Optimal Pathways to Lung Cancer Screening in Primary Care Settings: A Scoping Review
Abstract
:1. Introduction
2. Materials and Methods
2.1. Methodological Approach
2.2. Information Sources and Study Selection
2.3. Data Synthesis and Analysis
3. Results
3.1. Screening and Procedure
3.2. Overview Characteristics of the Included Studies
3.3. Description of Interventions Implemented to Facilitate the Uptake of LCS
3.4. Efficiency and Levels of Lung Cancer Screening
3.5. Detection of Lung Cancer
3.6. Engagement of GPs with Lung Cancer Early Detection and Referral
4. Discussion
Limitations
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Bray, F.; Laversanne, M.; Sung, H.; Ferlay, J.; Siegel, R.L.; Soerjomataram, I.; Jemal, A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA A Cancer J. Clin. 2024, 74, 229–263. [Google Scholar] [CrossRef]
- Bradley, S.H.; Kennedy, M.P.; Neal, R.D. Recognising lung cancer in primary care. Adv. Ther. 2019, 36, 19–30. [Google Scholar] [CrossRef] [PubMed]
- McPhail, S.; Johnson, S.; Greenberg, D.; Peake, M.; Rous, B. Stage at diagnosis and early mortality from cancer in England. Br. J. Cancer 2015, 112, S108–S115. [Google Scholar] [CrossRef]
- Allemani, C.; Matsuda, T.; Di Carlo, V.; Harewood, R.; Matz, M.; Nikšić, M.; Bonaventure, A.; Valkov, M.; Johnson, C.J.; Estève, J. Global surveillance of trends in cancer survival 2000–14 (CONCORD-3): Analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries. Lancet 2018, 391, 1023–1075. [Google Scholar] [CrossRef]
- Araghi, M.; Fidler-Benaoudia, M.; Arnold, M.; Rutherford, M.; Bardot, A.; Ferlay, J.; Bucher, O.; De, P.; Engholm, G.; Gavin, A. International differences in lung cancer survival by sex, histological type and stage at diagnosis: An ICBP SURVMARK-2 Study. Thorax 2022, 77, 378–390. [Google Scholar] [CrossRef]
- Tsiligianni, I.; Christodoulakis, A.; Monastirioti, A.; Mavroudis, D.; Agelaki, S. The journey of lung cancer patients from symptoms to diagnosis in Greece. A mixed methods approach. npj Prim. Care Respir. Med. 2024, 34, 5. [Google Scholar] [CrossRef]
- Hamilton, W. Five misconceptions in cancer diagnosis. Br. J. Gen. Pract. 2009, 59, 441–447. [Google Scholar] [CrossRef]
- Demagny, L.; Holtedahl, K.; Bachimont, J.; Thorsen, T.; Letourmy, A.; Bungener, M. General practitioners’ role in cancer care: A French-Norwegian study. BMC Res. Notes 2009, 2, 200. [Google Scholar] [CrossRef] [PubMed]
- Tørring, M.L.; Frydenberg, M.; Hansen, R.P.; Olesen, F.; Vedsted, P. Evidence of increasing mortality with longer diagnostic intervals for five common cancers: A cohort study in primary care. Eur. J. Cancer 2013, 49, 2187–2198. [Google Scholar] [CrossRef] [PubMed]
- Ewing, M.; Naredi, P.; Nemes, S.; Zhang, C.; Månsson, J. Increased consultation frequency in primary care, a risk marker for cancer: A case–control study. Scand. J. Prim. Health Care 2016, 34, 205–212. [Google Scholar] [CrossRef]
- Thompson, C.L.; Buchanan, A.H.; Myers, R.; Weinberg, D.S. Integrating primary care, shared decision making, and community engagement to facilitate equitable access to multi-cancer early detection clinical trials. Front. Oncol. 2023, 13, 1307459. [Google Scholar] [CrossRef] [PubMed]
- Saab, M.M.; McCarthy, M.; O’Driscoll, M.; Sahm, L.J.; Leahy-Warren, P.; Noonan, B.; FitzGerald, S.; O’Malley, M.; Lyons, N.; Burns, H.E.; et al. A systematic review of interventions to recognise, refer and diagnose patients with lung cancer symptoms. npj Prim. Care Respir. Med. 2022, 32, 42. [Google Scholar] [CrossRef]
- Jacobsen, M.M.; Silverstein, S.C.; Quinn, M.; Waterston, L.B.; Thomas, C.A.; Benneyan, J.C.; Han, P.K.J. Timeliness of access to lung cancer diagnosis and treatment: A scoping literature review. Lung Cancer 2017, 112, 156–164. [Google Scholar] [CrossRef]
- Iyen-Omofoman, B.; Tata, L.J.; Baldwin, D.R.; Smith, C.J.; Hubbard, R.B. Using socio-demographic and early clinical features in general practice to identify people with lung cancer earlier. Thorax 2013, 68, 451–459. [Google Scholar] [CrossRef] [PubMed]
- Lyratzopoulos, G.; Abel, G.; McPhail, S.; Neal, R.; Rubin, G. Measures of promptness of cancer diagnosis in primary care: Secondary analysis of national audit data on patients with 18 common and rarer cancers. Br. J. Cancer 2013, 108, 686–690. [Google Scholar] [CrossRef] [PubMed]
- Guerreiro, T.; Aguiar, P.; Araújo, A. Current evidence for a lung cancer screening program. Port. J. Public Health 2024, 42, 133–158. [Google Scholar] [CrossRef]
- The National Lung Screening Trial Research Team. Lung cancer incidence and mortality with extended follow-up in the National Lung Screening Trial. J. Thorac. Oncol. 2019, 14, 1732–1742. [Google Scholar] [CrossRef]
- de Koning, H.J.; van Der Aalst, C.M.; de Jong, P.A.; Scholten, E.T.; Nackaerts, K.; Heuvelmans, M.A.; Lammers, J.-W.J.; Weenink, C.; Yousaf-Khan, U.; Horeweg, N. Reduced lung-cancer mortality with volume CT screening in a randomized trial. N. Engl. J. Med. 2020, 382, 503–513. [Google Scholar] [CrossRef]
- U.S. Preventive Services Task Force. Lung Cancer: Screening. Available online: https://www.uspreventiveservicestaskforce.org/uspstf/recommendation/lung-cancer-screening (accessed on 15 October 2024).
- American Cancer Society Cancer Prevention and Early Detection Guidelines. Lung Cancer Screening Guidelines. Available online: https://www.cancer.org/health-care-professionals/american-cancer-society-prevention-early-detection-guidelines/lung-cancer-screening-guidelines.html (accessed on 20 October 2024).
- European Commission. Questions and Answers: A New EU Approach to Cancer Screening. Available online: https://ec.europa.eu/commission/presscorner/detail/en/qanda_22_5584 (accessed on 18 October 2024).
