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  • Review Article
  • Published:

Lung cancer LDCT screening and mortality reduction — evidence, pitfalls and future perspectives

Nature Reviews Clinical Oncology volume 18, pages 135–151 (2021)Cite this article

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Abstract

In the past decade, the introduction of molecularly targeted agents and immune-checkpoint inhibitors has led to improved survival outcomes for patients with advanced-stage lung cancer; however, this disease remains the leading cause of cancer-related mortality worldwide. Two large randomized controlled trials of low-dose CT (LDCT)-based lung cancer screening in high-risk populations — the US National Lung Screening Trial (NLST) and NELSON — have provided evidence of a statistically significant mortality reduction in patients. LDCT-based screening programmes for individuals at a high risk of lung cancer have already been implemented in the USA. Furthermore, implementation programmes are currently underway in the UK following the success of the UK Lung Cancer Screening (UKLS) trial, which included the Liverpool Health Lung Project, Manchester Lung Health Check, the Lung Screen Uptake Trial, the West London Lung Cancer Screening pilot and the Yorkshire Lung Screening trial. In this Review, we focus on the current evidence on LDCT-based lung cancer screening and discuss the clinical developments in high-risk populations worldwide; additionally, we address aspects such as cost-effectiveness. We present a framework to define the scope of future implementation research on lung cancer screening programmes referred to as Screening Planning and Implementation RAtionale for Lung cancer (SPIRAL).

Key points

  • The role of CT lung cancer screening on lung cancer-related mortality reduction has been under debate for five decades and is now an evidence-based reality.

  • The implementation of low-dose CT (LDCT)-based screening requires an optimal risk modelling methodology in order to select the high-risk population that will derive the greatest benefits.

  • Biomarkers have the potential to be included in future risk assessment models and work-up of CT nodules; laboratory tests should be developed to improve risk assessment before CT screening.

  • LDCT-based lung nodule diameter measurement cannot be used as an imaging biomarker for effective lung cancer risk stratification; however, volume doubling time can effectively be used as an imaging biomarker to rule out lesions with benign tissue growth.

  • The LDCT lung cancer screening interval should eventually be tailored to the expected mean nodule growth of the targeted population, starting with personalized screening, to improve screening performance (in particular for women).

  • Effective smoking cessation interventions must be integrated within cost-effective lung cancer screening programmes.

  • We propose a framework — the Screening Planning and Implementation RAtionale for Lung cancer (SPIRAL) — to define the scope of future implementation research on lung cancer screening programmes.

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Fig. 1: Screening Planning and Implementation RAtionale for Lung cancer.
Fig. 2: Randomized controlled trials of LDCT-based approaches to lung cancer screening.
Fig. 3: The NELSON-Plus Protocol for LDCT scan-detected lung nodules.
Fig. 4: Cost-effectiveness of LDCT-based lung cancer screening.

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References

  1. Bray, F. et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 68, 394–424 (2018).

    Article  PubMed  Google Scholar 

  2. Camidge, D. R., Doebele, R. C. & Kerr, K. M. Comparing and contrasting predictive biomarkers for immunotherapy and targeted therapy of NSCLC. Nat. Rev. Clin. Oncol. 16, 341–355 (2019).

    CAS  PubMed  Google Scholar 

  3. Goldstraw, P. et al. International Association for the Study of Lung Cancer Staging and Prognostic Factors Committee, Advisory Boards, and Participating Institutions; International Association for the Study of Lung Cancer Staging and Prognostic Factors Committee Advisory Boards and Participating Institutions. The IASLC Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groupings in the Forthcoming (Eighth) Edition of the TNM Classification for Lung Cancer. J. Thorac. Oncol. 11, 39–51 (2016).

    PubMed  Google Scholar 

  4. Aberle, D. R. et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N. Engl. J. Med. 365, 395–409 (2011).

    PubMed  Google Scholar 

  5. Koning, H. D. E., Van Der Aalst, C. & K. Ten Haaf, M. Oudkerk, PL02.05 effects of volume CT lung cancer screening: mortality results of the NELSON Randomised-Controlled Population Based Trial. J. Thorac. Oncol. 13, S185 (2018).

    Google Scholar 

  6. Becker, N. et al. Lung cancer mortality reduction by LDCT screening — Results from the randomized German LUSI trial. Int. J. Cancer 146, 1503–1513 (2020).

    CAS  PubMed  Google Scholar 

  7. Pastorino, U. et al. Prolonged lung cancer screening reduced 10-year mortality in the MILD trial: new confirmation of lung cancer screening efficacy. Ann. Oncol. 30, 1162–1169 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Infante, M. et al. Long-term follow-up results of the DANTE trial, a randomized study of lung cancer screening with spiral computed tomography. Am. J. Respir. Crit. Care Med. 191, 1166–1175 (2015).

