OBJECTIVES: This study systematically reviews applications of patient-level simulation (PLS) models in cancer care. The aim was to describe the main application areas, identify relevant model structures, assess reporting quality and critically discuss the potential contribution of PLS models in cancer care.

METHODS: A systematic literature search was completed in Web of Science, PubMed, EMBASE and EconLit. Reasons underlying the use of PLS models were identified with a conventional inductive content analysis and reporting quality was assessed with an 18-item checklist based on the ISPOR-SMDM guidelines.

RESULTS: A total of 133 papers met the predefined eligibility criteria and an increase in the number of publications was witnessed over time. Most studies used state-transition microsimulation (49.25%) or discrete event simulation (48.51%) and two application areas could be discerned, namely disease progression modelling (DPM) (78.36%) and health and care systems operation (HCSO) (21.64%). In the DPM domain, the use of PLS models was mainly motivated by the need to represent patient heterogeneity and history. In the HSCO domain, PLS models were used to better understand and improve cancer care delivery. Average reporting quality was 65.2% and did not improve over time.

CONCLUSIONS: PLS models can be used to both simulate the progression of cancer as to model cancer care delivery and the use of these models is increasing. In the DPM domain more direct comparisons with cohort models are required to establish the relative advantages of PLS models and in the HSCO domain the application of these models in clinical practice needs to be systematically assessed. Furthermore, adherence to the ISPOR-SMDM guidelines should be improved.