Biometrika · 1969 · 409 citations · 4 references
MedicineChronic Disease PreventionPreventive MedicineDisease PreventionEarly DetectionStochastic ModelingChronic DiseaseChronic Disease EpidemiologyDisease Progression ModelingMarkov ModelingPopulation ScreeningScreeningDisease Detection TimingDisease Progression TimingDisease ScreeningEarly DiagnosisEarly Disease ScreeningEarly ScreeningLead TimeStochastic Disease Models
Chronic disease is assumed to progress from a pre‑clinical to a clinical state, and early detection programmes can identify disease in the pre‑clinical state, potentially providing benefit proportional to the lead time gained. The study develops a stochastic model for early detection programmes to estimate mean lead time as a function of observable variables. The authors also investigate a non‑progressive disease model in which pre‑clinical individuals may not progress to the clinical state.
It is assumed that a chronic disease progresses from a pre-clinical state to a clinical state. If an individual, having pre-clinical disease, participates in an early detection programme, the disease may be detected in the pre-clinical state. The potential benefit of a screening programme is related to the lead time gained by early diagnosis. A stochastic model is developed for early detection programmes which leads to an estimate of the mean lead time as a function of observable variables. An investigation is also made of a non-progressive disease model in which individuals in a pre-clinical state may not necessarily advance to the clinical state.
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<i>The Theory of Stochastic Processes</i>
D. R. Cox, H. D. Miller, George H. Weiss et al. · Physics Today · 1966 · 3.4K citations
George B. Hutchison, Sam Shapiro · JNCI Journal of the National Cancer Institute · 1968 · 120 citations