A Potential Error in Evaluating Cancer Screening: A Comparison of 2 Approaches for Modeling Underlying Disease Progression

Sue J. Goldie and Karen M. Kuntz

Medical Decision Making, 2003, vol. 23, issue 3, 232-241

Abstract: Background. Evaluating cancer screening often requires modeling the underlying disease process and not observed disease, particularly in the absence of direct evidence linking screening to a survival benefit. Methods. To illustrate a potential error in modeling disease progression among healthy persons with a history of a precancerous lesion, we constructed 2 models with 4 basic health states (disease free, presence of a precancerous lesion, presence of cancer, dead), calibrated to predict the same 10-year cancer incidence. We assumed a homogeneous cohort enters each model free of disease, the probability of developing a precancerous lesion was greater for patients with a history of a prior lesion, and the screening test was perfect and riskless. In one model, we assigned a higher transition probability from a precancerous lesion to cancer in those with a history of a previously removed lesion; in the other, we assumed it was equal to those with no history. Results. Using the 1st model, life expectancy without screening was 2.4 months longer than with screening. This error did not occur using the 2nd model, in which the transition from precancerous lesions to cancer was not conditional on a history of a lesion. This modeling error's magnitude was examined under a variety of assumptions. Conclusions. We have identified an important error to avoid when modeling the underlying disease process in evaluating screening programs for cancers associated with precancerous states.

Date: 2003
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X03023003005 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:23:y:2003:i:3:p:232-241

DOI: 10.1177/0272989X03023003005

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().