Related Experiment Video
Updated: May 23, 2025
Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
Published on: February 6, 2019
Adaptable framework for cost-analyses in radiotherapy: Application to the cost of proton versus photon therapy for
Bradley M Sugden1, Willem J A Witlox2, Bram L T Ramaekers2
1Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Centre+ (MUMC+), Maastricht, The Netherlands; Department of Radiation Oncology (Maastro Clinic), Maastricht University Medical Centre+ (MUMC+), GROW School on Oncology and Developmental Biology, Maastricht, The Netherlands.
Background/Purpose:
Proton radiation-therapy (PrT) may provide clinical benefit for lung cancer compared to photon radiation-therapy (PhT), however is more costly. Literature reporting costs for PrT, PhT, and comparisons thereof, particularly from a societal perspective, are scarce. This study aims to provide an adaptable framework to estimate PrT/PhT costs, demonstrated through application to lung cancer, from societal and healthcare perspectives.
Methods:
Dutch Costing Guidelines were followed to estimate costs from first referral to end of treatment. A parallel base-case was conducted whereby centre-specific inputs replaced general input parameters. Costs were calculated probabilistically using Monte Carlo simulations (10,000 iterations) and separated into three categories: healthcare (subdivided: personnel, non-personnel), patient/family, and costs in other sectors. Direct healthcare personnel costs were estimated using time-driven activity-based costing, allowing separation of non-fraction-dependant costs. Further sensitivity/scenario analyses were explored.
Results:
Fixed costs (guideline[centre-specific] analyses mean) from a societal perspective were €11,208[€12,299] for PrT and €9,651[€10,977] for PhT. Variable costs per fraction were €932[€798] for PrT and €265[€265] for PhT. Total cost ratio for PrT to PhT was 2.00[1.74] for 20 fraction schedules and 2.23[1.91] for 30 fractions. The greatest incremental cost driver category for PrT versus PhT was non-(direct)personnel healthcare costs (overheads, capital outlays).
Conclusion:
An adaptable framework for probabilistic cost-analyses was developed. Results highlight cost disparities between PrT and PhT and serves to inform future cost-effectiveness analyses. Scenarios reveal potential for clinical experience and increased capacity to narrow differences. Parallel base-case analyses highlight cost disparities arising when utilising generic vs centre-specific inputs, and potential outcome differences between centres.
