Literature DB >> 27330355

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

W K Evans1, W M Flanagan2, A B Miller3, J R Goffin1, S Memon4, N Fitzgerald4, M C Wolfson5.   

Abstract

BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.

Entities:  

Keywords:  Canada; Lung cancer; low-dose computed tomography; modelling; nlst; screening

Year:  2016        PMID: 27330355      PMCID: PMC4900838          DOI: 10.3747/co.23.2988

Source DB:  PubMed          Journal:  Curr Oncol        ISSN: 1198-0052            Impact factor:   3.677


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