    PubMed  Google Scholar 

  9. Paci, E. et al. Mortality, survival and incidence rates in the ITALUNG randomised lung cancer screening trial. Thorax 72, 825–831 (2017).

    Google Scholar 

  10. de Koning, H. J. et al. Oudkerk, reduced lung-cancer mortality with volume CT screening in a randomized trial. N. Engl. J. Med. https://doi.org/10.1056/nejmoa1911793 (2020).

    Article  PubMed  Google Scholar 

  11. Field, J. K. et al. UK Lung Cancer RCT Pilot Screening Trial: baseline findings from the screening arm provide evidence for the potential implementation of lung cancer screening. Thorax 71, 161–170 (2016).

    CAS  PubMed  Google Scholar 

  12. Tammemägi, M. C. et al. Participant selection for lung cancer screening by risk modelling (the Pan-Canadian Early Detection of Lung Cancer [PanCan] study): a single-arm, prospective study. Lancet Oncol. 18, 1523–31. (2017).

    PubMed  Google Scholar 

  13. Henschke, C. I. et al. Survival of patients with stage I lung cancer detected on CT screening. N. Engl. J. Med. 355, 1763–1771 (2006).

    PubMed  Google Scholar 

  14. Villeneuve, P. J. Lifetime probability of developing lung cancer, by smoking status, Canada. Can. J. Public Health 85, 385–388 (1994).

    CAS  PubMed  Google Scholar 

  15. Bruder, C. et al. Estimating lifetime and 10-year risk of lung cancer. Prev. Med. Reports 11, 125–130 (2018).

    Google Scholar 

  16. Oudkerk, M. et al. European position statement on lung cancer screening. Lancet Oncol. 18, e754–e766 (2017).

    PubMed  Google Scholar 

  17. Ghimire, B. et al. Evaluation of a health service adopting proactive approach to reduce high risk of lung cancer: The Liverpool Healthy Lung Programme. Lung Cancer 134, 66–71 (2019).

    PubMed  Google Scholar 

  18. Crosbie, P. A. et al. Implementing lung cancer screening: baseline results from a community-based “Lung Health Check” pilot in deprived areas of Manchester. Thorax 74, 405–409 (2019).

    PubMed  Google Scholar 

  19. Bartlett, E. C. et al. Baseline results of the West London lung cancer screening pilot study – Impact of mobile scanners and dual risk model utilisation. Lung Cancer 148, 12–19 (2020).

    PubMed  Google Scholar 

  20. ISRCTN Registry The Yorkshire Lung Screening Trial- ISRCTN42704678. https://doi.org/10.1186/ISRCTN42704678 (2019).

  21. Raji, O. Y. et al. Predictive accuracy of the Liverpool Lung Project risk model for stratifying patients for computed tomography screening for lung cancer: a case-control and cohort validation study. Ann. Intern. Med. 157, 242–250 (2012).

    PubMed  PubMed Central  Google Scholar 

  22. Ten Haaf, K. et al. Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study. PLoS Med. 14, e1002277 (2017).

    PubMed  PubMed Central  Google Scholar 

  23. Tammemägi, M. C. et al. Development and validation of a multivariable lung cancer risk prediction model that includes low-dose computed tomography screening results. JAMA Netw. Open 2, e190204. (2019).

    PubMed  PubMed Central  Google Scholar 

  24. Cassidy, A. et al. The LLP risk model: an individual risk prediction model for lung cancer. Br. J. Cancer. 98, 270–276 (2008).

    CAS  PubMed  Google Scholar 

  25. Tammemagi, M. C. et al. Selection criteria for lung-cancer screening. N. Engl. J. Med. 368, 728–736 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Kovalchik, S. A. et al. Targeting of low-dose CT screening according to the risk of lung-cancer death. N. Engl. J. Med. 369, 245–254 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Katki, H. A., Kovalchik, S. A., Berg, C. D., Cheung, L. C. & Chaturvedi, A. K. Development and validation of risk models to select ever-smokers for ct lung cancer screening. JAMA 315, 2300–2311 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Field, J. K. et al. The UK lung cancer screening trial: a pilot randomised controlled trial of low-dose computed tomography screening for the early detection of lung cancer. Health Technol. Assess. 20, 1–146 (2016).

    PubMed  PubMed Central  Google Scholar 

  29. US-National-Libary-Medicine. ClinicalTrials.gov https://www.clinicaltrials.gov/ct2/show/NCT03934866 (2018).

  30. NHS-England National-Cancer-Programme. Targeted Screening for Lung Cancer with Low Radiation Dose Computed Tomography https://www.england.nhs.uk/wp-content/uploads/2019/02/targeted-lung-health-checks-standard-protocol-v1.pdf (2019).

