OBJECTIVES: Cost-effectiveness modeling of MCED should account for variations in curative potential by cancer stage. Mixture cure models are widely used to extrapolate long-term survival in heterogeneous oncological populations. This work evaluates such methodology in the context of MCED modeling and the cost implications.

METHODS: Cure fractions (proportion of patients cured of disease) by cancer type and stage were determined utilizing mixture cure models and SEER relative survival. We estimated uncured survival based on CDC life tables and SEER observed survival for ages 50-74 and U.S. demographic distributions across many cancer types targeted by MCED tests. We created a scenario to derive the potential economic impact of cure fractions when modeling MCED by tabulating 10-year cancer-attributable costs (initial, continuing, and end-of-life) across a static diagnosed population. The cured population included five years of continuing costs in addition to initial costs, while the uncured population also included end-of-life and continuing costs for the remaining duration of survival. Without cure fraction, all costs were tabulated as uncured using SEER observed survival.

RESULTS: Cure fractions varied by cancer stage and type – greater for earlier stages (61.7% local mean versus 2.7% distant mean) and cancers with higher 5-year survival (93.0% for local breast versus 12.9% for local liver). The example scenario showed reductions in cancer-attributable costs incorporating cure fraction compared to no cure fraction: 26.5%, 9.45%, and 0.5% for local, regional, and distant, respectively. All cancers showed cost reductions after implementing cure fractions, ranging from 39.7% (kidney) to 9.1% (liver).

CONCLUSIONS: Detecting cancers at earlier stages increases the fraction of the population that may be cured. MCED health economic modeling can use mixture cure models to estimate different costs between cured and uncured populations. Cured cost reduction will vary by cancer type and stage and is correlated to screening effectiveness and cancer aggressiveness.