Understanding Lung Cancer Related Risk Factors and Their Impact
NCT ID: NCT06473870
Last Updated: 2024-06-25
Study Results
Results pending
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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Recruitment Status
NOT_YET_RECRUITING
Total Enrollment
6160 participants
Study Classification
OBSERVATIONAL
Study Start Date
2024-07-31
Study Completion Date
2027-12-31
Brief Summary
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LUCIA aims to develop prediction models for the early diagnosis of lung cancer based on the identification of risk factors and deeper cellular knowledge, by recording real-world data; with risk assessment tools, non-invasive devices and omics analysis. These models will enable new clinical pathways and diagnostic workflow to be implemented to ensure early diagnosis and confirmation, including classification of lung cancer subtype.
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Detailed Description
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Lung cancer is the leading cause of cancer death worldwide, causing more deaths than breast and prostate cancer combined.
The current five-year survival rate after diagnosis of all types of lung cancer in Europe is 13% (11.2% for men and 13.9% for women). The five-year survival rate for some types of lung cancer ranges from 6% to 7% (small cell LC) and 23% to 28% for non-small cell lung cancer (NSCLC).
Currently there are important deficiencies when it comes to achieving an adequate lung cancer screening program. According to principles established in 1968, a screening program should be based on pathology that can be improved through the use of population screening.
The evidence suggests two important gaps in early detection. On the one hand, the identification of risk factors beyond smoking and age. And on the other hand, the only tool for early detection that has been shown to reduce morbidity and mortality in lung cancer is chest CT, a test that may not be sustainable in the long term for many healthcare systems. In parallel, lung cancer diagnoses among never smokers and reduced smokers are increasing rapidly, suggesting that if lung cancer screening research continues focusing only on the heaviest smokers, a gap will persist between the population that performs the test and the population that suffers from the disease.
Evidence also suggests that people undergoing screening are not being optimally referred for follow-up or kept engaged in long-term screening.
Currently there are important deficiencies when it comes to achieving an adequate lung cancer screening program. The incidence in individuals without a history of smoking is increasingly higher. Therefore, an observational, longitudinal, multicenter cohort analytical study will be conducted to determine eligibility for screening based on individualized risk (based on age, a more detailed smoking history, occupational exposure, and other risk factors such as ethnicity and family history of lung cancer) and the development and validation of lung cancer risk predictive models that can improve screening efficiency and reduce lung cancer morbidity and mortality.
These models will allow new clinical pathways and diagnostic workflow to be implemented to ensure rapid diagnosis and confirmation, including lung cancer subtype classification.
The study consists of collecting data from participants in 4 visits over two years. During each visit, the clinical evaluation will be carried out, which will consist of the collection of sociodemographic data and clinical history, physical examination, concomitant medication, collection of exposure data and guide symptoms, Quality of Life questionnaires and geolocation. In addition, the following tests will be performed: low-dose computed tomography (LDCT), blood tests, genomic analysis and tests with new non-invasive devices (spectrometry on card (SPOC), breath analyzer (BAN) and broad-spectrum biomarker sensor patch (WBSP)). With all this, the aim is to develop and validate new tests based on new non-invasive and easy-to-use technologies that allow for the implementation of more efficient, acceptable and equitable population screening programs in the near future.
The completion of this project will allow to provide data that can be used to better understand and discover new risk factors for suffering from lung cancer and therefore improve the management of the disease.
Furthermore, this study will favor the reduction of long-term morbidity and mortality from lung cancer and will allow the future implementation of a lung cancer program.
The current five-year survival rate after diagnosis of all types of lung cancer in Europe is 13% (11.2% for men and 13.9% for women). The five-year survival rate for some types of lung cancer ranges from 6% to 7% (small cell LC) and 23% to 28% for non-small cell lung cancer (NSCLC).
Currently there are important deficiencies when it comes to achieving an adequate lung cancer screening program. According to principles established in 1968, a screening program should be based on pathology that can be improved through the use of population screening.
The evidence suggests two important gaps in early detection. On the one hand, the identification of risk factors beyond smoking and age. And on the other hand, the only tool for early detection that has been shown to reduce morbidity and mortality in lung cancer is chest CT, a test that may not be sustainable in the long term for many healthcare systems. In parallel, lung cancer diagnoses among never smokers and reduced smokers are increasing rapidly, suggesting that if lung cancer screening research continues focusing only on the heaviest smokers, a gap will persist between the population that performs the test and the population that suffers from the disease.
