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A Game-Changing 20 Years: Progress and Future Directions in Lung Cancer Screening.

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Lung cancer screening (LCS) using low-dose computed tomography (LDCT) significantly reduces mortality by over 20% in high-risk individuals. Ongoing advancements in AI and risk prediction promise further improvements in early detection and patient outcomes.

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Area of Science:

  • Pulmonology
  • Radiology
  • Oncology

Background:

  • Lung cancer screening (LCS) with low-dose computed tomography (LDCT) has proven effective in reducing lung cancer mortality, with landmark trials like NLST and NELSON showing over 20% reduction.
  • LDCT is now a standard of care for early detection in high-risk populations, with 13 countries implementing national or regional screening programs.

Purpose of the Study:

  • To review the current state and future directions of lung cancer screening.
  • To highlight advancements in risk prediction, imaging analysis, and artificial intelligence integration.
  • To discuss strategies for improving screening uptake, expanding screening criteria, and integrating LCS with other health initiatives.

Main Methods:

  • Review of landmark clinical trials (NLST, NELSON) and current global implementation of LCS programs.
  • Analysis of recent technological advancements including AI in nodule detection and risk assessment.
  • Examination of strategies for enhancing screening accessibility, patient engagement, and integration with smoking cessation and other disease detection.

Main Results:

  • Real-world evidence supports improved lung cancer stage distribution and suggests mortality reduction.
  • AI integration enhances nodule detection, malignancy risk prediction, and screening interval personalization.
  • Expanding screening to never-smokers and integrating incidental findings (e.g., coronary artery disease, COPD) shows potential for broader health benefits.

Conclusions:

  • Lung cancer screening is a cornerstone of lung cancer control, with ongoing innovations crucial for maximizing global benefit and equity.
  • Continued advancements in risk stratification, imaging technology, and biomarker integration are essential for the evolution of LCS.
  • Harmonizing data standards, quality indicators, and workforce training are vital for sustained high-quality implementation of LCS programs.