title: Risk-specific optimal cancer screening schedules: an application to breast cancer early detection.
abstract: The optimal schedules for breast cancer screening in terms of examination frequency and ages at examination are of practical interest. A decision-theoretic approach is explored to search for optimal cancer screening programs which should achieve maximum survival benefit while balancing the associated cost to the health care system. We propose a class of utility functions that account for costs associated with screening examinations and value of survival benefit under a non-stable disease model. We consider two different optimization criteria: optimize the number of screening examinations with equal screening intervals between exams but without a pre-fixed total cost; and optimize the ages at which screening should be given for a fixed total cost. We show that an optimal solution exists under each of the two frameworks. The proposed methods may consider women at different levels of risk for breast cancer so that the optimal screening strategies will be tailored according to a woman's risk of developing the disease. Results of a numerical study are presented and the proposed models are illustrated with various data inputs. We also use the data inputs from the Health Insurance Plan of New York (HIP) and Canadian National Breast Screening Study (CNBSS) to illustrate the proposed models and to compare the utility values between the optimal schedules and the actual schedules in the HIP and CNBSS trials. Here, the utility is defined as the difference in cure rates between cases found at screening examinations and cases found between screening examinations while accounting for the cost of examinations, under a given screening schedule.
authors.affiliation: Division of Biostatistics, Dan L. Duncan Cancer Center at Baylor College of Medicine, One Baylor Plaza, BCM600, Houston, TX 77030, USA.
authors.forename: Charlotte Hsieh
authors.initials: CH
authors.lastname: Ahern
authors.forename: Yi
authors.initials: Y
authors.lastname: Cheng
authors.forename: Yu
authors.initials: Y
authors.lastname: Shen