Lung cancer screening

In this video, Dr Anouk Goudsmit and Prof Mariana Brandão, both medical oncologist at the Institut Jules Bordet in Brussels, discuss some of the key take-aways from an educational session at ELCC 2025 dedicated to lung cancer screening (LCS)

A first important challenge when it comes to LCS is the definition of the target population. For the moment, most of the existing LCS initiatives use smoking status and age as the only criteria to delineate the target population. However, in doing so, they forego on the important role of the genetic predisposistion, (lung) comorbidities, family history and pollution. In an attempt to better define the target population for LCS, several research groups have developed scores, of which the Modified PLCO Lung-Cancer Risk-Prediction Model (PLCOM2012), the Liverpool Lung Project (LLP) model and the Bach model are the ones that are best known. During ELCC 2025, data were presented of a study comparing these three models, suggesting that PLCOM2012 is probably the better choice.¹ While these models certainly have their worth, they don’t adequately address the increasing incidence of lung cancer among never smokers. In this respect, promising data were presented for a polygenetic model developed in Taiwan.²

Once the target population has been defined, a second important challenge related to LCS consists of actually motivating this target group to participate in the screening. The latter is especially true for LCS given the stigma that comes with smoking and the fact that the risk for lung cancer is especially pronounced in difficult to reach populations (e.g., lower social status). To overcome this, there is a need for innovative outreach strategies. In this respect, a nice example in the UK was discussed in which a mobile testing center goes to regions of the country where the risk for lung cancer is believed to be very high (e.g., lower income regions, regions with pollution, etc.). In addition to innovative strategies like this, Prof Brandão underscores that also the general practitioner can play an important role in motivating people to participate in a LCS program.

On a final note, the large understudied potential of artificial intelligence (AI) in LCS was addressed. Several studies are already evaluating AI as a tool to increase the efficacy of scan evaluation, but the potential of this technology is much broader than this. For example AI may also play a role in the identification of at-risk patients. According to Dr Goudsmit, embracing AI will be an important element to deal with the increased workload that will come after the implementation of a LCS in Belgium.