Optimal summary of information in longitudinal CA125 measurements for efficient ovarian cancer screening

Ovarian cancer mortality rates have changed little over 30 years despite therapeutic advances. Given the large proportion of cases discovered in late stages and consequent poor prognosis, and the excellent prognosis if discovered in early stages, screening is an appealing approach to investigate reducing ovarian cancer mortality, Due to the large scale of screening programs end the low incidence of ovarian cancer, it is paramount that the screening strategy is as efficient as possible. CA125 is a marker for ovarian cancer that shows promise in detecting most ovarian cancers preclinically. However, its efficiency could be substantially improved if longitudinal CA125 values were taken into account in the screening program, We provide a detailed description, with minimal mathematical notation, of a systematic statistical calculation to optimally summarize the information in longitudinal CA125 values. Based on this calculation we describe a strategy, called the risk of ovarian cancer algorithm (ROCA), which implements an efficient approach to screening for ovarian cancer based on longitudinal CA125 measurements.