Understanding Lung Cancer Related Risk Factors and Their Impact (LUCIA)

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.

Study Overview

• Status: Not yet recruiting
• Conditions: Lung Cancer Screening

Detailed Description

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.

• Study Type: Observational
• Enrollment (Estimated): 6160

Contacts and Locations

• Study Contact: Name: Eunate Arana-Arri, PhD; Phone Number: 841593 +34 944881593; Email: eunate.aranaarri@osakidetza.eus
• Study Contact Backup: Name: Jon E Idoyaga-Uribarrena, MPhar; Phone Number: 841593 +34 944881593; Email: joneneko.idoyagauribarrena@bio-bizkaia.eus

Study Locations

• Belgium
  • Wallonie
    • Liège, Wallonie, Belgium, 4000
      • Centre Hospitalier Universitaire de Liege
      • Contact: Julien Guiot, PhD; Phone Number: +32.4.284.49.01; Email: j.guiot@chuliege.be
      • Contact: Benoit Ernst, BA; Email: benoit.ernst@uliege.be
• Latvia
  • Riga, Latvia, LV-1038
    • Riga East University Hospital
    • Sub-Investigator: Linda Mežmale, MD
    • Contact: Alvils Krams, MD; Email: Alvils.Krams@aslimnica.lv
    • Contact: Ilmārs Stonāns, PhD; Phone Number: + 371 28655158; Email: ilmars.stonans@lu.lv
• Spain
  • Sevilla, Spain, 41009
    • Hospital Universitario Virgen Macarena
    • Contact: David Vicente-Baz, MD; Email: david.vicente.sspa@juntadeandalucia.es
    • Contact: Cristina Simarro; Phone Number: 650307416; Email: cristinasimarro5@gmail.com
  • Sevilla, Spain
    • Aljarafe-Sevilla Norte Health District
    • Contact: Luis G Luque Romero, MD; Email: luqueluis2@gmail.com
  • Viscay
    • Barakaldo, Viscay, Spain, 48903
      • Hospital Universitario Cruces
      • Contact: Eunate Arana-Arri, PhD; Phone Number: 841593 +34 944881593; Email: eunate.aranaarri@osakidetza.eus
      • Contact: Jon E Idoyaga-Uribarrena, MPhar; Phone Number: 841593 +34 944881593; Email: joneneko.idoyagauribarrena@bio-bizkaia.eus

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

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)".

Description

Inclusion Criteria (for the 3 phases):

• 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.

Inclusion criteria for Phase 2: Precision Screening:

• High risk of developing Lung Cancer volunteers will be selected by Lung Cancer risk factors modelling.

Inclusion criteria for Phase 3: Diagnosis:

- 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

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

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)".

