Journal of Medical Economics: Cost-effectiveness of a machine learning risk prediction model (LungFlag) in the selection of high-risk individuals for non-small cell lung cancer screening in Spain

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Authors:

Juan Carlos Trujillo, Joan B. Soriano, Mercè Marzo, Oliver Higuera, Luis Gorospe, Virginia Pajares, María Eugenia Olmedo, Natalia Arrabal, Andrés Flores, José Francisco García, María Crespo, David Carcedo, Carolina Heuser, Milan M. S. Obradović, Nicolò Olghi, Eran N. Choman & Luis M. Seijo

Objective:

The LungFlag risk prediction model uses individualized clinical variables to identify
individuals at high-risk of non-small cell lung cancer (NSCLC) for screening with low-
dose computed tomography (LDCT). This study evaluates the cost-effectiveness of

LungFlag implementation in the Spanish setting for the identification of individuals at
high-risk of NSCLC.

Conclusions

Using LungFlag for the selection of high-risk individuals for NSCLC screening in Spain would be
a cost-effective strategy over screening the entire population meeting USPSTF 2013 criteria and
is dominant over non-screening.

https://www.tandfonline.com/doi/full/10.1080/13696998.2024.2444781#abstract