- Otty, Z.; Brown, A.; Sabesan, S.; Evans, R.; Larkins, S. Optimal Care Pathways for People with Lung Cancer- a Scoping Review of the Literature. Int. J. Integr. Care 2020, 20, 14. [Google Scholar] [CrossRef] [PubMed]
- Rankin, N.M.; McGregor, D.; Stone, E.; Butow, P.N.; Young, J.M.; White, K.; Shaw, T. Evidence-practice gaps in lung cancer: A scoping review. Eur. J. Cancer Care 2018, 27, e12588. [Google Scholar] [CrossRef] [PubMed]
- Olazagasti, C.; Ehrlich, M.; Kohn, N.; Aviles, K.; Hoilett, A.; Seetharamu, N. Missed opportunities? An observational analysis of lung cancer screening utilization amongst patients with lung cancer. Cancer Control 2022, 29, 10732748221077959. [Google Scholar] [CrossRef] [PubMed]
- Lubuzo, B.; Ginindza, T.; Hlongwana, K. The barriers to initiating lung cancer care in low-and middle-income countries. Pan Afr. Med. J. 2020, 35, 38. [Google Scholar] [CrossRef]
- Reese, T.J.; Schlechter, C.R.; Kramer, H.; Kukhareva, P.; Weir, C.R.; Del Fiol, G.; Caverly, T.; Hess, R.; Flynn, M.C.; Taft, T. Implementing lung cancer screening in primary care: Needs assessment and implementation strategy design. Transl. Behav. Med. 2022, 12, 187–197. [Google Scholar] [CrossRef]
- Wagland, R.; Brindle, L.; James, E.; Moore, M.; Esqueda, A.; Corner, J. Facilitating early diagnosis of lung cancer amongst primary care patients: The views of GPs. Eur. J. Cancer Care 2017, 26, e12704. [Google Scholar] [CrossRef] [PubMed]
- Peters, M.D.; Godfrey, C.; McInerney, P.; Munn, Z.; Tricco, A.C.; Khalil, H. Chapter 11: Scoping reviews. JBI Man. Evid. Synth. 2020, 169, 467–473. [Google Scholar]
- Tricco, A.C.; Lillie, E.; Zarin, W.; O’Brien, K.K.; Colquhoun, H.; Levac, D.; Moher, D.; Peters, M.D.J.; Horsley, T.; Weeks, L.; et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann. Intern. Med. 2018, 169, 467–473. [Google Scholar] [CrossRef]
- Azubuike, U.C.; Cooper, D.; Aplin-Snider, C. Using United States preventive services task force guidelines to improve a family medicine clinic’s lung cancer screening rates: A quality improvement project. J. Nurse Pract. 2020, 16, e169–e172. [Google Scholar] [CrossRef]
- Brenner, A.T.; Cubillos, L.; Birchard, K.; Doyle-Burr, C.; Eick, J.; Henderson, L.; Jones, L.; Massaro, M.; Minish, B.; Molina, P. Improving the implementation of lung cancer screening guidelines at an academic primary care practice. J. Healthc. Qual. (JHQ) 2018, 40, 27–35. [Google Scholar] [CrossRef]
- Colamonici, M.; Khouzam, N.; Dell, C.; Auge-Bronersky, K.; Pacheco, E.; Rubinstein, I.; Recht, B. Promoting lung cancer screening of high-risk patients by primary care providers. Cancer 2023, 129, 3574–3581. [Google Scholar] [CrossRef]
- Chiarantano, R.S.; Vazquez, F.L.; Franco, A.; Ferreira, L.C.; Cristina da Costa, M.; Talarico, T.; Oliveira, Â.N.; Miziara, J.E.; Mauad, E.C.; Caetano da Silva, E.; et al. Implementation of an Integrated Lung Cancer Prevention and Screening Program Using a Mobile Computed Tomography (CT) Unit in Brazil. Cancer Control 2022, 29, 10732748221121385. [Google Scholar] [CrossRef]
- Crosbie, P.A.J.; Gabe, R.; Simmonds, I.; Hancock, N.; Alexandris, P.; Kennedy, M.; Rogerson, S.; Baldwin, D.; Booton, R.; Bradley, C.; et al. Participation in community-based lung cancer screening: The Yorkshire Lung Screening Trial. Eur. Respir. J. 2022, 60, 2200483. [Google Scholar] [CrossRef] [PubMed]
- Currier, J.; Howes, D.; Cox, C.; Bertoldi, M.; Sharman, K.; Cook, B.; Baden, D.; Farris, P.E.; Stoller, W.; Shannon, J. A Coordinated Approach to Implementing Low-Dose CT Lung Cancer Screening in a Rural Community Hospital. J. Am. Coll. Radiol. 2022, 19, 757–768. [Google Scholar] [CrossRef]
- DiCarlo, M.; Myers, P.; Daskalakis, C.; Shimada, A.; Hegarty, S.; Zeigler-Johnson, C.; Juon, H.-S.; Barta, J.; Myers, R.E. Outreach to primary care patients in lung cancer screening: A randomized controlled trial. Prev. Med. 2022, 159, 107069. [Google Scholar] [CrossRef]
- Fagan, H.B.; Fournakis, N.A.; Jurkovitz, C.; Petrich, A.M.; Zhang, Z.; Katurakes, N.; Myers, R.E. Telephone-based shared decision-making for lung cancer screening in primary care. J. Cancer Educ. 2020, 35, 766–773. [Google Scholar] [CrossRef] [PubMed]
- Goodley, P.; Balata, H.; Alonso, A.; Brockelsby, C.; Conroy, M.; Cooper-Moss, N.; Craig, C.; Evison, M.; Hewitt, K.; Higgins, C.; et al. Invitation strategies and participation in a community-based lung cancer screening programme located in areas of high socioeconomic deprivation. Thorax 2023, 79, 58–67. [Google Scholar] [CrossRef]
- Jani, B.D.; Sullivan, M.K.; Hanlon, P.; Nicholl, B.I.; Lees, J.S.; Brown, L.; MacDonald, S.; Mark, P.B.; Mair, F.S.; Sullivan, F.M. Personalised lung cancer risk stratification and lung cancer screening: Do general practice electronic medical records have a role? Br. J. Cancer 2023, 129, 1968–1977. [Google Scholar] [CrossRef] [PubMed]
- Kukhareva, P.V.; Li, H.; Caverly, T.J.; Del Fiol, G.; Fagerlin, A.; Butler, J.M.; Hess, R.; Zhang, Y.; Taft, T.; Flynn, M.C. Implementation of lung cancer screening in primary care and pulmonary clinics: Pragmatic clinical trial of electronic health record-integrated everyday shared decision-making tool and clinician-facing prompts. Chest 2023, 164, 1325–1338. [Google Scholar] [CrossRef]
- Liu, S.; McCoy, A.B.; Aldrich, M.C.; Sandler, K.L.; Reese, T.J.; Steitz, B.; Bian, J.; Wu, Y.; Russo, E.; Wright, A. Leveraging natural language processing to identify eligible lung cancer screening patients with the electronic health record. Int. J. Med. Inf. 2023, 177, 105136. [Google Scholar] [CrossRef]
- O’Brien, M.A.; Sullivan, F.; Carson, A.; Siddiqui, R.; Syed, S.; Paszat, L. Piloting electronic screening forms in primary care: Findings from a mixed methods study to identify patients eligible for low dose CT lung cancer screening. BMC Fam. Pract. 2017, 18, 95. [Google Scholar] [CrossRef]
