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Budget Impact of the LungFlag™ Predictive Risk Model for Lung Cancer Screening.

Carolina Heuser1, Michael K Gould2, Eran Choman3

  • 1F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, Building 002, 4070, Basel, Switzerland. carolina.heuser@roche.com.

Pharmacoeconomics - Open
|December 18, 2025
PubMed
Summary

Lung cancer screening using the LungFlag model can save $2.8 million over five years. This AI tool identifies high-risk individuals for early non-small cell lung cancer (NSCLC) detection, reducing advanced treatment costs.

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Area of Science:

  • Health Economics
  • Artificial Intelligence in Medicine
  • Oncology

Background:

  • Lung cancer screening often yields false positives, increasing costs and complications.
  • The LungFlag model uses machine learning for individual risk prediction of non-small cell lung cancer (NSCLC).
  • This study assesses the budget impact of LungFlag for identifying lung cancer screening candidates from a US payer viewpoint.

Purpose of the Study:

  • To evaluate the budget impact of implementing the LungFlag risk prediction model for lung cancer screening.
  • To determine the cost-effectiveness of using AI to identify high-risk individuals for low-dose computed tomography (LDCT) screening.

Main Methods:

  • A budget impact model simulated costs for a 1-million-member US commercial health plan over 5 years.
  • Included screening-naïve individuals aged 50-80 meeting US Preventive Services Task Force 2021 NSCLC screening criteria.
  • Analyzed incremental costs, with LungFlag performance assessed pre-diagnosis; sensitivity analyses were performed.

Main Results:

  • LungFlag implementation is projected to yield total cumulative cost savings of $2.8 million over 5 years.
  • Savings are primarily driven by reduced advanced NSCLC treatment costs ($4.4 million).
  • LungFlag identified 17 additional NSCLC cases, prevented 22 deaths, and shifted diagnoses to earlier stages (50 more Stage I, 33 fewer Stage III/IV).

Conclusions:

  • Utilizing the LungFlag model for lung cancer screening candidate identification is estimated to result in $2.8 million in savings over 5 years.
  • The cost savings stem mainly from decreased expenses associated with treating advanced non-small cell lung cancer.
  • LungFlag facilitates earlier detection, improving patient outcomes and reducing overall healthcare expenditures.