Scheduling Periodic Examinations for the Early Detection of Disease: Applications to Breast Cancer

Abstract

This article develops and extends previous investigations on stochastic models for selecting examination schedules targeted at earlier diagnosis of chronic diseases. The general aim is to provide guidelines for public health programs in the choice of examination schedules. The main features of such schedules are the initial age to begin a scheduled examination program, the intervals between subsequent examinations, and the number of examinations. Our basic model consists of three health states: a disease-free or nondetectable state; a preclinical state, in which an individual has disease but is asymptomatic and is unaware of it; and a clinical state in which the disease has been diagnosed by routine methods. The aim of early detection programs is to identify individuals in a preclinical local state, which may result in higher cure rates or longer survival. We introduce two basic ideas that either individually or together can lead to satisfactory examinations schedules. The threshold method constructs examination schedules so that the probability of an individual being in the preclinical state is always bounded by a preselected value. The concept of schedule sensitivity is the ratio of the expected number of cases diagnosed on scheduled examinations to the expectation of the total number of cases. Combining the threshold and schedule sensitivity methods enables an assessment of the trade-offs with regard to the initial age at examination and cost per case found. All of these methods are extended to high-risk populations. The schedule sensitivity, cost per case diagnosed on a scheduled exam, and the total cost can be calculated for any early detection program. This enables comparisons of different strategies. We illustrate the applicability of our methods to scheduling examinations for female breast cancer.

Key Words:

• Periodic screening.