Russian Federation
Moskva, Russian Federation
UDC 61
The incidence and mortality from lung cancer is increasing worldwide, which makes screening for this disease not only relevant but also extremely necessary. This review analyzes articles published in the databases of the electronic scientific library e-library.ru, the electronic scientific library cyberleninka.ru, and PubMed. The most important articles in English and Russian on lung cancer screening are selected. Low-dose computed tomography is considered the reference screening method, the disadvantages of which may include incorrect results and human radiation. Research is being conducted to find out how effective low-dose computed tomography is in detecting lung cancer in people who do not smoke. Artificial intelligence can significantly improve the accuracy of lung cancer screening. Endobronchial optical coherence tomography is proposed as an alternative to low-dose computed tomography. However, large-scale clinical trials are required to confirm the effectiveness of endobronchial optical coherence tomography. To overcome these problems, it is recommended to use lung cancer biomarkers. Such biomarkers include: circulating tumor DNA and fragments of extracellular DNA, clonal hematopoietic mutations, carcinoembryonic antigen, carbohydrate antigen 125, blood metabolites, volatile organic compounds. The use of biomarkers will significantly improve the results of lung cancer screening and increase the detection of this dangerous disease at early stages. Modern forms and methods of lung cancer screening, based on the latest scientific achievements and best practices, can significantly increase its effectiveness.
lung cancer, screening, artificial intelligence, low-dose computed tomography, endobronchial optical coherence tomography, biomarkers
1. Filho AM, Laversanne M, Ferlay J et al. The GLOBOCAN 2022 cancer estimates: Data sources, methods, and a snapshot of the cancer burden worldwide. Int J Cancer. 2025 Apr 1;156(7):1336-1346. http://www.doi.org:https://doi.org/10.1002/ijc.35278
2. Luo G, Zhang Y, Etxeberria J et al. Projections of Lung Cancer Incidence by 2035 in 40 Countries Worldwide: Population-Based Study. JMIR Public Health Surveill. 2023 Feb 17;9:e43651. http://www.doi.org:https://doi.org/10.2196/43651
3. Lancaster HL, Heuvelmans MA, Oudkerk M. Low-dose computed tomography lung cancer screening: Clinical evidence and implementation research. J Intern Med. 2022 Jul;292(1):68-80. http://www.doi.org:https://doi.org/10.1111/joim.13480
4. Metodicheskie rekomendacii po skriningu raka legkogo. sost. V. A. Gombolevskiy, I. A. Blohin, A. Sh. Laypan [i dr.] Seriya «Luchshie praktiki luchevoy i instrumental'noy diagnostiki». Vyp. 56. M.: GBUZ «Nauchno-prakticheskiy klinicheskiy centr diagnostiki i telemedicinskih tehnologiy Departamenta zdravoohraneniya goroda Moskvy» 2020. 60 s.
5. Tang Y, Zhou L, Wang F et al. Assessing the efficiency of eligibility criteria for low-dose computed tomography lung screening in China according to current guidelines. BMC Med. 2024 Jun 26;22(1):267. http://www.doi.org:https://doi.org/10.1186/s12916-024-03445-5
6. Emmerick ICM, Campos MR, Castanheira D et al. Lung Cancer Screening in Brazil Comparing the 2013 and 2021 USPSTF Guidelines. JAMA Netw Open. 2023 Dec 1;6(12):e2346994. http://www.doi.org:https://doi.org/10.1001/jamanetworkopen.2023.46994
7. Boyeras I, Roberti J, Seijo M et al. Argentine consensus recommendations for lung cancer screening programmes: a RAND/UCLA-modified Delphi study. BMJ Open. 2023 Feb 3;13(2):e068271. http://www.doi.org:https://doi.org/10.1136/bmjopen-2022-068271
8. Wang C, Dong X, Tan F et al. Risk-Adapted Starting Age of Personalized Lung Cancer Screening: A Population-Based, Prospective Cohort Study in China. Chest. 2024 Jun;165(6):1538-1554. http://www.doi.org:https://doi.org/10.1016/j.chest.2024.01.031
9. Parums DV. Editorial: Current Approaches to Screening for Lung Cancer in Smokers and Non-Smokers. Med Sci Monit. 2025 Feb 1;31:e948255. http://www.doi.org:https://doi.org/10.12659/MSM.948255
10. LoPiccolo J, Gusev A, Christiani DC, Jänne PA. Lung cancer in patients who have never smoked – an emerging disease. Nat Rev Clin Oncol. 2024;21(2):121–46. http://www.doi.org:https://doi.org/10.1038/s41571-023-00844-0
11. Gomez SL, DeRouen M, Chen MS Jr et al. Elevated risk of lung cancer among asian American females who have never smoked: an emerging cancer disparity. J Natl Cancer Inst. 2024 Nov 20:djae299. http://www.doi.org:https://doi.org/10.1093/jnci/djae299 Online ahead of print.
