Regier, D.A., Pollard, S., McPhail, M. et al. A perspective on life-cycle health technology assessment and real-world evidence for precision oncology in Canada. npj Precis. Onc. 6, 76 (2022).
This important new article from CLEO is hot off the press (October 25, 2022) and was supported in part by ARCC, as well as Genome British Columbia/Genome Canada.
Decision-makers use evidence of effectiveness and value to understand what treatments should be offered to patients. Using cancer patients’ DNA to inform treatment is called precision oncology. Evidence to support precision oncology is difficult to generate. It can also be low quality. This means that decision-makers are often uncertain if precision oncology treatments work. This uncertainty is preventing timely access to new therapies.
In this article, we present a framework to create better evidence for precision oncology. Our approach is based on data collected in everyday patient care. This concept is called learning healthcare. Learning healthcare systems collect data, create evidence, and use that evidence to inform treatment decisions. We describe how our framework allows learning healthcare systems to provide patients with new treatments while they monitor how well those treatments work. Our framework helps decision-makers to understand whether to continue collecting evidence, to fund the new treatment, or to stop collecting evidence. The goal is to achieve timely patient access to precision oncology that improves population health and our understanding of value.