The Feasibility of Combining Cost-Effectiveness, Bayesian Meta-Analysis and Meta-Regression Techniques When Evaluating Melanoma Treatment Methods

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Background: Melanoma treatment encompasses surgery, chemotherapy, radiotherapy, immunotherapy, and targeted therapy. Despite declining mortality due to therapeutic advances, increasing incidence underscores the growing importance of cost-effectiveness analyses. The integration of cost-effectiveness evaluation with Bayesian meta-analysis and meta-regression may enhance the synthesis of heterogeneous evidence. Methods: A systematic literature review was conducted to identify studies reporting quality-adjusted life years (QALYs) and direct treatment costs for melanoma in PubMed, MEDLINE, and MEDLINE Ultimate. Bayesian meta-analysis with non-informative priors was applied to derive pooled estimates and quantify uncertainty. Results: A total of 272 studies were identified, of which only a limited subset met the inclusion criteria. The studies exhibited substantial heterogeneity in treatments, populations, time horizons, perspectives, and costs. Meta-analysis based on the effects provided in one study showed that chemotherapy demonstrated lower effectiveness, as measured by QALYs, compared with treatment sequences such as Anti-PD1 → Bi-TT and Bi-TT → Anti-PD1 in both BRAF-mutated and wild-type populations. Lower costs were associated with chemotherapy, ipilimumab, and Anti-PD1 relative to combination and sequential regimens. Meta-analysis based on the effects provided in another study showed that treatment costs increased with advancing disease stage (≥IIIA) and exhibited greater variability in advanced melanoma. Conclusion: The combined methodological approach enhances the robustness and comparability of estimates. The observed variability in both clinical effectiveness and costs, across treatment strategies and disease stages, has important implications for healthcare decision-making and resource allocation.

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