Evidence also suggests that people undergoing screening are not being optimally referred for follow-up or kept engaged in long-term screening.
Currently there are important deficiencies when it comes to achieving an adequate lung cancer screening program. The incidence in individuals without a history of smoking is increasingly higher. Therefore, an observational, longitudinal, multicenter cohort analytical study will be conducted to determine eligibility for screening based on individualized risk (based on age, a more detailed smoking history, occupational exposure, and other risk factors such as ethnicity and family history of lung cancer) and the development and validation of lung cancer risk predictive models that can improve screening efficiency and reduce lung cancer morbidity and mortality.
These models will allow new clinical pathways and diagnostic workflow to be implemented to ensure rapid diagnosis and confirmation, including lung cancer subtype classification.
The study consists of collecting data from participants in 4 visits over two years. During each visit, the clinical evaluation will be carried out, which will consist of the collection of sociodemographic data and clinical history, physical examination, concomitant medication, collection of exposure data and guide symptoms, Quality of Life questionnaires and geolocation. In addition, the following tests will be performed: low-dose computed tomography (LDCT), blood tests, genomic analysis and tests with new non-invasive devices (spectrometry on card (SPOC), breath analyzer (BAN) and broad-spectrum biomarker sensor patch (WBSP)). With all this, the aim is to develop and validate new tests based on new non-invasive and easy-to-use technologies that allow for the implementation of more efficient, acceptable and equitable population screening programs in the near future.
The completion of this project will allow to provide data that can be used to better understand and discover new risk factors for suffering from lung cancer and therefore improve the management of the disease.
Furthermore, this study will favor the reduction of long-term morbidity and mortality from lung cancer and will allow the future implementation of a lung cancer program.
Conditions
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Lung Cancer Screening
Study Design
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Observational Model Type
COHORT
Study Time Perspective
PROSPECTIVE
Study Groups
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Study population
Adult subjects (40 years old or higher), smokers and non-smokers, both women and men who have the capacity to comply with the study follow-up and sign the informed consent, will be recruited from "Servicio Andaluz de Salud" (SAS), "Osakidetza Servicio Vasco de Salud" (OSA), "Centre Hospitalier Universitaire de Liège" (CHUL) and "Centre for Tuberculosis and Lung Diseases (CTLD) of Riga East University Hospital (REUH)".
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* Subjects aged between 40 and 80 years
* Both genders, of which at least 37% must be women to ensure representativeness
* Willingness and ability to comply with scheduled visits, laboratory tests, and other trial procedures
* Written informed consent obtained prior to performing any protocol-related procedures.
* High risk of developing Lung Cancer volunteers will be selected by Lung Cancer risk factors modelling.
\- Patients diagnosed with indeterminate pulmonary nodules or Lung Cancer from the screening phases.
* Both genders, of which at least 37% must be women to ensure representativeness
* Willingness and ability to comply with scheduled visits, laboratory tests, and other trial procedures
* Written informed consent obtained prior to performing any protocol-related procedures.
* High risk of developing Lung Cancer volunteers will be selected by Lung Cancer risk factors modelling.
\- Patients diagnosed with indeterminate pulmonary nodules or Lung Cancer from the screening phases.
Exclusion Criteria
* Subjects under 40 years of age
* Unable to be followed-up for at least 2-years or complete the study
* Subjects that do not sign the informed consent
* Current or prior history of lung cancer
* History of neoplasia in the previous 5 years except non-melanoma skin cancer
* Moderate-severe comorbidities that prevent completion of a diagnostic study in the event of findings suggestive of lung neoplasia (by means of the investigator's clinical judgment) or surgical intervention (\< 6 months) if not previously confirmed by cytohistology.
* Vulnerable subjects: severe psychiatric comorbidity, adults under guardianship or deprived of liberty
* Pregnant women
* Unable to be followed-up for at least 2-years or complete the study
* Subjects that do not sign the informed consent
* Current or prior history of lung cancer
* History of neoplasia in the previous 5 years except non-melanoma skin cancer
* Moderate-severe comorbidities that prevent completion of a diagnostic study in the event of findings suggestive of lung neoplasia (by means of the investigator's clinical judgment) or surgical intervention (\< 6 months) if not previously confirmed by cytohistology.
