OBJECTIVES: Gliomas are a heterogenous group of primary brain tumors. The most common malignant brain tumor in adults is glioblastoma, characterized by poor prognosis and high mortality. Various treatments are available depending on clinical and pathological factors. This study aimed to review the literature on economic evaluations and health economic models related to gliomas.

METHODS: The systematic literature search was performed on 23rd of August 2023, covering Medline, Embase, Scopus, Cochrane Library and PROSPERO. Grey literature sources were also searched, and snowball searches were applied. Studies were eligible if they investigated any form of glioma, contained data on economic evaluations, had a geographical focus on Europe or North America and were written in English. The protocol was registered in PROSPERO (ID: CRD42023488181).

RESULTS: The review of 5503 records resulted in 48 included studies published from 2001, including 42 peer-reviewed publications, 4 ISPOR posters and 2 grey literature materials. 23 studies investigated patients with glioblastoma, 25 other types of gliomas. 29 included information about a health economic model, the remaining reported simple calculations of costs and benefits. A large variety of technologies were investigated including diagnostic interventions, surgery procedures, pharmacotherapies alone or in combination with radiotherapy and other technologies like Tumor Treating Fields. For economic modelling, various types were used, including decision-tree models (n=9), Markov cohort or partitioned-survival models (n=17), hybrid models (n=2), while in 1 case the model type was unclear. Cost-utility analysis was used in 19 studies, and 5 applied decreasing utility values over time for patients in progression to model the deteriorating quality of life.

CONCLUSIONS: A substantial and increasing amount of data is available on economic evaluations in the field of gliomas, and particularly on patients with glioblastoma. Several methodologies are applied for modelling to evaluate the cost and benefits of technologies used for diagnosis and treatment.