To evaluate the association of photography-estimated biological age (face age) and spirometry-estimated age (lung age) with overall survival and early mortality outcomes in early-stage NSCLC patients undergoing SBRT.
Key Findings:
Face age and lung age provide complementary information regarding biological fitness in NSCLC patients, highlighting the potential of AI in enhancing prognostic assessments in high-risk cancer populations.
Patients with a significant difference between face age and chronological age showed varied survival outcomes.
Interpretation:
The findings suggest that biological age markers can improve prognostic accuracy and aid in treatment decision-making for older NSCLC patients undergoing SBRT by providing a more nuanced understanding of patient health.
Limitations:
Retrospective design may introduce selection bias.
Limited generalizability due to the specific patient population studied.
Potential inaccuracies in biological age estimation methods.
Confounding factors such as comorbidities may affect the results.
Conclusion:
Biological age assessment using AI-driven models may enhance treatment personalization and prognostication in early-stage NSCLC patients receiving SBRT.
by Grace Lee, Fridolin Haugg, Dennis Bontempi, John He, Danielle S. Bitterman, Suraj Pai, Christian Guthier, Kelly J. Fitzgerald, David E. Kozono, Benjamin H. Kann, Hugo J. W. L. Aerts, Raymond H. Mak
