BACKGROUND: Survival rates in @entity2 in England are significantly lower than in many similar countries. A range of Be Clear on Cancer (BCOC) campaigns have been conducted targeting @entity2 and found to improve the proportion of diagnoses at the early stage of disease. This paper considers the cost-effectiveness of such campaigns, evaluating the effect of both the regional and national BCOC campaigns on the stage distribution of @entity1149 ( @entity1149 ) at diagnosis. METHODS: A natural history model of @entity1149 was developed using incidence data, data elicited from clinical experts and model calibration techniques. This structure is used to consider the lifetime cost and quality-adjusted survival implications of the early awareness campaigns. Incremental cost-effectiveness ratios (ICERs) in terms of additional costs per quality-adjusted life-years (QALYs) gained are presented. Two scenario analyses were conducted to investigate the role of changes in the 'worried-well' population and the route of diagnosis that might occur as a result of the campaigns. RESULTS: The base-case theoretical model found the regional and national early awareness campaigns to be associated with QALY gains of 289 and 178 QALYs and ICERs of   13   660 and   18   173 per QALY gained, respectively. The scenarios found that increases in the 'worried-well' population may impact the cost-effectiveness conclusions. CONCLUSIONS: Subject to the available evidence, the analysis suggests that early awareness campaigns in @entity2 have the potential to be cost-effective. However, significant additional research is required to address many of the limitations of this study. In addition, the estimated natural history model presents previously unavailable estimates of the prevalence and rate of disease progression in the undiagnosed population.

Modelling the cost-effectiveness of public awareness campaigns for the early detection of XXXX .

@entity1149 :: ('MESH:D002289', 'Disease') :: ['NSCLC', 'non-small-cell lung cancer'] @entity2 :: ('MESH:D008175', 'Disease') :: ['lung cancer']
@entity1149 :: (MESH:D002289,Disease) :: ['non-small-cell lung cancer']
