(untitled) (Global Journal of Sciences, 2025)
The combination of multi-criteria decision-making (MCDM) methods and fuzzy logic technique offers novel approaches to decision-making in the treatment planning of liver cancer; hepatocellular carcinoma (HCC), particularly the decision on how to propose the right therapeutic approach depending on multiple criteria. Since none of the treatment methods can provide fully satisfactory results for liver cancer when considering different patients, it is crucial to identify the optimal therapeutic method tailored for each individual, based on certain pertinent criteria. This study provides insight into the various factors that are likely to influence HCC pharmacological treatments. All the chosen drugs were assessed based on their effectiveness in meeting each of the criteria considered. To achieve this, we applied an MCDM-fuzzy hybrid model that combines both fuzzy logic and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) technique. We evaluated eight FDA-approved medications for HCC treatment alternatives. These drugs include, Cabozantinib, sorafenib, Lenvatinib, Atezolizumab, Tivantinib, Nivolumab and Pembrozumab. Similarly, based on the multiple criteria approach, five alternatives were adopted such as efficacy, cost, safety, drug development stage and side effects. The ranking result revealed that Sorafenib ranked the highest and Tivantinib ranked the least. The study offers a structured and data-driven approach in the classification of drugs which provides valuable insights for health practitioners and policy makers and HCC treatment optimization.