  31. Ten Haaf, K. et al. A comparative modeling analysis of risk-based lung cancer screening strategies. J. Natl Cancer Inst. 112, 466–479 (2020).

    PubMed  Google Scholar 

  32. Gordon, W. J., Landman, A., Zhang, H. & Bates, D. W. Beyond validation: getting health apps into clinical practice. NPJ Digit. Med. https://doi.org/10.1038/s41746-019-0212-z (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Seijo, L. M. et al. Biomarkers in lung cancer screening: achievements, promises, and challenges. J. Thorac. Oncol. 14, 343–357 (2019).

    CAS  PubMed  Google Scholar 

  34. Amos, C. I., Brennan, P. J., Hung, R. J. & Lin, X. Integrative analysis of lung cancer etiology and risk. Grantome.com https://grantome.com/grant/NIH/U19-CA203654-01A1 (2017).

  35. Kachuri, L. et al. Immune-mediated genetic pathways resulting in pulmonary function impairment increase lung cancer susceptibility. Nat. Commun. https://doi.org/10.1038/s41467-019-13855-2 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Liu, Y. et al. Rare variants in known susceptibility loci and their contribution to risk of lung cancer. J. Thorac. Oncol. 13, 1483–1495 (2018).

    PubMed  PubMed Central  Google Scholar 

  37. Ji, X. et al. Identification of susceptibility pathways for the role of chromosome 15q25.1 in modifying lung cancer risk. Nat. Commun. 9, 3221 (2018).

    PubMed  PubMed Central  Google Scholar 

  38. Guida, F. et al. Assessment of lung cancer risk on the basis of a biomarker panel of circulating proteins. JAMA Oncol. 4, e182078 (2018).

    PubMed  PubMed Central  Google Scholar 

  39. Accomasso, L., Cristallini, C. & Giachino, C. Risk assessment and risk minimization in nanomedicine: A need for predictive, alternative, and 3Rs strategies. Front. Pharmacol. 9, 228 (2018).

    PubMed  PubMed Central  Google Scholar 

  40. Pham, D., Bhandari, S., Pinkston, C., Oechsli, M. & Kloecker, G. Lung cancer screening registry reveals low-dose CT screening remains heavily underutilized. Clin. Lung Cancer 21, e206–e211 (2020).

    PubMed  Google Scholar 

  41. van der Aalst, C. M., Ten Haaf, K. & de Koning, H. J. Lung cancer screening: latest developments and unanswered questions. Lancet Respir. Med. 4, 749–761 (2016).

    PubMed  Google Scholar 

  42. Ali, N. et al. Barriers to uptake among high-risk individuals declining participation in lung cancer screening: a mixed methods analysis of the UK lung cancer screening (UKLS) trial. BMJ Open 5, e008254 (2015).

    PubMed  PubMed Central  Google Scholar 

  43. McRonald, F. E. et al. The UK Lung Screen (UKLS): Demographic profile of first 88,897 approaches provides recommendations for population screening. Cancer Prev. Res. 7, 362–371 (2014).

    Google Scholar 

  44. Cassim, S. et al. Patient and carer perceived barriers to early presentation and diagnosis of lung cancer: a systematic review. BMC Cancer 19, 25 (2019).

    PubMed  PubMed Central  Google Scholar 

  45. National Lung Screening Trial Research Team. et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N. Engl. J. Med. 365, 395–409 (2011).

    Google Scholar 

  46. van Klaveren, R. J. et al. Management of lung nodules detected by volume CT scanning. N. Engl. J. Med. 361, 2221–2229 (2009).

    PubMed  Google Scholar 

  47. Field, J. K., Duffy, S. W., Devaraj, A. & Baldwin, D. R. Implementation planning for lung cancer screening: five major challenges. Lancet Respir. Med. 4, 685–687 (2016).

    PubMed  Google Scholar 

  48. Fontana, R. S. et al. Lung cancer screening: the Mayo program. J. Occup. Med. 28, 746–750 (1986).

    CAS  PubMed  Google Scholar 

  49. Oken, M. M. et al. Screening by chest radiograph and lung cancer mortality: The Prostate, Lung, Colorectal, and Ovarian (PLCO) randomized trial. JAMA 306, 1865–1873 (2011).

    CAS  PubMed  Google Scholar 

  50. American College of Radiology and Radiological Society of North America. Radiation Dose in X-Ray and CT Exams https://www.radiologyinfo.org/en/pdf/safety-xray.pdf (2019).