* Vulnerable subjects: severe psychiatric comorbidity, adults under guardianship or deprived of liberty
* Pregnant women
Minimum Eligible Age
40 Years
Maximum Eligible Age
80 Years
Eligible Sex
ALL
Accepts Healthy Volunteers
Yes
Sponsors
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Technion, Israel Institute of Technology
OTHER
Sponsor Role
collaborator
Centro Nacional de Análisis Genómico
UNKNOWN
Sponsor Role
collaborator
Vicomtech
UNKNOWN
Sponsor Role
collaborator
University of Latvia
OTHER
Sponsor Role
collaborator
Centre Hospitalier Universitaire de Liege
OTHER
Sponsor Role
collaborator
Andaluz Health Service
OTHER_GOV
Sponsor Role
collaborator
Nanose Medical Ltd.
INDUSTRY
Sponsor Role
collaborator
Biocruces Bizkaia Health Research Institute
OTHER_GOV
Sponsor Role
lead
Responsible Party
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Responsibility Role
SPONSOR
Principal Investigators
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Luis G Luque-Romero, MD
Role: PRINCIPAL_INVESTIGATOR
Andaluz Health Service
David Vicente-Baz, MD
Role: PRINCIPAL_INVESTIGATOR
Andaluz Health Service
Alvils Krams, MD
Role: PRINCIPAL_INVESTIGATOR
University of Latvia
Julien Guiot, MD
Role: PRINCIPAL_INVESTIGATOR
Centre Hospitalier Universitaire de Liege
Locations
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Centre Hospitalier Universitaire de Liège
Liège, Wallonia, Belgium
Site Status
Riga East University Hospital
Riga, , Latvia
Site Status
Hospital Universitario Cruces
Barakaldo, Viscay, Spain
Site Status
Hospital Universitario Virgen Macarena
Seville, , Spain
Site Status
Aljarafe-Sevilla Norte Health District
Seville, , Spain
Site Status
Countries
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Belgium
Latvia
Spain
Central Contacts
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Facility Contacts
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References
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van Meerbeeck JP, Franck C. Lung cancer screening in Europe: where are we in 2021? Transl Lung Cancer Res. 2021 May;10(5):2407-2417. doi: 10.21037/tlcr-20-890.
Reference Type
BACKGROUND
Oudkerk M, Liu S, Heuvelmans MA, Walter JE, Field JK. Lung cancer LDCT screening and mortality reduction - evidence, pitfalls and future perspectives. Nat Rev Clin Oncol. 2021 Mar;18(3):135-151. doi: 10.1038/s41571-020-00432-6. Epub 2020 Oct 12.
Reference Type
BACKGROUND
Adams SJ, Stone E, Baldwin DR, Vliegenthart R, Lee P, Fintelmann FJ. Lung cancer screening. Lancet. 2023 Feb 4;401(10374):390-408. doi: 10.1016/S0140-6736(22)01694-4. Epub 2022 Dec 20.
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BACKGROUND
Gomez-Carballo N, Fernandez-Soberon S, Rejas-Gutierrez J. Cost-effectiveness analysis of a lung cancer screening programme in Spain. Eur J Cancer Prev. 2022 May 1;31(3):235-244. doi: 10.1097/CEJ.0000000000000700.
Reference Type
BACKGROUND
Thandra KC, Barsouk A, Saginala K, Aluru JS, Barsouk A. Epidemiology of lung cancer. Contemp Oncol (Pozn). 2021;25(1):45-52. doi: 10.5114/wo.2021.103829. Epub 2021 Feb 23.
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BACKGROUND
Schabath MB, Cote ML. Cancer Progress and Priorities: Lung Cancer. Cancer Epidemiol Biomarkers Prev. 2019 Oct;28(10):1563-1579. doi: 10.1158/1055-9965.EPI-19-0221.
