OBJECTIVES: Precision cancer medicine (PCM) relies on resource-intensive comprehensive genomic profiling (CGP) based on next-generation sequencing. Detailed information on resource use related to CGP can inform hospital budgeting, resource input values in cost-effectiveness analysis, and highlight capacity bottlenecks. We aimed to conduct a micro-costing study of CGP for PCM in Norway within the national Infrastructure for Precision Diagnostics (InPreD) and IMPRESS-Norway clinical trial (EudraCT: 2020-004414-35).

METHODS: We first reviewed existing micro-costing studies related to CGP to develop a costing framework. We conducted site visits and discussions with associated staff to map the diagnostic pathway, and subsequently developed a costing model in Excel. Based on the site visits, discussions, and available information about InPreD, we identified and measured relevant cost components. We compared our results to previously conducted costing studies to identify differences in cost categories and level of detail.

RESULTS: Consumables were the most impactful cost category in most of the 11 micro-costing studies reviewed. Additionally, we identified the following costing categories for our study: personnel, equipment, software, and overhead. We mapped the diagnostic pathway into 8 steps over 4 weeks, including subject recruitment and data storage, which were often neglected in previous studies. InPreD currently allows for processing of 24 patient samples per week across 4 test centers in Norway. Costs per sample are highest for small sample sizes. However, higher capacities could increase both total variable and total step-fixed costs, for instance additional staff for sample analysis.

CONCLUSIONS: Our study presents a detailed costing framework and provides insight into potential constraints for higher test capacities. Next steps involve valuing input factors using Norwegian fee schedules, wage rates and price lists for equipment and machines obtained from the hospital. Further research could then extend our costing model to a generalized costing approach, especially to facilitate cost-effectiveness analyses of CGP.