  51. Field, J. K. et al. European randomized lung cancer screening trials: Post NLST. J. Surg. Oncol. 108, 280–286 (2013).

    PubMed  Google Scholar 

  52. Han, D. et al. An update on the European lung cancer screening trials and comparison of lung cancer screening recommendations in Europe. J. Thorac. Imaging 34, 65–71 (2019).

    PubMed  Google Scholar 

  53. American College of Radiology. Lung-RADS Version 1.1 https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/Lung-Rads (2019).

  54. Smith, R. A. et al. Cancer screening in the United States, 2017: a review of current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J. Clin. 67, 100–121 (2017).

    PubMed  Google Scholar 

  55. Walter, J. E. et al. Occurrence and lung cancer probability of new solid nodules at incidence screening with low-dose CT: analysis of data from the randomised, controlled NELSON trial. Lancet Oncol. 17, 907–916 (2016).

    PubMed  Google Scholar 

  56. Wilson, D. O. et al. The Pittsburgh Lung Screening Study (PLuSS): outcomes within 3 years of a first computed tomography scan. Am. J. Respir. Crit. Care Med. 178, 956–961 (2008).

    PubMed  PubMed Central  Google Scholar 

  57. Swensen, S. J. et al. CT screening for lung cancer: five-year prospective experience. Radiology 235, 259–265 (2005).

    PubMed  Google Scholar 

  58. van Klaveren, R. J. et al. Management of lung nodules detected by volume CT scanning. N. Engl. J. Med. 361, 2221–2229 (2009).

    PubMed  Google Scholar 

  59. Henschke, C. I. et al. Early lung cancer action project: overall design and findings from baseline screening. Lancet 354, 99–105 (1999).

    CAS  PubMed  Google Scholar 

  60. Pedersen, J. H. et al. The Danish randomized lung cancer CT screening trial–overall design and results of the prevalence round. J. Thorac. Oncol. 4, 608–614 (2009).

    PubMed  Google Scholar 

  61. The National Lung Screening Trial Research Team. Results of initial low-dose computed tomographic screening for lung cancer. N. Engl. J. Med. 368, 1980–1991 (2013).

    PubMed Central  Google Scholar 

  62. Henschke, C. I. et al. Survival of patients with stage I lung cancer detected on CT screening. N. Engl. J. Med. 355, 1763–1771 (2006).

    PubMed  Google Scholar 

  63. Lopes Pegna, A. et al. Design, recruitment and baseline results of the ITALUNG trial for lung cancer screening with low-dose CT. Lung Cancer 64, 34–40 (2009).

    PubMed  Google Scholar 

  64. Becker, N. et al. Randomized study on early detection of lung cancer with MSCT in Germany: study design and results of the first screening round. J. Cancer Res. Clin. Oncol. 138, 1475–1486 (2012).

    CAS  PubMed  Google Scholar 

  65. Henschke, C. I. et al. Early lung cancer action project: initial findings on repeat screening. Cancer 92, 153–159 (2001).

    CAS  PubMed  Google Scholar 

  66. Swensen, S. J. et al. Screening for lung cancer with low-dose spiral computed tomography. Am. J. Respir. Crit. Care Med. 165, 508–513 (2002).

    PubMed  Google Scholar 

  67. Pinsky, P. F., Gierada, D. S., Hrudaya Nath, P. & Munden, R. Lung cancer risk associated with new solid nodules in the national lung screening trial. Am. J. Roentgenol. 209, 1009–1014 (2017).

    Google Scholar 

  68. Saghir, Z. et al. CT screening for lung cancer brings forward early disease. The randomised Danish Lung Cancer Screening Trial: status after five annual screening rounds with low-dose CT. Thorax 67, 296–301 (2012).

    PubMed  Google Scholar 

  69. Heuvelmans, M. A. et al. Relationship between nodule count and lung cancer probability in baseline CT lung cancer screening: The NELSON study. Lung Cancer 113, 45–50 (2017).

    PubMed  Google Scholar 

  70. Walter, J. E. et al. Relationship between the number of new nodules and lung cancer probability in incidence screening rounds of CT lung cancer screening: The NELSON study. Lung Cancer 125, 103–108 (2018).

    PubMed  Google Scholar 

  71. MacMahon, H. et al. Guidelines for management of incidental pulmonary nodules detected on CT images: from the Fleischner Society 2017. Radiology 284, 228–243 (2017).

    PubMed  Google Scholar 

  72. American College of Radiology. LungRADSTM Version 1.0 Assessment Categories Release date: April 28, 2014 https://www.acr.org/-/media/ACR/Files/RADS/Lung-RADS/LungRADS_AssessmentCategories.pdf (2014).

