Objective: Ovarian cancer is a leading cause of cancer-related deaths among women. Given the low prevalence of this disease, the effectiveness of screening strategies has not been established. We wished to estimate the clinical impact and cost-effectiveness of potential screening strategies for ovarian cancer using population-specific data.
Methods: A Markov state transition model to simulate the natural history of ovarian cancer in a cohort of women age 20 to 100. Age-specific incidence and mortality rates were obtained from SEER. Base-case characteristics of a potential screening test were sensitivity 85%, specificity 95%, and cost $50. Outcome measures were mortality reduction, lifetime number of false positive screening tests, positive predictive value, years of life saved (YLS), lifetime costs in US dollars, and incremental cost-effectiveness ratios (ICER, in cost/YLS).
Results: Model-predicted lifetime risk of ovarian cancer (1.38%), lifetime risk of death from ovarian cancer (0.95%), and stage distribution (stage I-19%; stage II-7%; stage III, IV, or unstaged - 74%) closely approximated SEER data. Annual screening resulted in 43% reduction in ovarian cancer mortality, with ICER of $73,469/YLS (base case) and $36,025/YLS (high-risk population) compared to no screening. In the base case, the average lifetime number of false positive tests is 1.06. Cost-effectiveness of screening is most sensitive to test frequency, specificity and cost.
Conclusions: Annual screening for ovarian cancer has the potential to be cost effective, particularly in high-risk populations. Clinically acceptable positive predictive values are achieved if specificity exceeds 99%. Mortality reduction above 50% may not be achievable without screening intervals less than 12 months.