Abstract
OBJECTIVE: Through the conduct of an individual-based intervention study, the main purpose of this project was to build and evaluate the required infrastructure that may enable routine practice of precision cancer medicine in the public health services of Norway, including modelling of costs. METHODS: An eligible patient had end-stage metastatic disease from a solid tumour. Metastatic tissue was analysed by DNA sequencing, using a 50-gene panel and a study-generated pipeline for analysis of sequence data, supplemented with fluorescence in situ hybridisation to cover relevant biomarkers. Cost estimations compared best supportive care, biomarker-agnostic treatment with a molecularly targeted agent and biomarker-based treatment with such a drug. These included costs for medication, outpatient clinic visits, admission from adverse events and the biomarker-based procedures. RESULTS: The diagnostic procedures, which comprised sampling of metastatic tissue, mutation analysis and data interpretation at the Molecular Tumor Board before integration with clinical data at the Clinical Tumor Board, were completed in median 18 (8-39) days for the 22 study patients. The 23 invasive procedures (12 from liver, 6 from lung, 5 from other sites) caused a single adverse event (pneumothorax). Per patient, 0-5 mutations were detected in metastatic tumours; however, no actionable target case was identified for the current single-agent therapy approach. Based on the cost modelling, the biomarker-based approach was 2.5-fold more costly than best supportive care and 2.5-fold less costly than the biomarker-agnostic option. CONCLUSIONS: The first project phase established a comprehensive diagnostic infrastructure for precision cancer medicine, which enabled expedite and safe mutation profiling of metastatic tumours and data interpretation at multidisciplinary tumour boards for patients with end-stage cancer. Furthermore, it prepared for protocol amendments, recently approved by the designated authorities for the second study phase, allowing more comprehensive mutation analysis and opportunities to define therapy targets.