  73. Han, D. et al. Influence of lung nodule margin on volume-and diameter-based reader variability in CT lung cancer screening. Br. J. Radiol. 91, 20170405 (2018).

    PubMed  Google Scholar 

  74. Heuvelmans, M. A. et al. Disagreement of diameter and volume measurements for pulmonary nodule size estimation in CT lung cancer screening. Thorax 73, 779–781 (2018).

    PubMed  Google Scholar 

  75. Callister, M. E. J. et al. British Thoracic Society guidelines for the investigation and management of pulmonary nodules. Thorax 70, 1–54 (2015).

    Google Scholar 

  76. Heuvelmans, M. A. & Oudkerk, M. Pulmonary nodules measurements in CT lung cancer screening. J. Thorac. Dis. 10, S2100–S2102 (2018).

    PubMed  PubMed Central  Google Scholar 

  77. Han, D. et al. Influence of lung nodule margin on volume- and diameter-based reader variability in CT lung cancer screening. Br. J. Radiol. 91, 20170405 (2018).

    PubMed  Google Scholar 

  78. Bankier, A. A. et al. Recommendations for measuring pulmonary nodules at CT: a statement from the Fleischner society. Radiology 285, 584–600 (2017).

    PubMed  Google Scholar 

  79. Kakinuma, R. et al. Solitary pure ground-glass nodules 5 mm or smaller: frequency of growth. Radiology 276, 873–882 (2015).

    PubMed  Google Scholar 

  80. Horeweg, N. et al. Lung cancer probability in patients with CT-detected pulmonary nodules: A prespecified analysis of data from the NELSON trial of low-dose CT screening. Lancet Oncol. 15, 1332–1341 (2014).

    PubMed  Google Scholar 

  81. Henschke, C. I. et al. CT screening for lung cancer: part-solid nodules in baseline and annual repeat rounds. Am. J. Roentgenol. 207, 1176–1184 (2016).

    Google Scholar 

  82. Yip, R. et al. Lung cancer deaths in the national lung screening trial attributed to nonsolid nodules. Radiology 281, 589–596 (2016).

    PubMed  Google Scholar 

  83. Walter, J. E. et al. New subsolid pulmonary nodules in lung cancer screening: the NELSON trial. J. Thorac. Oncol. 13, 1410–1414 (2018).

    PubMed  Google Scholar 

  84. Henschke, C. I. et al. ELCAP Group, CT screening for lung cancer: frequency and significance of part-solid and nonsolid nodules. Am. J. Roentgenol. 178, 1053–1057 (2002).

    Google Scholar 

  85. Lee, S. M. et al. Transient part-solid nodules detected at screening thin-section CT for lung cancer: comparison with persistent part-solid nodules. Radiology 255, 242–251 (2010).

    PubMed  Google Scholar 

  86. Oh, J.-Y. et al. Clinical significance of a solitary ground-glass opacity (GGO) lesion of the lung detected by chest CT. Lung Cancer 55, 67–73 (2007).

    PubMed  Google Scholar 

  87. Kakinuma, R. et al. Natural history of pulmonary subsolid nodules: a prospective multicenter study. J. Thorac. Oncol. 11, 1012–1028 (2016).

    PubMed  Google Scholar 

  88. McWilliams, A. et al. Probability of cancer in pulmonary nodules detected on first screening CT. N. Engl. J. Med. 369, 910–919 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  89. Tammemagi, M. et al. Predicting malignancy risk of screen-detected lung nodules–mean diameter or volume. J. Thorac. Oncol. 14, 203–211 (2019).

    PubMed  Google Scholar 

  90. Marcus, M. W. et al. Probability of cancer in lung nodules using sequential volumetric screening up to 12 months: the UKLS trial. Thorax 74, 761–767 (2019).

    PubMed  Google Scholar 

  91. Raghu, V. K. et al. Feasibility of lung cancer prediction from low-dose CT scan and smoking factors using causal models. Thorax 74, 643–649 (2019).

    PubMed  Google Scholar 

  92. Swensen, S. J., Silverstein, M. D., Ilstrup, D. M., Schleck, C. D. & Edell, E. S. The probability of malignancy in solitary pulmonary nodules. Application to small radiologically indeterminate nodules. Arch. Intern. Med. 157, 849–855 (1997).

    CAS  PubMed  Google Scholar 

  93. Li, Y., Chen, K. Z. & Wang, J. Development and validation of a clinical prediction model to estimate the probability of malignancy in solitary pulmonary nodules in Chinese people. Clin. Lung Cancer 12, 313–319 (2011).