- Ostrowski, M.; Bińczyk, F.; Marjański, T.; Dziedzic, R.; Pisiak, S.; Małgorzewicz, S.; Adamek, M.; Polańska, J.; Rzyman, W. Performance of various risk prediction models in a large lung cancer screening cohort in Gdańsk, Poland-a comparative study. Transl. Lung Cancer Res. 2021, 10, 1083–1090. [Google Scholar] [CrossRef]
- Park, B.; Kim, Y.; Lee, J.; Lee, N.; Jang, S.H. Risk-based prediction model for selecting eligible population for lung cancer screening among ever smokers in Korea. Transl. Lung Cancer Res. 2021, 10, 4390–4402. [Google Scholar] [CrossRef] [PubMed]
- Percac-Lima, S.; Ashburner, J.M.; Rigotti, N.A.; Park, E.R.; Chang, Y.; Kuchukhidze, S.; Atlas, S.J. Patient navigation for lung cancer screening among current smokers in community health centers a randomized controlled trial. Cancer Med. 2018, 7, 894–902. [Google Scholar] [CrossRef] [PubMed]
- Reuland, D.S.; Cubillos, L.; Brenner, A.T.; Harris, R.P.; Minish, B.; Pignone, M.P. A pre-post study testing a lung cancer screening decision aid in primary care. BMC Med. Inform. Decis. Mak. 2018, 18, 5. [Google Scholar] [CrossRef]
- Schapira, M.M.; Hubbard, R.A.; Whittle, J.; Vachani, A.; Kaminstein, D.; Chhatre, S.; Rodriguez, K.L.; Bastian, L.A.; Kravetz, J.D.; Asan, O. Lung cancer screening decision aid designed for a primary care setting: A randomized clinical trial. JAMA Netw. Open 2023, 6, e2330452. [Google Scholar] [CrossRef] [PubMed]
- American College of Radiology. Lung-RADS® Version 1.1. Available online: https://www.acr.org/-/media/ACR/Files/RADS/Lung-RADS/LungRADSAssessmentCategoriesv1-1.pdf (accessed on 21 October 2024).
- Atkinson, M.D.; Kennedy, J.I.; John, A.; Lewis, K.E.; Lyons, R.A.; Brophy, S.T.; on behalf of the DEMISTIFY Research Group. Development of an algorithm for determining smoking status and behaviour over the life course from UK electronic primary care records. BMC Med. Inform. Decis. Mak. 2017, 17, 2. [Google Scholar] [CrossRef] [PubMed]
- Modin, H.E.; Fathi, J.T.; Gilbert, C.R.; Wilshire, C.L.; Wilson, A.K.; Aye, R.W.; Farivar, A.S.; Louie, B.E.; Vallières, E.; Gorden, J.A. Pack-year cigarette smoking history for determination of lung cancer screening eligibility. Comparison of the electronic medical record versus a shared decision-making conversation. Ann. Am. Thorac. Soc. 2017, 14, 1320–1325. [Google Scholar] [CrossRef] [PubMed]
- Dineen, M.; Sidaway-Lee, K.; Pereira Gray, D.; Evans, P.H. Family history recording in UK general practice: The lIFeLONG study. Fam. Pract. 2022, 39, 610–615. [Google Scholar] [CrossRef]
- O’dowd, E.L.; Lee, R.W.; Akram, A.R.; Bartlett, E.C.; Bradley, S.H.; Brain, K.; Callister, M.E.; Chen, Y.; Devaraj, A.; Eccles, S.R. Defining the road map to a UK national lung cancer screening programme. Lancet Oncol. 2023, 24, e207–e218. [Google Scholar] [CrossRef]
- O’Dowd, E.L.; Ten Haaf, K.; Kaur, J.; Duffy, S.W.; Hamilton, W.; Hubbard, R.B.; Field, J.K.; Callister, M.E.; Janes, S.M.; de Koning, H.J. Selection of eligible participants for screening for lung cancer using primary care data. Thorax 2022, 77, 882–890. [Google Scholar] [CrossRef]
- Burzic, A.; O’Dowd, E.L.; Baldwin, D.R. The future of lung cancer screening: Current challenges and research priorities. Cancer Manag. Res. 2022, 14, 637–645. [Google Scholar] [CrossRef] [PubMed]
- Baldwin, D.R.; Brain, K.; Quaife, S. Participation in lung cancer screening. Transl. Lung Cancer Res. 2021, 10, 1091. [Google Scholar] [CrossRef]
- Lopez-Olivo, M.A.; Maki, K.G.; Choi, N.J.; Hoffman, R.M.; Shih, Y.-C.T.; Lowenstein, L.M.; Hicklen, R.S.; Volk, R.J. Patient adherence to screening for lung cancer in the US: A systematic review and meta-analysis. JAMA Netw. Open 2020, 3, e2025102. [Google Scholar] [CrossRef]
- Dickson, J.L.; Hall, H.; Horst, C.; Tisi, S.; Verghese, P.; Mullin, A.M.; Teague, J.; Farrelly, L.; Bowyer, V.; Gyertson, K.; et al. Uptake of invitations to a lung health check offering low-dose CT lung cancer screening among an ethnically and socioeconomically diverse population at risk of lung cancer in the UK (SUMMIT): A prospective, longitudinal cohort study. Lancet Public Health 2023, 8, e130–e140. [Google Scholar] [CrossRef] [PubMed]
- Polubriaginof, F.; Salmasian, H.; Albert, D.A.; Vawdrey, D.K. Challenges with collecting smoking status in electronic health records. In Proceedings of the AMIA Annual Symposium Proceedings, Washington, DC, USA, 4–8 November 2017; p. 1392. [Google Scholar]
- Tildy, B.E.; McNeill, A.; Robins, J.; Dregan, A.; Richardson, S.; Brose, L.S. How is nicotine vaping product (e-cigarette) use monitored in primary care electronic health records in the United Kingdom? An exploratory analysis of Clinical Practice Research Datalink (CPRD). BMC Public Health 2023, 23, 2263. [Google Scholar] [CrossRef]
- Sanford, B.T.; Rojewski, A.M.; Palmer, A.M.; Baker, N.L.; Carpenter, M.J.; Smith, T.T.; Toll, B.A. E-Cigarette Screening in Primary Care. Am. J. Prev. Med. 2023, 65, 517–520. [Google Scholar] [CrossRef] [PubMed]
- Bracken-Clarke, D.; Kapoor, D.; Baird, A.M.; Buchanan, P.J.; Gately, K.; Cuffe, S.; Finn, S.P. Vaping and lung cancer—A review of current data and recommendations. Lung Cancer 2021, 153, 11–20. [Google Scholar] [CrossRef] [PubMed]
- Jankowski, M.; Krzystanek, M.; Zejda, J.E.; Majek, P.; Lubanski, J.; Lawson, J.A.; Brozek, G. E-Cigarettes are More Addictive than Traditional Cigarettes-A Study in Highly Educated Young People. Int. J. Env. Res. Public Health 2019, 16, 2279. [Google Scholar] [CrossRef] [PubMed]
- Patel, U.; Patel, N.; Khurana, M.; Parulekar, A.; Patel, A.; Ortiz, J.F.; Patel, R.; Urhoghide, E.; Mistry, A.; Bhriguvanshi, A.; et al. Effect Comparison of E-Cigarette and Traditional Smoking and Association with Stroke-A Cross-Sectional Study of NHANES. Neurol. Int. 2022, 14, 441–452. [Google Scholar] [CrossRef] [PubMed]