Reference Type
BACKGROUND
Zhang T, Joubert P, Ansari-Pour N, Zhao W, Hoang PH, Lokanga R, Moye AL, Rosenbaum J, Gonzalez-Perez A, Martinez-Jimenez F, Castro A, Muscarella LA, Hofman P, Consonni D, Pesatori AC, Kebede M, Li M, Gould Rothberg BE, Peneva I, Schabath MB, Poeta ML, Costantini M, Hirsch D, Heselmeyer-Haddad K, Hutchinson A, Olanich M, Lawrence SM, Lenz P, Duggan M, Bhawsar PMS, Sang J, Kim J, Mendoza L, Saini N, Klimczak LJ, Islam SMA, Otlu B, Khandekar A, Cole N, Stewart DR, Choi J, Brown KM, Caporaso NE, Wilson SH, Pommier Y, Lan Q, Rothman N, Almeida JS, Carter H, Ried T, Kim CF, Lopez-Bigas N, Garcia-Closas M, Shi J, Bosse Y, Zhu B, Gordenin DA, Alexandrov LB, Chanock SJ, Wedge DC, Landi MT. Genomic and evolutionary classification of lung cancer in never smokers. Nat Genet. 2021 Sep;53(9):1348-1359. doi: 10.1038/s41588-021-00920-0. Epub 2021 Sep 6.
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Ramaswamy A. Lung Cancer Screening: Review and 2021 Update. Curr Pulmonol Rep. 2022;11(1):15-28. doi: 10.1007/s13665-021-00283-1. Epub 2022 Apr 2.
Reference Type
BACKGROUND
Ten Haaf K, van der Aalst CM, de Koning HJ, Kaaks R, Tammemagi MC. Personalising lung cancer screening: An overview of risk-stratification opportunities and challenges. Int J Cancer. 2021 Jul 15;149(2):250-263. doi: 10.1002/ijc.33578. Epub 2021 May 3.
Reference Type
BACKGROUND
Berghmans T, Lievens Y, Aapro M, Baird AM, Beishon M, Calabrese F, Degi C, Delgado Bolton RC, Gaga M, Lovey J, Luciani A, Pereira P, Prosch H, Saar M, Shackcloth M, Tabak-Houwaard G, Costa A, Poortmans P. European Cancer Organisation Essential Requirements for Quality Cancer Care (ERQCC): Lung cancer. Lung Cancer. 2020 Dec;150:221-239. doi: 10.1016/j.lungcan.2020.08.017. Epub 2020 Sep 4.
Reference Type
BACKGROUND
Lemjabbar-Alaoui H, Hassan OU, Yang YW, Buchanan P. Lung cancer: Biology and treatment options. Biochim Biophys Acta. 2015 Dec;1856(2):189-210. doi: 10.1016/j.bbcan.2015.08.002. Epub 2015 Aug 19.
Reference Type
BACKGROUND
Nasim F, Sabath BF, Eapen GA. Lung Cancer. Med Clin North Am. 2019 May;103(3):463-473. doi: 10.1016/j.mcna.2018.12.006.
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BACKGROUND
Nooreldeen R, Bach H. Current and Future Development in Lung Cancer Diagnosis. Int J Mol Sci. 2021 Aug 12;22(16):8661. doi: 10.3390/ijms22168661.
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BACKGROUND
Liu Y, Pan IE, Tak HJ, Vlahos I, Volk R, Shih YT. Assessment of Uptake Appropriateness of Computed Tomography for Lung Cancer Screening According to Patients Meeting Eligibility Criteria of the US Preventive Services Task Force. JAMA Netw Open. 2022 Nov 1;5(11):e2243163. doi: 10.1001/jamanetworkopen.2022.43163.
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BACKGROUND
Braithwaite D, Gould MK. Is Lung Cancer Screening Reaching the People Who Are Most Likely to Benefit? JAMA Netw Open. 2022 Nov 1;5(11):e2243171. doi: 10.1001/jamanetworkopen.2022.43171. No abstract available.
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BACKGROUND
Ten Haaf K, Jeon J, Tammemagi MC, Han SS, Kong CY, Plevritis SK, Feuer EJ, de Koning HJ, Steyerberg EW, Meza R. Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study. PLoS Med. 2017 Apr 4;14(4):e1002277. doi: 10.1371/journal.pmed.1002277. eCollection 2017 Apr.
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BACKGROUND
Gould MK, Huang BZ, Tammemagi MC, Kinar Y, Shiff R. Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data. Am J Respir Crit Care Med. 2021 Aug 15;204(4):445-453. doi: 10.1164/rccm.202007-2791OC.