    PubMed  Google Scholar 

  94. González Maldonado, S. et al. Evaluation of prediction models for identifying malignancy in pulmonary nodules detected via low-dose computed tomography. JAMA Netw. Open 3, e1921221 (2020).

    PubMed  Google Scholar 

  95. Heuvelmans, M. A. & Oudkerk, M. Less is more in lung cancer risk prediction models. JAMA Netw. Open 3, e1921492 (2020).

    PubMed  Google Scholar 

  96. De Koning, H. J. et al. Benefits and harms of computed tomography lung cancer screening strategies: a comparative modeling study for the U.S. Preventive services task force. Ann. Intern. Med. 160, 311–320 (2014).

    PubMed  PubMed Central  Google Scholar 

  97. Patz, E. F. et al. Lung cancer incidence and mortality in National Lung Screening Trial participants who underwent low-dose CT prevalence screening: a retrospective cohort analysis of a randomised, multicentre, diagnostic screening trial. Lancet Oncol. 17, 590–599 (2016).

    PubMed  PubMed Central  Google Scholar 

  98. Pastorino, U. et al. Ten-year results of the Multicentric Italian Lung Detection trial demonstrate the safety and efficacy of biennial lung cancer screening. Eur. J. Cancer 118, 142–148 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  99. Schreuder, A. et al. Lung cancer risk to personalise annual and biennial follow-up computed tomography screening. Thorax https://doi.org/10.1136/thoraxjnl-2017-211107 (2018).

    Article  PubMed  Google Scholar 

  100. Yousaf-Khan, U. et al. Final screening round of the NELSON lung cancer screening trial: the effect of a 2.5-year screening interval. Thorax 72, 1–9 (2016).

    Google Scholar 

  101. Heuvelmans, M. A. & Oudkerk, M. Appropriate screening intervals in low-dose CT lung cancer screening. Transl Lung Cancer Res. 7, 281–287 (2018).

    PubMed  PubMed Central  Google Scholar 

  102. Pinsky, P. F., Church, T. R., Izmirlian, G. & Kramer, B. S. The National Lung Screening Trial: results stratified by demographics, smoking history, and lung cancer histology. Cancer 119, 3976–3983 (2013).

    PubMed  Google Scholar 

  103. National Lung Screening Trial Research Team. Lung cancer incidence and mortality with extended follow-up in the national lung screening trial. J. Thorac. Oncol. 14, 1732–1742 (2019).

    Google Scholar 

  104. Ten Haaf, K., Van Rosmalen, J. & de Koning, H. J. Lung cancer detectability by test, histology, stage, and gender: Estimates from the NLST and the PLCO trials. Cancer Epidemiol. Biomarkers Prev. 24, 154–161 (2015).

    PubMed  Google Scholar 

  105. Radkiewicz, C. et al. Sex and survival in non-small cell lung cancer: a nationwide cohort study. PLoS ONE 14, e0219206 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  106. Wainer, Z. et al. Sex-dependent staging in non–small-cell lung cancer; analysis of the effect of sex differences in the eighth edition of the Tumor, Node, Metastases Staging System. Clin. Lung Cancer 19, e933–e944 (2018).

    PubMed  Google Scholar 

  107. Tammemägi, M. C., Berg, C. D., Riley, T. L., Cunningham, C. R. & Taylor, K. L. Impact of lung cancer screening results on smoking cessation. J. Natl Cancer Inst. 106, dju084 (2014).

    PubMed  PubMed Central  Google Scholar 

  108. Ashraf, H. et al. Smoking habits in the randomised Danish Lung Cancer Screening Trial with low-dose CT: final results after a 5-year screening programme. Thorax 69, 574–579 (2014).

    PubMed  Google Scholar 

  109. Brain, K. et al. Impact of low-dose CT screening on smoking cessation among high-risk participants in the UK Lung Cancer Screening trial. Thorax 72, 912–918 (2017).

    PubMed  Google Scholar 

  110. Kummer, S. et al. Mapping the spectrum of psychological and behavioural responses to low-dose CT lung cancer screening offered within a Lung Health Check. Health Expect. 23, 433–441 (2020).

    PubMed  PubMed Central  Google Scholar 

  111. Villanti, A. C., Jiang, Y., Abrams, D. B. & Pyenson, B. S. A cost-utility analysis of lung cancer screening and the additional benefits of incorporating smoking cessation interventions. PLoS ONE 8, e71379 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  112. Black, W. C. et al. Cost-effectiveness of CT screening in the National Lung Screening Trial. N. Engl. J. Med. 371, 1793–1802 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  113. Criss, S. D. et al. Cost-effectiveness analysis of lung cancer screening in the United States: a Comparative Modeling Study. Ann. Intern. Med. 171, 796–804 (2019).

