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Statistical models for cancer screening

journal contribution
posted on 1995-03-01, 00:00 authored by Christopher StevensonChristopher Stevenson
This paper reviews the application of statistical models to planning and evaluating cancer screening programmes. Models used to analyse screening strategies can be classified as either surface models, which consider only those events which can be directly observed such as disease incidence, prevalence or mortality, or deep models, which incorporate hypotheses about the disease process that generates the observed events. This paper focuses on the latter type. These can be further classified as analytic models, which use a model of the disease to derive direct estimates of characteristics of the screening procedure and its consequent benefits, and simulation models, which use the disease model to simulate the course of the disease in a hypothetical population with and without screening and derive measures of the benefit of screening from the simulation outcomes. The main approaches to each type of model are described and an overview given of their historical development and strengths and weaknesses. A brief review of fitting and validating such models is given and finally a discussion of the current state of, and likely future trends in, cancer screening models is presented.

History

Journal

Statistical methods in medical research

Volume

4

Issue

1

Pagination

18 - 32

Publisher

Sage Publications

Location

London, England

ISSN

0962-2802

eISSN

1477-0334

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

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