OBJECTIVES: To provide an overview on published decision-analytic models evaluating various treatment strategies in chronic myeloid leukemia (CML). We sought to describe and analyze the structural and methodological approaches used and to derive recommendations for future CML models. METHODS: We performed a systematic literature review in electronic databases (Medline/PreMedline, EconLit, EMBASE, and others) to identify published studies evaluating CML treatment strategies using mathematical decision models. The models were required to compare different treatment strategies and to comprise relevant clinical health outcomes such as life-years gained or QALYs over a defined time horizon and population. We used standardized forms for data extraction, description of study design, methodological framework, and data sources. RESULTS: We identified 14 different decision-analytic modeling studies among which 13 included economic evaluations. The modeling approaches varied substantially and comprised decision trees, Markov models, Monte Carlo simulations, and mathematical equations. Time horizons ranged from two years to lifetime. Health outcomes included survival, life expectancy, and QALYs. Compared treatment strategies comprised bone or blood marrow transplantation, conventional chemotherapy, interferon-alpha, and first generation tyrosine kinase inhibitor (TKI) imatinib. None of the models evaluated comprehensive personalized medicine strategies or second generation TKI (e.g., nilotinib, dasatinib). Only few models were validated using independent data. CONCLUSIONS: We found several well-designed models for different CML treatment strategies. However, the quality of reporting varied substantially. We recommend that future models should include novel treatment options, subgroup evaluations for a more personalized decision making, and validation using independent data. Already available models with a short time horizon could be up-dated with new survival data.