Occult metastases and survival of lung cancer by clinical diagnosis and CT screening: A simulation study

PLoS One. 2025 Jan 3;20(1):e0313544. doi: 10.1371/journal.pone.0313544. eCollection 2025.

Abstract

Objectives: It is significant to know how much early detection and screening could reduce the proportion of occult metastases and benefit NSCLC patients.

Methods: We used previously designed and validated mathematical models to obtain the characteristics of LC in the population including undetectable metastases at the time of diagnosis. The survival was simulated using the survival functions from Surveillance, Epidemiology and End Results (SEER) data stratified by stage.

Results: Based on the simulations, 35.3% of patients diagnosed with stage N0M0 and 56.9% of those diagnosed with stage N1M0 had nodal or distant metastases that were not discovered at the time of diagnosis. Among clinically detected Stage I lung cancers with tumor diameter 1-2 cm, 78% were true stage N0M0 (no occult metastases) while it was only 37% for patients with tumor diameters of 2-3 cm. This size threshold can be translated into a 0.75-year the "window of opportunity" for the curable disease. In a comparative analysis of two simulated groups of individuals: (1) clinically diagnosed (2) diagnosed by screening with a varying screening frequency (quarterly, biannual, annual and biennial), it was estimated that, once the screening intervals become shorter, substantially more cancers are found, but at an expense of a higher radiation exposure. The simulation projected that the mortality reduction in screened patients depending on the frequency, ranged from 15.04% to 18.82%.

Conclusions: The probability of occult metastases significantly increases when the primary tumor exceeds 2 cm in diameter. Effective screening measures that detect smaller tumors will considerably benefit asymptomatic LC patients.

MeSH terms

  • Carcinoma, Non-Small-Cell Lung / diagnosis
  • Carcinoma, Non-Small-Cell Lung / diagnostic imaging
  • Carcinoma, Non-Small-Cell Lung / mortality
  • Carcinoma, Non-Small-Cell Lung / pathology
  • Computer Simulation
  • Early Detection of Cancer* / methods
  • Female
  • Humans
  • Lung Neoplasms* / diagnosis
  • Lung Neoplasms* / diagnostic imaging
  • Lung Neoplasms* / mortality
  • Lung Neoplasms* / pathology
  • Male
  • Neoplasm Metastasis
  • Neoplasm Staging
  • SEER Program
  • Survival Analysis
  • Tomography, X-Ray Computed*

Grants and funding

This study was funded by the following grants: National Natural Science Foundation of China No. 82172064 and 81571769 to X.C.; 'Pioneer' and 'Leading Goose' R&D Program of Zhejiang No. 2022c03188 and 2022C03SA1I1049 to X.C.; CISNET 5 U01 CA097431 to M.K. and O.G.; FAMRI Young Clinical Scientist Award and Prevent Cancer Foundation grants to O.G.; NIH grants R01 CA149462 to OYG, R03CA1338885 and R03128025 to O.G., CA55769 to M.R.S.; NIH U19CA203654 grant; the RR170048 Cancer Prevention and Research Institute of Texas grant; and ARC Foundation Project CANC’AIR grant. M.K. was supported by the National Science Center (Poland) grant 2021/41/B/NZ2/04134. M.J. was funded by Medical Health Science and Technology Project of Zhejiang Provincial Health Commission (No. 2022KY828). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.