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Yeh MC, Wang YH, Yang HC, Bai KJ, Wang HH, Li YJ. Artificial Intelligence-Based Prediction of Lung Cancer Risk Using Nonimaging Electronic Medical Records: Deep Learning Approach. J Med Internet Res. 2021 Aug 3;23(8):e26256. doi: 10.2196/26256.
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BACKGROUND
de Koning HJ, van der Aalst CM, de Jong PA, Scholten ET, Nackaerts K, Heuvelmans MA, Lammers JJ, Weenink C, Yousaf-Khan U, Horeweg N, van 't Westeinde S, Prokop M, Mali WP, Mohamed Hoesein FAA, van Ooijen PMA, Aerts JGJV, den Bakker MA, Thunnissen E, Verschakelen J, Vliegenthart R, Walter JE, Ten Haaf K, Groen HJM, Oudkerk M. Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial. N Engl J Med. 2020 Feb 6;382(6):503-513. doi: 10.1056/NEJMoa1911793. Epub 2020 Jan 29.
Reference Type
BACKGROUND
US Preventive Services Task Force; Krist AH, Davidson KW, Mangione CM, Barry MJ, Cabana M, Caughey AB, Davis EM, Donahue KE, Doubeni CA, Kubik M, Landefeld CS, Li L, Ogedegbe G, Owens DK, Pbert L, Silverstein M, Stevermer J, Tseng CW, Wong JB. Screening for Lung Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2021 Mar 9;325(10):962-970. doi: 10.1001/jama.2021.1117.
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Triplette M, Wenger DS, Shahrir S, Kross EK, Kava C, Phipps A, Hawes SE, Cole A, Snidarich M, Crothers K. Patient Identification of Lung Cancer Screening Follow-Up Recommendations and the Association with Adherence. Ann Am Thorac Soc. 2022 May;19(5):799-806. doi: 10.1513/AnnalsATS.202107-887OC.
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Lin Y, Fu M, Ding R, Inoue K, Jeon CY, Hsu W, Aberle DR, Prosper AE. Patient Adherence to Lung CT Screening Reporting & Data System-Recommended Screening Intervals in the United States: A Systematic Review and Meta-Analysis. J Thorac Oncol. 2022 Jan;17(1):38-55. doi: 10.1016/j.jtho.2021.09.013. Epub 2021 Oct 6.
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BACKGROUND
Rivera GA, Wakelee H. Lung Cancer in Never Smokers. Adv Exp Med Biol. 2016;893:43-57. doi: 10.1007/978-3-319-24223-1_3.
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Smith RJ, Vijayaharan T, Linehan V, Sun Z, Ein Yong JH, Harris S, Mariathas HH, Bhatia R. Efficacy of Risk Prediction Models and Thresholds to Select Patients for Lung Cancer Screening. Can Assoc Radiol J. 2022 Nov;73(4):672-679. doi: 10.1177/08465371221089899. Epub 2022 Apr 26.
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BACKGROUND
Tammemagi MC, Ten Haaf K, Toumazis I, Kong CY, Han SS, Jeon J, Commins J, Riley T, Meza R. Development and Validation of a Multivariable Lung Cancer Risk Prediction Model That Includes Low-Dose Computed Tomography Screening Results: A Secondary Analysis of Data From the National Lung Screening Trial. JAMA Netw Open. 2019 Mar 1;2(3):e190204. doi: 10.1001/jamanetworkopen.2019.0204.
Reference Type
BACKGROUND
Related Links
Access external resources that provide additional context or updates about the study.
http://www.cancer.org/cancer/lung-cancer/detection-diagnosis-staging/survival-rates.html
Lung Cancer Survival Rates
http://gco.iarc.fr/today/data/factsheets/populations/900-world-fact-sheets.pdf
GLOBOCAN 2020: Estimated cancer incidence, mortality and prevalence worldwide in 2020
http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52022SC0296&qid=1664222001392
Proposal for a Council Recommendation on strengthening prevention through early detection: A new EU approach on cancer screening replacing Council Recommendation 2003/878/EC
Other Identifiers
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LUCIA
Identifier Type: -
Identifier Source: org_study_id
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