Implementation of whole genome sequencing in cancer management: modelling and sensitivity analysis using system...

Precision oncology using biomarkers and genomic testing facilitates individualised diagnosis and consequently treatment for cancer patients. Standard of Care is conducted through assays of biomarkers for treatment selection. However, Whole Genome Sequencing (WGS) provides excessively more information about actionable mutations and complex interventions. Despite its potentials in cancer management, WGS is restricted by its high cost and limited capacity. Implementing WGS is complex because it influences several elements of the care delivery and deals with the dynamic changes in supply, demand, technology, and cost. In this study, we use a System Dynamics (SD) model to evaluate WGS implementation. We also use the developed SD model to conduct sensitivity analysis to derive insights for decision-making on genomic testing scenarios. Various scenarios have been compared by the number of diagnosed patients and total cost. These scenarios have been created through alterations in WGS referral system, capacity, price, and willingness rate as well as testing time across different hospitals. The results showed that referring more patients for WGS will increase the number of diagnosed patients (by 30%), however it will impose more cost on the system (by 20%) due to higher cost of WGS. Therefore, investment strategies toward reducing cost of WGS as well as reimbursement policies can be beneficial to make WGS more economic and accessible. This study shows how the developed SD model can contribute to providing insights for policy makers in finding the optimal way for implementing WGS.