P61 Cost Utility Analysis of Circulating Tumour DNA Guided Adjuvant Chemotherapy in Stage II Colon Cancer

There is currently potential overuse of adjuvant chemotherapy (AC) in patients with stage II colon cancer (CC) given the uncertain survival benefit in unselected patients. A circulating tumour DNA (ctDNA) approach has the ability to improve patient selection for AC, defining patients who may benefit from treatment (ctDNA positive) and those who will not (ctDNA negative). This study aimed to estimate the health and economic impact of ctDNA-guided prescription of AC for stage II CC. A cost-utility analysis was performed comparing ctDNA-guided AC prescription for stage II CC to standard of care (SOC), where 22.6% of SOC patients received AC, all ctDNA-positive patients (8.7%) received AC and all ctDNA-negative patients (91.3%) did not. A third preference-sensitive ctDNA strategy was included where 6.8% of ctDNA-negative patients would receive AC to reflect potential non-compliance. A state-transition model was populated utilising a landmark cohort study investigating the prognostic value of ctDNA and clinical registries. The analysis employed an Australian payer perspective and lifetime horizon. Extensive scenario and probabilistic analyses quantified model uncertainty. Compared to SOC, the ctDNA and preference-sensitive ctDNA strategies increased quality-adjusted life years (QALYs) by 0.20 (95% confidence interval -0.40 to 0.81) and 0.19 (-0.40 to 0.78), and resulted in incremental costs of AUD - 4,215 (-17,651 to 9,216) and AUD - 2,450 (-15,472 to 10,570), respectively. ctDNA remained cost-effective at a willingness-to-pay of AUD 20,000 per QALY gained throughout most scenario analyses in which the proportion of ctDNA-positive patients cured by AC and compliance to a ctDNA negative test results were decreased. ctDNA-guided AC is a potentially cost-effective strategy to improve patient selection for adjuvant chemotherapy in resected stage II colon cancer. Expanding the analysis with results from ongoing randomised clinical studies will be important to reduce uncertainty in the model.