NODG-08 A MARKOV MODEL-BASED ASSESSMENT OF A COMPREHENSIVE CANCER CENTER’S EFFECT ON PATIENT NEURO-ONCOLOGY STATE TRANSITIONS AND COST IMPLICATIONS IN GHANA

Abstract Introduction Central nervous system cancers remain a significant challenge in Africa, with limited access to specialized care. This study sought to evaluate the cost-effectiveness of establishing a national comprehensive cancer center (CCC) in Ghana. Methods This cost-effectiveness analysis employed a Markov model using Amua to simulate the progression of neuro-oncology patients through eight health states over 10 years. Transition probabilities between the health states and costs were derived from peer-reviewed literature, the Institute for Health Metrics and Evaluation Global Burden of Disease, and expert opinion. A hypothetical cohort of 1,000 patients was used to simulate the outcomes and costs associated with the comprehensive cancer center (CCC) strategy versus a counterfactual scenario without a CCC. A 3% discount rate was applied from the first cycle to account for the time preference of costs and benefits. Half-cycle correction was used to adjust for transitions occurring mid-cycle. Additionally, a Monte Carlo simulation was employed to incorporate stochastic variability and provide robust estimates of outcomes and costs. Results The CCC strategy incurred higher cumulative costs compared to the counterfactual (USD 83,179,950 vs. USD 79,622,900). Discounted cumulative costs were equally higher for the CCC (USD 72,693,723 vs. USD 69,674,729). However, the CCC strategy had a higher number of patients in treatment (9 vs. 1), post-treatment (2 vs. 1), and event-free (48 vs. 1) states at the end of the 10 cycles (Figure 1 a and b). Conclusion Although the CCC model had higher costs, it equally had better management and outcomes. This finding suggests that investing in a CCC in Ghana, may lead to long-term benefits that justify the initial upfront investment.