TY - JOUR
T1 - A potential error in evaluating cancer screening
T2 - A comparison of 2 approaches for modeling underlying disease progression
AU - Goldie, Sue J.
AU - Kuntz, Karen M.
PY - 2003/5
Y1 - 2003/5
N2 - 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.
AB - 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.
KW - Cancer screening
KW - Markov models
KW - Model errors
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U2 - 10.1177/0272989X03023003005
DO - 10.1177/0272989X03023003005
M3 - Article
C2 - 12809321
AN - SCOPUS:0038814016
SN - 0272-989X
VL - 23
SP - 232
EP - 241
JO - Medical Decision Making
JF - Medical Decision Making
IS - 3
ER -