Use of the Predictive Risk Model, LungFlag™ for Lung Cancer Screening in a Spanish Reference Center: A Cost-effectiveness Analysis.

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Authors:

María Eugenia Olmedo, Luis Gorospe, Luis Miguel Seijo, Virginia Pajares, Mercè Marzo, Joan B. Soriano, Juan Carlos Trujillo, Natalia Arrabal, Andrés Flores, Fran García, María Crespo, David Carcedo, Carolina Heuser, Olghi Nicolò, Eran Choman, Oliver Higuera

BACKGROUND

Several risk prediction models have been developed to select high-risk individuals for lung cancer screening. These allow the calculation of personalized risk as an alternative to standard criteria based on age and cumulative smoking exposure.

  • LungFlag™ is an artificial intelligence-based risk prediction model effective in the selection of high-risk individuals by evaluating routine clinical and laboratory. 
  • In Spain, there is no national lung cancer screening program, and only a few pilot programs have been developed.
  • The aim of this analysis is to assess the cost-effectiveness of LungFlag for the identification of high-risk individuals for enrolment in a NSCLC screening programme in a hypothetical Spanish reference center.

Conclusions

The implementation of LungFlag as a risk model for NSCLC screening in a hypothetical Spanish reference center would be cost-effective compared to no-screening for the 2 hypothetical cohorts analyzed, providing savings and a higher clinical benefit. Narrowing the screening to patients who meet USPSTF criteria seems to optimise the benefits of using LungFlag.