- McCutchan, G.; Engela-Volker, J.; Anyanwu, P.; Brain, K.; Abel, N.; Eccles, S. Assessing, updating and utilising primary care smoking records for lung cancer screening. BMC Pulm. Med. 2023, 23, 445. [Google Scholar] [CrossRef] [PubMed]
- Katki, H.A.; Kovalchik, S.A.; Petito, L.C.; Cheung, L.C.; Jacobs, E.; Jemal, A.; Berg, C.D.; Chaturvedi, A.K. Implications of nine risk prediction models for selecting ever-smokers for computed tomography lung cancer screening. Ann. Intern. Med. 2018, 169, 10–19. [Google Scholar] [CrossRef] [PubMed]
- Oudkerk, M.; Devaraj, A.; Vliegenthart, R.; Henzler, T.; Prosch, H.; Heussel, C.P.; Bastarrika, G.; Sverzellati, N.; Mascalchi, M.; Delorme, S. European position statement on lung cancer screening. Lancet Oncol. 2017, 18, e754–e766. [Google Scholar] [CrossRef] [PubMed]
- Aberle, D.R.; Adams, A.M.; Berg, C.D.; Black, W.C.; Clapp, J.D.; Fagerstrom, R.M.; Gareen, I.F.; Gatsonis, C.; Marcus, P.M.; Sicks, J.D. Reduced lung-cancer mortality with low-dose computed tomographic screening. N. Engl. J. Med. 2011, 365, 395–409. [Google Scholar] [CrossRef] [PubMed]
- Field, J.K.; Duffy, S.W.; Baldwin, D.R.; Brain, K.E.; Devaraj, A.; Eisen, T.; Green, B.A.; Holemans, J.A.; Kavanagh, T.; Kerr, K.M. 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. 2016, 20, 1. [Google Scholar] [CrossRef]
- Paci, E.; Puliti, D.; Pegna, A.L.; Carrozzi, L.; Picozzi, G.; Falaschi, F.; Pistelli, F.; Aquilini, F.; Ocello, C.; Zappa, M. Mortality, survival and incidence rates in the ITALUNG randomised lung cancer screening trial. Thorax 2017, 72, 825–831. [Google Scholar] [CrossRef] [PubMed]
- Sullivan, F.M.; Mair, F.S.; Anderson, W.; Armory, P.; Briggs, A.; Chew, C.; Dorward, A.; Haughney, J.; Hogarth, F.; Kendrick, D. Earlier diagnosis of lung cancer in a randomised trial of an autoantibody blood test followed by imaging. Eur. Respir. J. 2021, 57, 2000670. [Google Scholar] [CrossRef] [PubMed]
- Bernstein, E.; Bade, B.C.; Akgün, K.M.; Rose, M.G.; Cain, H.C. Barriers and facilitators to lung cancer screening and follow-up. Semin. Oncol. 2022, 49, 213–219. [Google Scholar] [CrossRef] [PubMed]
- Ten Haaf, K.; van der Aalst, C.M.; de Koning, H.J.; Kaaks, R.; Tammemägi, M.C. Personalising lung cancer screening: An overview of risk-stratification opportunities and challenges. Int. J. Cancer 2021, 149, 250–263. [Google Scholar] [CrossRef] [PubMed]
- Ten Haaf, K.; Jeon, J.; Tammemägi, M.C.; Han, S.S.; Kong, C.Y.; Plevritis, S.K.; Feuer, E.J.; de Koning, H.J.; Steyerberg, E.W.; Meza, R. Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study. PLoS Med. 2017, 14, e1002277. [Google Scholar] [CrossRef] [PubMed]
- Kim, Y.; Lee, J.; Lee, E.; Lim, J.; Kim, Y.; Lee, C.-T.; Jang, S.H.; Paek, Y.-J.; Lee, W.-C.; Lee, C.W. Strategies to Improve Smoking Cessation for Participants in Lung Cancer Screening Program: Analysis of Factors Associated with Smoking Cessation in Korean Lung Cancer Screening Project (K-LUCAS). Cancer Res. Treat. Off. J. Korean Cancer Assoc. 2024, 56, 92. [Google Scholar] [CrossRef]
- McMahon, P.M.; Kong, C.Y.; Bouzan, C.; Weinstein, M.C.; Cipriano, L.E.; Tramontano, A.C.; Johnson, B.E.; Weeks, J.C.; Gazelle, G.S. Cost-effectiveness of computed tomography screening for lung cancer in the United States. J. Thorac. Oncol. 2011, 6, 1841–1848. [Google Scholar] [CrossRef]
- Becker, N.; Motsch, E.; Trotter, A.; Heussel, C.P.; Dienemann, H.; Schnabel, P.A.; Kauczor, H.U.; Maldonado, S.G.; Miller, A.B.; Kaaks, R. Lung cancer mortality reduction by LDCT screening—Results from the randomized German LUSI trial. Int. J. Cancer 2020, 146, 1503–1513. [Google Scholar] [CrossRef] [PubMed]
- Pham, D.; Bhandari, S.; Oechsli, M.; Pinkston, C.M.; Kloecker, G.H. Lung cancer screening rates: Data from the lung cancer screening registry. J. Clin. Oncol. 2018, 36, 15. [Google Scholar] [CrossRef]
- Fedewa, S.A.; Kazerooni, E.A.; Studts, J.L.; Smith, R.A.; Bandi, P.; Sauer, A.G.; Cotter, M.; Sineshaw, H.M.; Jemal, A.; Silvestri, G.A. State variation in low-dose computed tomography scanning for lung cancer screening in the United States. JNCI J. Natl. Cancer Inst. 2021, 113, 1044–1052. [Google Scholar] [CrossRef] [PubMed]
- Pinsky, P.F.; Miller, E. Use and outcomes of low-dose CT scan lung cancer screening in the medicare population. Chest 2022, 162, 721–729. [Google Scholar] [CrossRef] [PubMed]
- 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 2020, 21, e206–e211. [Google Scholar] [CrossRef]
- Carter-Harris, L.; Gould, M.K. Multilevel barriers to the successful implementation of lung cancer screening: Why does it have to be so hard? Ann. Am. Thorac. Soc. 2017, 14, 1261–1265. [Google Scholar] [CrossRef]
- Coughlin, J.M.; Zang, Y.; Terranella, S.; Alex, G.; Karush, J.; Geissen, N.; Chmielewski, G.W.; Arndt, A.T.; Liptay, M.J.; Zimmermann, L.J. Understanding barriers to lung cancer screening in primary care. J. Thorac. Dis. 2020, 12, 2536. [Google Scholar] [CrossRef]
- Tarnoki, A.D.; Tarnoki, D.L.; Dabrowska, M.; Knetki-Wroblewska, M.; Frille, A.; Stubbs, H.; Blyth, K.G.; Juul, A.D. New developments in the imaging of lung cancer. Breathe 2024, 20, 230176. [Google Scholar] [CrossRef]
- Bradley, S.H.; Abraham, S.; Callister, M.E.; Grice, A.; Hamilton, W.T.; Lopez, R.R.; Shinkins, B.; Neal, R.D. Sensitivity of chest X-ray for detecting lung cancer in people presenting with symptoms: A systematic review. Br. J. Gen. Pr. 2019, 69, e827–e835. [Google Scholar] [CrossRef]
- Nam, J.G.; Hwang, E.J.; Kim, J.; Park, N.; Lee, E.H.; Kim, H.J.; Nam, M.; Lee, J.H.; Park, C.M.; Goo, J.M. AI Improves Nodule Detection on Chest Radiographs in a Health Screening Population: A Randomized Controlled Trial. Radiology 2023, 307, e221894. [Google Scholar] [CrossRef] [PubMed]
- Birring, S.; Peake, M. Symptoms and the early diagnosis of lung cancer. Thorax 2005, 60, 268–269. [Google Scholar] [CrossRef] [PubMed]