12. Kerpel-Fronius A, Tammemägi M, Cavic M, et al. Members of the Diagnostics Working Group; ED Screening Committee. Screening for lung cancer in individuals who never smoked: An International Association for the Study of Lung Cancer Early Detection and Screening Committee report. J Thorac Oncol. 2022;17(1):56–66. http://www.doi.org:https://doi.org/10.1016/j.jtho.2021.07.031
13. Chang GC, Chiu CH, Yu CJ, et al. TALENT Investigators. Low-dose CT screening among never-smokers with or without a family history of lung cancer in Taiwan: A prospective cohort study. Lancet Respir Med. 2024;12(2):141–52. http://www.doi.org:https://doi.org/10.1016/S2213-2600(23)00338-7
14. Gao W, Wen CP, Wu A, Welch HG. Association of computed tomographic screening promotion with lung cancer overdiagnosis among Asian women. JAMA Intern Med. 2022;182(3):283–90. http://www.doi.org:https://doi.org/10.1001/jamainternmed.2021.7769
15. Kim YW, Joo DH, Kim SY, et al. Gender disparities and lung cancer screening outcomes among individuals who have never smoked. JAMA Netw Open. 2025;8(1):e2454057. http://www.doi.org:https://doi.org/10.1001/jamanetworkopen.2024.54057
16. Silvestri GA, Young RP, Tanner NT, Mazzone P. Screening low-risk individuals for lung cancer: The need may be present, but the evidence of benefit is not. J Thorac Oncol. 2024;19(8):1155–63. http://www.doi.org:https://doi.org/10.1016/j.jtho.2024.05.001
17. Kim RY. Insights into opportunistic lung cancer screening for individuals who have never smoked. JAMA Netw Open. 2025;8(1):e2454009. http://www.doi.org:https://doi.org/10.1001/jamanetworkopen.2024.54009
18. Lai GGY, Tan DSW. Lung cancer screening in never smokers. Curr Opin Oncol. 2025 Jan 1;37(1):95-104. http://www.doi.org:https://doi.org/10.1097/CCO.0000000000001099
19. Rehman S, Lim M, Sidhu R et al. Barriers to lung cancer screening. Cancer Epidemiol. 2025 Feb;94:102722. http://www.doi.org:https://doi.org/10.1016/j.canep.2024.102722
20. Quanyang W, Yao H, Sicong W et al. Artificial intelligence in lung cancer screening: Detection, classification, prediction, and prognosis. Cancer Med. 2024 Apr;13(7):e7140. http://www.doi.org:https://doi.org/10.1002/cam4.7140
21. Mulshine JL, Avila RS, Silva M et. AI integrations with lung cancer screening: Considerations in developing AI in a public health setting. Eur J Cancer. 2025 May 2;220:115345. http://www.doi.org:https://doi.org/10.1016/j.ejca.2025.115345
22. Ahluwalia VS, Schapira MM, Weissman GE, Parikh RB. Primary Care Provider Preferences Regarding Artificial Intelligence in Point-of-Care Cancer Screening. MDM Policy Pract. 2025 Apr 4;10(1):23814683251329007. http://www.doi.org:https://doi.org/10.1177/23814683251329007
23. Duranti L, Tavecchio L, Rolli L, Solli P. New Perspectives on Lung Cancer Screening and Artificial Intelligence. Life (Basel). 2025 Mar 19;15(3):498. http://www.doi.org: https://doi.org/10.3390/life15030498
24. Lancaster HL, Jiang B, Davies MPA et al. Histological proven AI performance in the UKLS CT lung cancer screening study: Potential for workload reduction. Eur J Cancer. 2025 May 2;220:115324. http://www.doi.org:https://doi.org/10.1016/j.ejca.2025.115324
25. Lee M, Hwang EJ, Lee JH et al. Artificial Intelligence for Low-Dose CT Lung Cancer Screening: Comparison of Utilization Scenarios. AJR Am J Roentgenol. 2025 Apr 16. http://www.doi.org:https://doi.org/10.2214/AJR.25.32829