    PubMed  Google Scholar 

  114. Toumazis, I. et al. Cost-effectiveness analysis of lung cancer screening accounting for the effect of indeterminate findings. JNCI Cancer Spectr. 3, pkz035 (2019).

    PubMed  PubMed Central  Google Scholar 

  115. Pyenson, B. S., Henschke, C. I., Yankelevitz, D. F., Yip, R. & Dec, E. Offering lung cancer screening to high-risk medicare beneficiaries saves lives and is cost-effective: an actuarial analysis. Am. Health Drug Benefits 7, 272–282 (2014).

    PubMed  PubMed Central  Google Scholar 

  116. Goffin, J. R. et al. Biennial lung cancer screening in Canada with smoking cessation — outcomes and cost-effectiveness. Lung Cancer 101, 98–103 (2016).

    PubMed  Google Scholar 

  117. Ten Haaf, K. et al. Performance and cost-effectiveness of computed tomography lung cancer screening scenarios in a population-based setting: a microsimulation modeling analysis in Ontario, Canada. PLOS Med. 14, e1002225 (2017).

    PubMed  PubMed Central  Google Scholar 

  118. Cressman, S. et al. The cost-effectiveness of high-risk lung cancer screening and drivers of program efficiency. J. Thorac. Oncol. 12, 1210–1222 (2017).

    PubMed  Google Scholar 

  119. Tomonaga, Y. et al. Cost-effectiveness of low-dose CT screening for lung cancer in a European country with high prevalence of smoking — a modelling study. Lung Cancer 121, 61–69 (2018).

    PubMed  Google Scholar 

  120. Kumar, V. et al. Risk-targeted lung cancer screening a cost-effectiveness analysis. Ann. Intern. Med. 168, 161–169 (2018).

    PubMed  PubMed Central  Google Scholar 

  121. Hinde, S. et al. The cost-effectiveness of the Manchester ‘lung health checks’, a community-based lung cancer low-dose CT screening pilot. Lung Cancer 126, 119–124 (2018).

    PubMed  Google Scholar 

  122. Snowsill, T. et al. Low-dose computed tomography for lung cancer screening in high-risk populations: a systematic review and economic evaluation. Health Technol. Assess. 22, 1–276 (2018).

    PubMed  PubMed Central  Google Scholar 

  123. Whynes, D. K. Could CT screening for lung cancer ever be cost effective in the United Kingdom? Cost Eff. Resour. Alloc. 6, 5 (2008).

    PubMed  PubMed Central  Google Scholar 

  124. Zeng, H. et al. Changing cancer survival in China during 2003–15: a pooled analysis of 17 population-based cancer registries. Lancet Glob. Health 6, e555–e567 (2018).

    PubMed  Google Scholar 

  125. Chen, W. et al. Cancer incidence and mortality in China, 2014. Chin. J. Cancer Res. 30, 1–12 (2018).

    PubMed  PubMed Central  Google Scholar 

  126. Martín-Sánchez, J. C. et al. Projections in breast and lung cancer mortality among women: a Bayesian analysis of 52 countries worldwide. Cancer Res. 78, 4436–4442 (2018).

    PubMed  Google Scholar 

  127. Cheng, Y. I., Davies, M. P. A., Liu, D., Li, W. & Field, J. K. Implementation planning for lung cancer screening in China. Precis. Clin. Med. 2, 13–44 (2019).

    Google Scholar 

  128. Zhou, Q. et al. Demonstration program of population-based lung cancer screening in China: Rationale and study design. Thorac. Cancer 5, 197–203 (2014).

    PubMed  PubMed Central  Google Scholar 

  129. Wang, Z. et al. Mortality outcomes of low-dose computed tomography screening for lung cancer in urban China: a decision analysis and implications for practice. Chin. J. Cancer 36, 57 (2017).

    PubMed  PubMed Central  Google Scholar 

  130. Fan, L. et al. Lung cancer screening with low-dose CT: baseline screening results in Shanghai. Acad. Radiol. 26, 1283–1291 (2019).

    PubMed  Google Scholar 

  131. Luo, X. et al. Should nonsmokers be excluded from early lung cancer screening with low-dose spiral computed tomography? community-based practice in Shanghai. Transl Oncol. 10, 485–490 (2017).

    PubMed  PubMed Central  Google Scholar 

  132. Nawa, T. et al. A decrease in lung cancer mortality following the introduction of low-dose chest CT screening in Hitachi, Japan. Lung Cancer 78, 225–228 (2012).