- Rubin, K.H.; Haastrup, P.F.; Nicolaisen, A.; Möller, S.; Wehberg, S.; Rasmussen, S.; Balasubramaniam, K.; Søndergaard, J.; Jarbøl, D.E. Developing and validating a lung cancer risk prediction model: A nationwide population-based study. Cancers 2023, 15, 487. [Google Scholar] [CrossRef] [PubMed]
- Henderson, S.; DeGroff, A.; Richards, T.B.; Kish-Doto, J.; Soloe, C.; Heminger, C.; Rohan, E. A qualitative analysis of lung cancer screening practices by primary care physicians. J. Community Health 2011, 36, 949–956. [Google Scholar] [CrossRef]
- Brenner, A.; Howard, K.; Lewis, C.; Sheridan, S.; Crutchfield, T.; Hawley, S.; Reuland, D.; Kistler, C.; Pignone, M. Comparing 3 values clarification methods for colorectal cancer screening decision-making: A randomized trial in the US and Australia. J. Gen. Intern. Med. 2014, 29, 507–513. [Google Scholar] [CrossRef] [PubMed]
- Japuntich, S.J.; Krieger, N.H.; Salvas, A.L.; Carey, M.P. Racial disparities in lung cancer screening: An exploratory investigation. J. Natl. Med. Assoc. 2018, 110, 424–427. [Google Scholar] [CrossRef]
- Carter-Harris, L.; Slaven Jr, J.E.; Monahan, P.O.; Shedd-Steele, R.; Hanna, N.; Rawl, S.M. Understanding lung cancer screening behavior: Racial, gender, and geographic differences among Indiana long-term smokers. Prev. Med. Rep. 2018, 10, 49–54. [Google Scholar] [CrossRef] [PubMed]
- Tangka, F.K.; Subramanian, S.; Mobley, L.R.; Hoover, S.; Wang, J.; Hall, I.J.; Singh, S.D. Racial and ethnic disparities among state Medicaid programs for breast cancer screening. Prev. Med. 2017, 102, 59–64. [Google Scholar] [CrossRef] [PubMed]
- Tanner, N.T.; Gebregziabher, M.; Hughes Halbert, C.; Payne, E.; Egede, L.E.; Silvestri, G.A. Racial differences in outcomes within the National Lung Screening Trial. Implications for widespread implementation. Am. J. Respir. Crit. Care Med. 2015, 192, 200–208. [Google Scholar] [CrossRef] [PubMed]
- Wools, A.; Dapper, E.; Leeuw, J.d. Colorectal cancer screening participation: A systematic review. Eur. J. Public Health 2016, 26, 158–168. [Google Scholar] [CrossRef] [PubMed]
- Wender, R.; Fontham, E.T.; Barrera, E., Jr.; Colditz, G.A.; Church, T.R.; Ettinger, D.S.; Etzioni, R.; Flowers, C.R.; Scott Gazelle, G.; Kelsey, D.K. American Cancer Society lung cancer screening guidelines. CA A Cancer J. Clin. 2013, 63, 106–117. [Google Scholar] [CrossRef]
- Smith, R.A.; Andrews, K.S.; Brooks, D.; Fedewa, S.A.; Manassaram-Baptiste, D.; Saslow, D.; Brawley, O.W.; Wender, R.C. Cancer screening in the United States, 2018: A review of current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J. Clin. 2018, 68, 297–316. [Google Scholar] [CrossRef] [PubMed]
- Cheung, L.C.; Katki, H.A.; Chaturvedi, A.K.; Jemal, A.; Berg, C.D. Preventing lung cancer mortality by computed tomography screening: The effect of risk-based versus US Preventive Services Task Force eligibility criteria, 2005–2015. Ann. Intern. Med. 2018, 168, 229–232. [Google Scholar] [CrossRef]
- Richards, T.B.; Doria-Rose, V.P.; Soman, A.; Klabunde, C.N.; Caraballo, R.S.; Gray, S.C.; Houston, K.A.; White, M.C. Lung cancer screening inconsistent with US Preventive Services Task Force recommendations. Am. J. Prev. Med. 2019, 56, 66–73. [Google Scholar] [CrossRef]
- Ezenwankwo, E.; Nguyen, D.T.; Akpabio, I.U.; Eberth, J.M. Expanding reach, enhancing capacity: Embracing the role of primary care in lung cancer screening and smoking cessation in the United States. Lancet Reg. Health–Am. 2024, 38, 100870. [Google Scholar] [CrossRef] [PubMed]
- Patel, P.; Bradley, S.H.; McCutchan, G.; Brain, K.; Redmond, P. What should the role of primary care be in lung cancer screening? Br. J. Gen. Pract. 2023, 73, 340–341. [Google Scholar] [CrossRef]
- Brady, L.A.; Tumiel-Berhalter, L.M.; Schad, L.A.; Bentham, A.; Vitale, K.; Norton, A.; Noronha, G.; Swanger, C.; Morley, C.P. Increasing breast, cervical, and colorectal cancer screenings: A qualitative assessment of barriers and promoters in safety-net practices. J. Patient-Centered Res. Rev. 2021, 8, 323. [Google Scholar] [CrossRef]
- Wong, L.-Y.; Kapula, N.; Kang, A.; Phadke, A.J.; Schechtman, A.D.; Elliott, I.A.; Guenthart, B.A.; Liou, D.Z.; Backhus, L.M.; Berry, M.F. The role of primary care providers in lung cancer screening: A cross-sectional survey. Clin. Lung Cancer, 2024; in press. [Google Scholar] [CrossRef] [PubMed]
- Wang, G.X.; Baggett, T.P.; Pandharipande, P.V.; Park, E.R.; Percac-Lima, S.; Shepard, J.-A.O.; Fintelmann, F.J.; Flores, E.J. Barriers to lung cancer screening engagement from the patient and provider perspective. Radiology 2019, 290, 278–287. [Google Scholar] [CrossRef]
- Lowenstein, M.; Karliner, L.; Livaudais-Toman, J.; Gregorich, S.; Velazquez, A.I.; Vijayaraghavan, M.; Walsh, J.M.; Kaplan, C.P. Barriers and facilitators to lung cancer screening: A physician survey. Am. J. Health Promot. 2022, 36, 1208–1212. [Google Scholar] [CrossRef]
- Baptista, S.; Teixeira, A.; Castro, L.; Cunha, M.; Serrão, C.; Rodrigues, A.; Duarte, I. Physician burnout in primary care during the COVID-19 pandemic: A cross-sectional study in Portugal. J. Prim. Care Community Health 2021, 12, 21501327211008437. [Google Scholar] [CrossRef]
- Cunningham, A.T.; Felter, J.; Smith, K.R.; Sifri, R.; Arenson, C.; Patel, A.; Kelly, E.L. Burnout and commitment after 18 months of the COVID-19 pandemic: A follow-up qualitative study with primary care teams. J. Am. Board. Fam. Med. 2023, 36, 105–117. [Google Scholar] [CrossRef] [PubMed]
Author/Year (Ref.) | Study Design | Country | Setting/Participants | Eligibility Criteria [Age (y); Smoking Exposure (py); Quit Duration (y)] |
---|---|---|---|---|
Azubuike et al., 2020 [30] | Interventional, pre–post study design | USA | Family medicine clinic N = 27 | USPSTF 2013 criteria [55–74; ≥30; ≤15] |
Brenner et al., 2018 [31] | Interventional, pre–post study design | USA | Academic primary care clinic N = 2349 | [55–80] |
