Implementing low-dose computed tomography screening for lung cancer in Canada: implications of alternative at-risk populations, screening frequency, and duration

W.K. Evans, W.M. Flanagan, A.B. Miller, J.R. Goffin, S. Memon, N. Fitzgerald, M.C. Wolfson



Low-dose computed tomography (LDCT) screening has been shown to reduce mortality from lung cancer; however, the optimal screening duration and “at risk” population are not known.


The Cancer Risk Management Model developed by Statistics Canada for the Canadian Partnership Against Cancer includes a lung screening module based on data from the U.S. National Lung Screening Trial (NLST). The base-case scenario reproduces NLST outcomes with high fidelity. The impact in Canada of annual screening on the number of incident cases and life-years gained, with a wider range of age and smoking history eligibility criteria and varied participation rates, was modelled to show the magnitude of clinical benefit nationally and by province. Life-years gained, costs (discounted and undiscounted), and resource requirements were also estimated.


In 2014, 1.4 million Canadians were eligible for screening according to NLST criteria. Over 10 years, screening would detect 12,500 more lung cancers than the expected 268,300 and would gain 9200 life-years. The computed tomography imaging requirement of 24,000–30,000 at program initiation would rise to between 87,000 and 113,000 by the 5th year of an annual NLST-like screening program. Costs would increase from approximately $75 million to $128 million at 10 years, and the cumulative cost nationally over 10 years would approach $1 billion, partially offset by a reduction in the costs of managing advanced lung cancer.


Modelling various ways in which LDCT might be implemented provides decision-makers with estimates of the effect on clinical benefit and on resource needs that clinical trial results are unable to provide.


Lung cancer; screening; low-dose computed tomography; modelling; NLST; Canada

Full Text:



Copyright © 2019 Multimed Inc.
ISSN: 1198-0052 (Print) ISSN: 1718-7729 (Online)