
Number of pages10
JournalMedical Decision Making
Issue number4
StatePublished - Jul 2011

Bibliographical note

Funding Information:
This work was supported by the National Institutes of Health/National Cancer Institute (U01-CA-088204, U01-CA-097427, U01-CA-097426, and U01-CA-115953).


  • colorectal cancer
  • microsimulation
  • natural history
  • screening models
  • standard model output


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