Chiarantano et al., 2022 [33] | Interventional, pre–post study design | Brazil | Community N = 233 | National Lung Screening Trial criteria [55–74; ≥30; ≤15] |
Colamonici et al., 2023 [32] | Interventional, pre–post study design | USA | Primary care center N = 341 | [50–74; ≥20; ≤15] |
Crosbie et al., 2022 [34] | Interventional, RCT | UK | Primary care center N = 89,917 | USPSTF 2013 criteria [55–74; ≥30; ≤15] or PLCOm2012 (6-year risk ≥1.51%) or LLP criteria (5-year risk ≥5%) |
Currier et al., 2022 [35] | Interventional, pre–post study design | USA | Rural primary care and community hospital N = 567 | USPSTF 2013 criteria and CMS screening guidelines [55–74; ≥30] |
DiCarlo et al., 2022 [36] | RCT | USA | Primary care practices N= 2376 | USPSTF, CMS, and National Comprehensive Cancer Center Network guidelines [50–74; ever-smokers] |
Fagan et al., 2020 [37] | Interventional, pre–post study design | USA | Academic healthcare system– primary care practice N = 2829 | USPSTF criteria [55–80; ≥30; ≤15] |
Goodley et al., 2023 [38] | Interventional, pre–post study design | UK | Primary care practices N = 10,708 | [55–80; ever smoked] PLCOm2012NoRace |
Jani et al., 2023 [39] | Retrospective | UK | Development cohort Primary care records N = 574,196 Validation cohort UK Biobank N = 137,918 | [55–75] |
Kukhareva et al., 2023 [40] | Interventional, pre–post study design | USA | 30 primary care and 4 pulmonary clinics N = 1090 | USPSTF 2013 guideline criteria |
Liu et al., 2023 [41] | Retrospective | USA | Primary care clinic N = 102,475 | 2021 USPSTF guideline [50–80; ≥20; ≤ 15) |
O’Brien et al., 2017 [42] | Mixed method pilot comparative study | Canada | Primary care practices N = 831 | [55–74] |
Ostrowski et al., 2021 [43] | Retrospective | Poland | Community N = 6631 | Lung Cancer Screening NCCN Clinical Practice Guidelines ([50–79; ≥30] |
Park et al., 2021 [44] | Retrospective | Korea | National Health Insurance Service N = 969,351 Patients | [40–79; ever-smokers] |
Percac-Lima et al., 2018 [45] | RCT | USA | Five community health centers affiliated with an academic primary care network N = 1200 | [55–77; current smokers] |
Reuland et al., 2018 [46] | Interventional, pre–post study design | USA | Academic primary care practice N = 50 | USPSTF criteria [55–80; ≥30; ≤15] |
Schapira et al., 2023 [47] | RCT | USA | Veteran Affairs Medical Centers N = 140 | [55–80; ≥30; ≤15] |
Author/Year [Ref] | Screening Method | Pathway | Lung Cancer Diagnosis | Recruitment/ Follow-Up Period | Main Results |
---|---|---|---|---|---|
Azubuike et al., 2020 [30] | LDCT | QI project to increase provider compliance with the LCS guidelines. HCPs received education on guidelines on a new phone script for identifying at-risk patients from EHRs. | 3 suspicious granulomas found, sent for additional follow-up | 2017–2020/ 1 year | 8/27 agreed to LDCT. The 19 patients who declined had concerns about testing, including radiation exposure, psychological distress, the efforts required to obtain the test, inability to take time off work, and lack of transportation. A significant difference in the number of LDCTs ordered from the preintervention (n = 0) to postintervention (n = 8) periods (p = 0.0043). |
Brenner et al., 2018 [31] | LDCT | QI project to address three key quality gaps (EHR complete smoking history, VBR, SDM). Software-incorporated reminder system. | N/A | 2015–2016/ 1 year | Percentage of completed smoking histories increased (22% pre-test to 47% post-test). Providers interacted with 27% of VBRs (172/644). Training decreased the frequency of deferral (16% pre-training vs. 7% post-training) and increased interaction with other features of the VBR (11% pre-training vs. 19% post-training). |
Chiarantano et al., 2022 [33] | LDCT | Eligible participants referred from primary care or from screening campaign held on the “World No Tobacco Day”. Mobile Unit for screening. Trained primary care HCPs. Additional smoking cessation counseling and treatment. | 3/233, diagnosis rate of 12.8/1000. | 2019–2021/ 1 year | Participation in a smoking cessation group increased the odds of quitting smoking 2-fold (OR 2.16, CI 95%: 0.83–5.64, p value = 0.158). Less than 10% of the total high-risk population estimates were recruited. |
Colamonici et al., 2023 [32] | LDCT | PCP-based, socially equitable, hybrid QI project on LCS in high-risk patients that incorporates patient education, SDM, and real-time tracking of the screening process. | Lung-RADS scores 4B/4X were more than double the expected prevalence (p = 0.008). | 2021–2022/ 60 weeks | Increase in weekly LCS referrals from PCPs. Out of the 341 referrals, 229 scans were completed and scored. |
Crosbie et al., 2022 [34] | LDCT | Eligible individuals from primary care records randomized to invitation to telephone LCS (intervention) or usual care. If eligibility criteria were met, a LHC appointment and baseline LDCT scan were offered through a mobile scanner. Smoking cessation advice offered during LHC. | N/A | 2018–2021/ N/A | 50.8% response rate in the intervention group. Of those responding, 34.4% were potentially eligible for screening, 29.9% attended a LHC, and 29.1% underwent LDCT screening. Responding reduced by 56% in people who currently smoked (adjusted OR 0.44, 95% CI 0.42–0.47). A similar pattern was seen for high socioeconomic deprivation, with response 42% lower in the most deprived IMD quintile compared with the least deprived (adjusted OR 0.58, 95% CI 0.54–0.62) and LHC attendance 22% lower (adjusted OR 0.78, 95% CI 0.62–0.98). |
Currier et al., 2022 [35] | LDCT | PCPs assessed patient eligibility using EHRs and through care appointments, conducted SDM conversations with their patients about LDCT screening before referring them for LCS and support follow-up care after screening, including smoking cessation support. SDM education and resources provided to PCPs. Community stakeholders engagement in the screening program’s design and implementation. | 2.11% (12/567) | 2018–2020/ 3 years | In 2020, the LDCT lung cancer screening program successfully screened 6.9% of eligible adults compared to 0.93% in 2018. Adherence to follow-up scans increased from 51% in 2019 to 60% in 2020. |
