Mortality modeling of early detection programs.
Consider a group of subjects who are offered an opportunity to receive a sequence of periodic special examinations for the purpose of diagnosing a chronic disease earlier relative to usual care. The mortality for the early detection group is to be compared with a group receiving usual care. Benefit is reflected in a potential reduction in mortality. This article develops a general probability model that can be used to predict cumulative mortality for each of these groups. The elements of the model assume (i) a four-state progressive disease model in which a subject may be in a disease-free state (or a disease state that cannot be detected), preclinical disease state (capable of being diagnosed by a special exam), clinical state (diagnosis by usual care), and a death state; (ii) age-dependent transitions into the states; (iii) age-dependent examination sensitivity; (iv) age-dependent sojourn time in each state; and (v) the distribution of disease stages on diagnosis conditional on modality of detection. The model may be used to (i) compare mortality rates for different screening schedules; (ii) explore potential benefit of subpopulations; and (iii) compare relative reductions in disease-specific mortality due to advances and dissemination of both treatment and early detection screening programs.
Lee
Sandra J
SJ
Harvard School of Public Health and the Dana-Farber Cancer Institute, Boston, Massachusetts 02115, USA. lee.sandra@jimmy.harvard.edu
Zelen
Marvin
M
D001699:Biometry / Q000379:methods; D002908:Chronic Disease / Q000401:mortality* / Q000517:prevention & control*; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D011159:Population Surveillance / Q000379:methods*; D016016:Proportional Hazards Models; D016019:Survival Analysis; D015996:Survival Rate