Modern radiotherapy modalities have improved treatment precision and clinical effectiveness, but the economic evidence informing their adoption is heterogeneous. Published economic evaluations vary widely in costing methods, data sources, analytic designs (trial-based, real-world/observational and decision-analytic modelling), perspectives and treatment of uncertainty. This protocol describes a systematic mapping review designed to characterise that peer-reviewed evidence base and identify methodological gaps relevant to health technology assessment and policy-making.
The review has three primary aims:
To systematically catalogue published, peer-reviewed economic evaluations of modern radiotherapy and the methodological approaches they use.
To identify methodological trends across the literature, including the uptake and implementation of value of information analysis.
To highlight evidence gaps by tumour type, geographical region and methodological approach.
Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines, the authors searched major bibliographic databases for economic evaluations of radiotherapy published from 2005 onward. Databases searched included PubMed (MEDLINE), Embase, Scopus, Web of Science Core Collection and EconLit. The initial search date was 24 February 2026, and a planned search update will occur before synthesis. The source reports that study selection is ongoing; extraction and quality appraisal in duplicate have not been completed, and no study results are presented in the protocol.
Study selection procedures are ongoing according to the protocol. Methodological information to be extracted from included studies is specified and includes:
Model structure (for example, Markov model).
Analytical perspective (for example, healthcare payer).
Time horizon of the analysis.
Costing approach (for example, diagnosis-related group (DRG)-based methods).
Utility measurement instruments (for example, EQ-5D).
The methods used to assess uncertainty will be mapped across all eligible studies. The protocol indicates that extraction and quality appraisal will be performed in duplicate, but at the time of reporting these steps had not yet been undertaken.
Reporting completeness, methodological limitations and uncertainty will be appraised as three separate dimensions using established checklists and frameworks. The protocol specifies the following tools:
CHEERS 2022 checklist to appraise reporting completeness.
ECOBIAS (Bias in Economic Evaluation) checklist to assess potential bias in economic evaluations.
TRUST (TRansparent Uncertainty ASsessmenT) framework to evaluate how uncertainty is considered and communicated.
These instruments will be applied descriptively rather than combined into a single composite quality score. The protocol further clarifies that the ECOBIAS checklist and the TRUST framework will be applied only to decision-analytic model–based evaluations, whereas uncertainty mapping will be conducted across all study designs.
Given the anticipated heterogeneity of methods and outcomes, no meta-analysis is planned. Instead, findings will be synthesised descriptively and presented as an evidence gap map. Pre-specified visualisations include heat maps and bubble plots to display distributions of methodological characteristics across studies.
Additionally, a conceptual co-occurrence network will be constructed to show how radiotherapy modalities, tumour sites and economic characteristics cluster across the literature. Network analysis will be conducted in R, with visualisation produced using VOSviewer. The protocol indicates that final synthesis will reflect methodological trends and geographic and tumour-site gaps, but the source does not report synthesis results.
This review uses data from previously published studies and therefore does not require ethical approval. The authors plan to disseminate results through peer-reviewed publications, conference presentations and open-access release of data extraction files and visual maps via the Open Science Framework (OSF).
The protocol was prospectively registered in the OSF Registries. The source reports a registration date of 9 February 2026 and provides a DOI for the registry entry. No additional registration details or results are reported in the source.