DiCarlo et al., 2022 [36] | LDCT | Participants identified through HER and randomized to Outreach Contact plus Decision Counseling (OC-DC,), Outreach Contact alone (OC), or usual care (UC). Participants in both the OC and OC-DC groups were mailed a decision aid (Option Grid™) including LCS educational materials. Within 10 days after the mailing, a study care coordinator attempted to make telephone contact with participants in the OC and OC-DC groups and assessed LCS eligibility, and for those who were eligible for screening discussed LCS. With OC-DC group participants, the care coordinator used an online interactive decision support software application (DCP) to guide participants through a brief decision-counseling session focused on eliciting values and clarifying preferences related to LCS. At the end of the session, the care coordinator used the application to compute an LCS preference score. | N/A | 2019/ 90–280 days | LCS was significantly higher in the combined OC/OC-DC group versus UC controls (5.5% vs. 1.8%; HR = 3.28; 95%, CI: 1.98 to 5.41; p = 0.001). LCS was higher in the OC-DC group than in the OC group, although not significantly so (7% vs. 4%, respectively; HR = 1.75; 95% CI: 0.86 to 3.55; p = 0.123). LCS referral/scheduling was also significantly higher in the OC/OC-DC group compared to controls (11% vs. 5%; OR = 2.02; p = 0.001). |
Fagan et al., 2020 [37] | LDCT | Eligible participants identified through her. Decision Counseling Program© (DCP) software used to guide a telephone-based SDM led by a trained decision counselor. Tobacco cessation hotline offered to all current smokers. | N/A | N/A/ 90 days | 297/829 individuals were reachable by telephone, out of which 54 were eligible for screening with LDCT. 28 participants were recruited to the study, of which 20 completed SDM. 9 participants completed DCP and LDCT. |
Goodley et al., 2023 [38] | LDCT | Population-based invitation approach. Letters were sent to all individuals from primary care records, inviting ever-smokers to attend an LHC. Attendees at higher risk (PLCOm2012NoRace score ≥ 1.5%) were offered two rounds of annual LDCT. | 3.2% (144/4468) | 2019–2020/ 2 years | 83% of eligible respondents attended an LHC (n = 8887/10 708). Just over half of LHC attendees were eligible for screening (51%, n = 4540/8887), 98% of whom had a baseline LDCT scan (n = 4468/4540). Out of 4199 participants eligible for the second round, 83% (n = 3488) attended. |
Jani et al., 2023 [39] | LDCT | Development and validation of an EHR-based lung cancer risk score (ALIGNED) from two large community cohorts. The new score was based on demographic information, smoking status, BMI, family history of lung cancer, and the presence of the following LTCs: alcohol misuse, COPD, coronary heart disease, dementia, hypertension, painful condition, stroke/TIA, peripheral vascular disease, and history of previous cancer, and previous pneumonia. | Six-year lung cancer incidence was 1.1% (6430) in the development and 0.48% (656) in the validation cohort. | 2011–2017/ 6 years | The final model included 17/56 variables for the EHR-derived score: age, sex, socioeconomic status, smoking status, family history, BMI, BMI/smoking interaction, alcohol misuse, chronic obstructive pulmonary disease, coronary heart disease, dementia, hypertension, painful conditions, stroke, peripheral vascular disease, and history of previous cancer and previous pneumonia. The EHR-derived score had an AUC of 80.4% in the development and 74.4% in validation cohort and outperformed ever-smoked criteria. |
Kukhareva et al., 2023 [40] | LDCT | Clinician-facing EHR prompts and an EHR-integrated everyday SDM tool designed to support the routine incorporation of SDM into primary care. | N/A | 2019–2021/ 9 months | LDCT ordering and completion increased from 7.1% to 27.3% (p < 0.001) and from 4.4% to 17.7% (p < 0.001), respectively. A fivefold increase in the odds of LDCT scan imaging ordering for eligible patients. |
Liu et al., 2023 [41] | N/A | Development and test of an NLP-based approach to extract smoking information from clinical notes to identify LCS eligible patients. | N/A | 2019–2022/ 3 years | After adding NLP-extracted smoking information from clinical notes in 1 year and 3 years, the number of identified LCS-eligible patients were 8931 (51.7% increment) and 10,231 (73.8% increment), respectively NLP-based approach identified 119% more Black/African Americans who meet screening guidelines. |
O’Brien et al., 2017 [42] | LDCT | All patients completed a pre-consultation questionnaire including questions of LCS. Practices were allocated to a screening electronic form (e-form) completion via pre-consultation software group or a paper form (p-form) group (completion of paper forms in the waiting room). After completing the screening form, patients in both e-form and p-form groups were invited to participate in a brief semi-structured telephone interview about their experience. Staff members were asked about their experiences implementing the screening forms, the impact on clinical functioning, and their interactions with patients. | N/A | 2015/ 16 weeks | The number of patients who would be potentially eligible for LDCT screening based on their smoking history as assessed by patient responses was 116/831 (14%) overall, with 74/573 (13%) in the e-form group and 42/258 (16%) in the p-form group. Patients were willing to discuss lung cancer screening eligibility with their PCP. |