    PubMed  Google Scholar 

  133. Sagawa, M. et al. Efficacy of low-dose computed tomography screening for lung cancer: the current state of evidence of mortality reduction. Surg. Today 47, 783–788 (2017).

    PubMed  Google Scholar 

  134. Nawa, T. et al. A population-based cohort study to evaluate the effectiveness of lung cancer screening using low-dose CT in Hitachi city, Japan. Jpn. J. Clin. Oncol. 49, 130–136 (2019).

    PubMed  Google Scholar 

  135. Lee, J. et al. Development of protocol for Korean Lung Cancer Screening Project (K-LUCAS) to evaluate effectiveness and feasibility to implement national cancer screening program. Cancer Res. Treat. 51, 1285–1294 (2019).

    PubMed  PubMed Central  Google Scholar 

  136. The Royal College of Radiologists. www.rcr.ac.uk/publication/clinical-radiology-uk-workforce-census-report-2018 (2019).

  137. Ather, S., Kadir, T. & Gleeson, F. Artificial intelligence and radiomics in pulmonary nodule management: current status and future applications. Clin. Radiol. 75, 13–19 (2020).

    CAS  PubMed  Google Scholar 

  138. Christe, A. et al. Lung cancer screening with CT: Evaluation of radiologists anddifferent computer assisted detection software (CAD) as first and second readers for lung nodule detection at different dose levels. Eur. J. Radiol. 82, e873–8 (2013).

    CAS  PubMed  Google Scholar 

  139. Wang, Y. et al. No benefit for consensus double reading at baseline screening for lung cancer with the use of semiautomated volumetry software. Radiology 262, 320–326 (2012).

    PubMed  Google Scholar 

  140. Liang, M. et al. Low-dose CT screening for lung cancer: computer-aided detection of missed lung cancers. Radiology 281, 279–288 (2016).

    PubMed  Google Scholar 

  141. Vlahos, I. et al. Lung cancer screening: Nodule identification and characterization. Transl Lung Cancer Res. 7, 288–303 (2018).

    PubMed  PubMed Central  Google Scholar 

  142. Ebner, L. et al. Maximum-intensity-projection and computer-aided-detection algorithms as stand-alone reader devices in lung cancer screening using different dose levels and reconstruction kernels. Am. J. Roentgenol. 207, 282–288 (2016).

    Google Scholar 

  143. Ciompi, F. et al. Towards automatic pulmonary nodule management in lung cancer screening with deep learning. Sci. Rep. 7, 46479 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  144. Ardila, D. et al. End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nat. Med. 25, 954–961 (2019).

    CAS  PubMed  Google Scholar 

  145. Huang, P. et al. Prediction of lung cancer risk at follow-up screening with low-dose CT: a training and validation study of a deep learning method. Lancet Digit. Health 1, e353–e362 (2019).

    PubMed  PubMed Central  Google Scholar 

  146. Baldwin, D. R. et al. External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodules. Thorax 75, 306–312 (2020).

    PubMed  Google Scholar 

  147. Liu, K. et al. Evaluating a fully automated pulmonary nodule detection approach and its impact on radiologist performance. Radiol. Artif. Intell. https://doi.org/10.1148/ryai.2019180084 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  148. Duffy, S. W. & Field, J. K. Mortality reduction with low-dose CT screening for lung cancer. N. Engl. J. Med. 382, 572–573 (2020).

    PubMed  Google Scholar 

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Authors and Affiliations

  1. Institute of Diagnostic Accuracy (iDNA), Groningen, Netherlands

    Matthijs Oudkerk

  2. Faculty of Medical Sciences, University of Groningen, Groningen, Netherlands

    Matthijs Oudkerk

  3. Department of Radiology, Changzheng Hospital, Second Military Medical University, Shanghai, China

    ShiYuan Liu

  4. Department of Pulmonary Diseases, Medisch Spectrum Twente, Enschede, Netherlands

    Marjolein A. Heuvelmans

  5. Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands

    Marjolein A. Heuvelmans

  6. Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland

    Joan E. Walter

  7. Roy Castle Lung Cancer Research Programme, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, UK

    John K. Field

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M.O. contributed to all aspects of the preparation of this article. S.L. and J.E.W. researched data. M.A.H. contributed to discussions, researched data and supported the draft of the manuscript. J.K.F. contributed to all aspects of the preparation of this article. The final manuscript was approved by all authors.

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Oudkerk, M., Liu, S., Heuvelmans, M.A. et al. Lung cancer LDCT screening and mortality reduction — evidence, pitfalls and future perspectives. Nat Rev Clin Oncol 18, 135–151 (2021). https://doi.org/10.1038/s41571-020-00432-6

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