Empirical Assessments for Cost and Benefit of Cancer Screening with Multi-state Models for Semi-competing Risks Data

Music City Center 

Health-care policy makers are often interested in the cost-effectiveness of an intervention. The effectiveness is usually measured by quality adjusted life years, which is subject to informative censoring, and the costs, both of which are often assessed from large-scale observational studies and databases (e.g., claims data, large cohort studies) and are thus susceptible to confounding. There is considerably rich literature available to accommodate censoring and adjust for confounding factors. However, most cost-effectiveness studies are primarily concerned with the terminal event rather than the entire disease progression. Motivated by informing optimal initial screening age for colorectal cancer (CRC) through cost-effectiveness analysis, we provide a unified measure of cost-effectiveness with semi-competing risks and multistate modeling, which allows us to gain insights on benefit and cost at each stage of cancer progression. Unlike most existing causal inference works focusing on static interventions, we develop a causal framework and estimation procedure to evaluate cost-effectiveness as a function of time-varying screening strategy. These methods are justified theoretically and numerically using both simulation and the CRC data from the Women's Health Initiative observational study.