Ostrowski et al., 2021 [43] | LDCT | Role of prediction models (I) Tammemagi’s PLCOm2012, (II) LLP, and (III) Bach’s lung cancer risk on risk assessment from the MOLTEST BIS program. Each participant underwent an LDCT, and selected participants underwent a further diagnostic work-up. | Lung cancer detection rate was 2.3%. | 2016–2018/ 6 years | Based on the risk estimates by PLCOm2012, LLP, and Bach’s models, there were 82.4%, 50.3%, and 19.8% of the MOLTEST BIS participants, respectively, who fulfilled the above-mentioned threshold criteria of a lung cancer development probability. Of those detected for increased lung cancer risk, 97.4%, 74.0%, and 44.8% were eligible for screening by PLCOm2012, LLP, and Bach’s model criteria, respectively. In Tammemagi’s risk prediction model, only four cases (2.6%) would have been missed from the group of 154 lung cancer patients primarily detected in the MOLTEST BIS. All three models perform better than a screening program based on age and pack-years. |
Park et al., 2021 [44] | LDCT | Role of prediction models for risk assessment with five models, including Bach, lung cancer risk models for screening (LCRAT), the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Model 2012 (PLCOM2012), Pittsburgh, and Liverpool Lung Project models (LLPi). | 7.767/678.407 (1.14%) developed lung cancer in the training dataset. In the validation dataset 3368/290,994 (1.16%) developed lung cancer. | 2007–2008/ 6.6 years | Models developed for ever-smokers in the Western population were applied to the Korean population; they moderately discriminated people who would develop and those who would not develop lung cancer (AUC, 0.66–0.81). The efficiency of risk model-based selection for lung cancer screening is superior to that of fixed criteria-based selection. |
Percac-Lima et al., 2018 [45] | Any chest CT | Prior to the study, the principal investigator provided an educational session about LCS to PCPs. EHR was used to identify eligible subjects. Participants were randomized to intervention (IG) or usual care group (CG). The intervention group received invitation materials by means of mail and a call from the patient navigator. Navigators contacted patients to determine LCS eligibility, introduce shared decision-making about screening, schedule appointments with primary care physicians (PCPs), and help overcome barriers to obtaining a screening and follow-up. | LC was diagnosed in 8 participants in IG (2%) and 4 in CG (0.5%). | 2016–2017/ 1 year | Percentage uptake of LDCT was 23.5% in the IG and 8.6% in the CG. Greater proportion of patients in the IG had any chest CT compared to patients in the CG (31% [124] vs. 17.3% [138], p < 0.001). LC screening CTs were performed in 94 IG patients (23.5%) vs. 69 CG (8.6%, p < 0.001). 20% of screened patients required follow-up. |
Reuland et al., 2018 [46] | LDCT | Eligible patients identified by EHR were sent recruitment packages by post. Eligibility for LCS was determined by means of telephone, and patient was scheduled for an in-person visit. Study participants viewed the video at the clinic and completed a baseline knowledge survey, follow-up survey, and another survey at 3 mo. | Among the 10 completed LDCTs, 7 were Lung-RADS category 1 (normal result) and 2 were category 2 (small nodules, benign appearance). One was category 4a (suspicious findings); a 3-month follow-up scan showed resolution of the nodule. | 2015–2017/ 3 months | 36/50 participants had a clinic visit in the 3 months following study enrolment. Most participants (n = 48.96%) reported that the decision aid was “useful in making a decision about getting screened for lung cancer.” Knowledge increased from pre- to post-decision aid viewing (mean 2.6 vs. 5.5). 13/50 participants had an LDCT ordered. 10/50 participants completed an LDCT. |
Schapira et al., 2023 [47] | LDCT | Participants eligible for LCS who had an upcoming appointment within 3 weeks were randomized to the LCSDecTool or control program. The LCSDecTool was designed to be used independently by the patient before the clinic visit, with the option to share some components with the clinician during the clinic visit. Smoking cessation support was also included in the tool. | N/A | 2019–2021/ 3 years | Mean decisional conflict score at 1 month did not differ between the LCSDecTool and control groups (25.7 [95% CI, 21.4–30.1] vs. 29.9 [95% CI, 25.6–34.2], respectively; p = 0.18). Mean LCS knowledge score was greater in the LCSDecTool group immediately after intervention (7.0 [95% CI, 6.3–7.7] vs. 4.9 [95% CI, 4.3–5.5]; p < 0.001) and remained higher at 1 month (6.3 [95% CI, 5.7–6.8] vs. 5.2 [95% CI, 4.5–5.8]; p = 0.03) and 3 months (6.2 [95% CI, 5.6–6.8] vs. 5.1 [95% CI, 4.4–5.8]; p = 0.01). Uptake of LCS was greater in the LCSDecTool group at 6 months (26 of 69 [37.7%] vs. 15 of 71 [21.1%]; p = 0.04). |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Symvoulakis, E.K.; Bouloukaki, I.; Christodoulakis, A.; Aravantinou-Karlatou, A.; Tsiligianni, I. Optimal Pathways to Lung Cancer Screening in Primary Care Settings: A Scoping Review. Curr. Oncol. 2025, 32, 8. https://doi.org/10.3390/curroncol32010008
Symvoulakis EK, Bouloukaki I, Christodoulakis A, Aravantinou-Karlatou A, Tsiligianni I. Optimal Pathways to Lung Cancer Screening in Primary Care Settings: A Scoping Review. Current Oncology. 2025; 32(1):8. https://doi.org/10.3390/curroncol32010008
Chicago/Turabian StyleSymvoulakis, Emmanouil K., Izolde Bouloukaki, Antonios Christodoulakis, Antonia Aravantinou-Karlatou, and Ioanna Tsiligianni. 2025. "Optimal Pathways to Lung Cancer Screening in Primary Care Settings: A Scoping Review" Current Oncology 32, no. 1: 8. https://doi.org/10.3390/curroncol32010008
APA StyleSymvoulakis, E. K., Bouloukaki, I., Christodoulakis, A., Aravantinou-Karlatou, A., & Tsiligianni, I. (2025). Optimal Pathways to Lung Cancer Screening in Primary Care Settings: A Scoping Review. Current Oncology, 32(1), 8. https://doi.org/10.3390/curroncol32010008