e21508 Background: Compared to single-gene BRAF testing to guide targeted treatment for advanced melanoma, multi-gene panels can identify additional gene mutations with known therapeutic or prognostic relevance. No randomized control trials of multi-gene panel sequencing have been completed in advanced melanoma. This study determined the population-level cost-effectiveness of multi-gene panel sequencing compared to single-gene BRAF testing for advanced melanoma. Methods: Our population-based retrospective study emulated a hypothetical pragmatic trial using comprehensive patient-level clinical and health administrative data between September 2016 and December 2018 from British Columbia, Canada. To emulate random treatment assignment, we 1:1 matched multi-gene panel patients to contemporaneous controls using a machine learning approach that maximized balance on 15 covariates. Following matching, we estimated mean three-year survival time and costs (2021 CAD), and calculated incremental net monetary benefit (INMB) for life-years gained (LYG) at $100,000/LYG using inverse probability of censoring weighted linear regression and nonparametric bootstrapping. Besides an intention-to-treat (ITT) effect, we also estimated the per-protocol (PP) effect of initiating treatment within 90 days of receiving test results additionally using inverse probability of treatment weights. We also estimated overall survival using Weibull regression and Kaplan-Meier (KM) survival analysis. Results: We matched 147 patients receiving multi-gene panel sequencing to controls, achieving good balance for all included covariates. ITT mean incremental costs were $19,541 (95%CI: -$18,939, $77,396) and mean incremental LYG were 0.22 (95%CI: -0.06, 0.50). We did not find statistically significant different differences in overall survival using the KM (P = 0.11) and Weibull regression (HR: 0.73 [95%CI: 0.51-1.03]) survival analysis in the ITT analysis. PP incremental costs were $36,367 (95%CI: -$6,653, $120,216) and incremental LYG were 0.56 (95%CI: 0.39, 1.24), with corresponding differences in overall survival using KM (P = 0.02) and Weibull regression (HR: 0.56 [95%CI: 0.36-0.87]) survival analysis. The probability of multi-gene panel sequencing being cost-effective at $100,000/LYG was 54.9% in the ITT analysis and 64.5% in the PP analysis. Conclusions: We found the cost-effectiveness of multi-gene panel sequencing to be evenly poised, with estimates favouring multi-gene panel sequencing with respect to overall survival and cost-effectiveness when accounting for probability of treatment initiation. This real-world evidence generated using randomized trial design principles can support jurisdictions’ deliberations on the reimbursement of precision oncology interventions.