26. Megat Ramli PN, Aizuddin AN, Ahmad N et al. A Systematic Review: The Role of Artificial Intelligence in Lung Cancer Screening in Detecting Lung Nodules on Chest X-Rays. Diagnostics (Basel). 2025 Jan 22;15(3):246. http://www.doi.org:https://doi.org/10.3390/diagnostics15030246
27. Dai H, Huang Y, He X et al. Optimizing Strategy for Lung Cancer Screening: From Risk Prediction to Clinical Decision Support. JCO Clin Cancer Inform. 2025 May;9:e2400291. http://www.doi.org:https://doi.org/10.1200/CCI-24-00291
28. Trujillo JC, Soriano JB, Marzo M et al. Cost-effectiveness of a machine learning risk prediction model (LungFlag) in the selection of high-risk individuals for non-small cell lung cancer screening in Spain. J Med Econ. 2025 Dec;28(1):147-156. http://www.doi.org: https://doi.org/10.1080/13696998.2024.2444781
29. Purohit L, Kiamos A, Ali S et al. Incidental Pulmonary Nodule (IPN) Programs Working Together with Lung Cancer Screening and Artificial Intelligence to Increase Lung Cancer Detection. Cancers (Basel). 2025 Mar 28;17(7):1143. http://www.doi.org: https://doi.org/10.3390/cancers17071143
30. Kenaan N, Hanna G, Sardini M et al. Advances in early detection of non-small cell lung cancer: A comprehensive review. Cancer Med. 2024 Sep;13(18):e70156. http://www.doi.org:https://doi.org/10.1002/cam4.70156
31. Stephens EKH, Guayco Sigcha J, Lopez-Loo K et al. Biomarkers of lung cancer for screening and in never-smokers-a narrative review. Transl Lung Cancer Res. 2023 Oct 31;12(10):2129-2145. http://www.doi.org:https://doi.org/10.21037/tlcr-23-291
32. Vasseur A, Kiavue N, Bidard FC et al. Clinical utility of circulating tumor cells: an update. Mol Oncol. 2021 Jun;15(6):1647-1666. http://www.doi.org:https://doi.org/10.1002/1878-0261.12869
33. Duffy MJ. Circulating tumor DNA (ctDNA) as a biomarker for lung cancer: Early detection, monitoring and therapy prediction. Tumour Biol. 2024;46(s1):S283-S295. http://www.doi.org:https://doi.org/10.3233/TUB-220044
34. Mazzone PJ, Bach PB, Carey J et al. Clinical Validation of a Cell-Free DNA Fragmentome Assay for Augmentation of Lung Cancer Early Detection. Cancer Discov. 2024 Nov 1;14(11):2224-2242. http://www.doi.org:https://doi.org/10.1158/2159-8290
35. Anandakrishnan R, Shahidi R, Dai A et al. An approach for developing a blood-based screening panel for lung cancer based on clonal hematopoietic mutations. PLoS One. 2024 Aug 22;19(8):e0307232. http://www.doi.org:https://doi.org/10.1371/journal.pone.0307232
36. Dou X, Lu J, Yu Y et al. Determination of Tumor Marker Screening for Lung Cancer Using ROC Curves. Dis Markers. 2024 Mar 21;2024:4782618. http://www.doi.org:https://doi.org/10.1155/2024/4782618
37. Tang Z, Liang D, Deubler EL et al. Lung cancer metabolomics: a pooled analysis in the Cancer Prevention Studies. BMC Med. 2024 Jun 24;22(1):262. http://www.doi.org: https://doi.org/10.1186/s12916-024-03473-1
38. Wu G, Liu J, Shi H et al. The associations between dysregulation of human blood metabolites and lung cancer risk: evidence from genetic data. BMC Cancer. 2024 Jul 18;24(1):854. http://www.doi.org:https://doi.org/10.1186/s12885-024-12416-1
39. Fan X, Zhong R, Liang H et al. Exhaled VOC detection in lung cancer screening: a comprehensive meta-analysis. BMC Cancer. 2024 Jun 27;24(1):775. http://www.doi.org:https://doi.org/10.1186/s12885-024-12537-7