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
presence of pulmonary nodules	The main variable is the presence of pulmonary nodules identified by Low Dose Computerized Tomography (LDCT)	2 years
Lung Cancer diagnosis	The main variable is the presence of Lung Cancer diagnosis identified by Low Dose Computerized Tomography (LDCT).	2 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Age	years	2 years
Gender	Male/female	2 years
Ethnicity	description of the ethnia	2 years
Socioeconomic factors	deprivation index	2 years
Education level	description of the education level	2 years
height	meter	2 years
weight	kilograms	2 years
Body Mass Index	kg/m^2	2 years
Blood pressure	Systolic and diastolic blood pressure in mmHg	2 years
heart rate	beats/min	2 years
respiratory rate	breaths/min	2 years
Global Initiative for Obstructive Lung Disease (GOLD) classification	only for COPD patient classification. Grade: GOLD 1 to 4 (from GOLD 1 which means mild stage of COPD to GOLD 4 very severe stage of COPD) Exacerbation history: GOLD A, B or E (depending on exacerbations: Gold A id 0 or 1 moderate exacerbations (not leading to hospitalization) with mMRC 0-1 CAT<10; GOLD B if 0 or 1 moderate exacerbations (not leading to hospitalization) with mMRC >= 2 CAT >=10 and GOLD E if 2 or more moderate exacerbations or 1 or more leading to hospitalization) with mMRC 0-1 CAT<10.	2 years
Medical record	Family history of lung cancer or other types of cancer, emphysema/ COPD (+ GOLD classification)/ asthma, Interstitial Lung Disease (interstitial patterns), bronchiectasis, arterial hypertension, dyslipidemia, previous acute myocardial infarction, vasculopathies and chronic treatment.	2 years
Exposure to harmful agents	Smoking and occupational exposure (physical activity and frequency, alcohol intake, cigarette packets/year, age of smoking onset, time elapsed since last cigarette, occupational exposure to carcinogens).	2 years
Exploratory Omics markers	Dedicated blood samples will be specifically performed for a large Omics analysis.	baseline
HEALTH-PROMOTING LIFESTYLE PROFILE II questionnaire (HPLP II)	A score for overall health-promoting lifestyle is obtained by calculating a mean of the individual's responses to all 52 items; six subscale scores are obtained similarly by calculating a mean of the responses to subscale items. The use of means rather than sums of scale items is recommended to retain the 1 to 4 metric of item responses and to allow meaningful comparisons of scores across subscales. Lower scores (1) mean lower engage in a health-promoting lifestyle Higher scores (4) mean higher engage in a health-promoting lifestyle	2 years
Fantastic lifestyle Checklist	Evaluation of the population lifestyle: 85-100 points --> Excellent 70-84 points --> Very good 55-69 points --> Good 35-54 points --> Fair 0-34 points --> needs improvement	2 years
Mediterranean diet adherence questionnaire	0-14 points scale <9 points --> low adherence to Mediterranean diet >9 points --> High adherence to Mediterranean diet	2 years
EuroQoL-5D-5L questionnaire	Scoring from 0-100 points. 0 points low quality of life 100 high quality of life	2 years
The Alcohol Use Disorders Identification Test (AUDIT) questionnaire	Scoring from 0-40 points >8 points --> indicators of hazardous and harmful alcohol use 8-15 points --> simple advice focused on the reduction of hazardous drinking 16-19 points --> brief counseling and continued monitoring >20 points --> warrant further diagnostic evaluationfor alcohol dependence	2 years
Breath Analyzer (BAN) device	Measurement of Volatile Organic Compounds (VOCs) of a breath sample for Lung Cancer early detection	2 years
Wide-biomarker-spectrum Multi-Use Sensing Patch (WBSP)	Measurement of Volatile Organic Compounds (VOCs) in the sweat and skin headspace for Lung Cancer early detection	2 years
Spectrometry-on-Card (SPOC)	Measurement of biomarkers and signals from a blood sample for the early detection of lung cancer	2 years
Tumor pathology	Tumor biopsy will be carried out in order to classify and characterize it regarding its size and location.	2 years
Lung CT scan description	A lungCT scan will be performed to. Lung nodules and other findings (if any) will be reported in order to diagnose a lung cancer. If no anomalies are found, it will also be reported.	2 years
Forced Vital Capacity (FVC)	mL, %, Lower limit of Normal and z-score	2 years
Forced Expiratory Volume in 1 second (FEV1)	mL, %, Lower limit of Normal and z-score	2 years
FEV1/FVC ratio	percentage (%)	2 years
Glucose	mg/dL	baseline
HDL Cholesterol	mg/dL	baseline
Iron	μg/dL	baseline
C reactive protein	mg/L	baseline
Proteins	g/dL	baseline
Albumin	g/dL	baseline
LDL Cholesterol	mg/dL	baseline
Ferritin	ng/mL	baseline
Chloride	mEq/L	baseline
Lactate dehydrogenase	U/L	baseline
Triglycerides	mg/dL	baseline
Transferrin Index	index	baseline
Cholesterol	mg/dL	baseline
transferrin	mg/dL	baseline
phosphate	mg/dL	baseline
calcium	mg/dL	baseline
GOT	U/L	baseline
GPT	U/L	baseline
GGT	U/L	baseline
Bilirubin	mg/dL	baseline
Alkaline phosphatase	U/L	baseline
urea	mg/dL	baseline
Creatinine	mg/dL	baseline
Sodium	mEq/L	baseline
potassium	mEq/L	baseline
Urate	mg/dL	baseline
carcinoembryonic antigen (CEA)	ng/mL	baseline
CA 125	U/mL	baseline
CYFRA 21.1	ng/mL	baseline
Neuronal specific enolase (NSE)	ng/mL	baseline
Complete blood count	number of blood cells, composition and percentage	baseline
erythrocyte sedimentation rate	mm/h	baseline
partial thromboplastin time	seg	baseline
fibrinogen	mg/dL	baseline
international normalized ratio (INR)	ratio	baseline
prothrombin time	seg	baseline
Geo location	Participant's census tract identification (one for home address and one for workplace address)	2 years

Collaborators and Investigators

• Sponsor: Biocruces Bizkaia Health Research Institute
• Collaborators: Technion, Israel Institute of Technology; Andaluz Health Service; University of Latvia; Centre Hospitalier Universitaire de Liege; Nanose Medical Ltd.; Vicomtech; Centro Nacional de Análisis Genómico
• Investigators: Principal Investigator: Julien Guiot, MD, Centre Hospitalier Universitaire de Liege; Principal Investigator: Luis G Luque-Romero, MD, Andaluz Health Service; Principal Investigator: David Vicente-Baz, MD, Andaluz Health Service; Principal Investigator: Alvils Krams, MD, University of Latvia

Publications and helpful links

General Publications

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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. Erratum In: Int J Cancer. 2021 Oct 15;149(8):E13. doi: 10.1002/ijc.33738.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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. Erratum In: PLoS Med. 2020 Sep 25;17(9):e1003403. doi: 10.1371/journal.pmed.1003403.
• 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.
• 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. Erratum In: J Med Internet Res. 2021 Oct 15;23(10):e33519. doi: 10.2196/33519.
• 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.
• 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.
• 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.
• 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.
• 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.

Helpful Links

• Lung Cancer Survival Rates
• GLOBOCAN 2020: Estimated cancer incidence, mortality and prevalence worldwide in 2020
• Proposal for a Council Recommendation on strengthening prevention through early detection: A new EU approach on cancer screening replacing Council Recommendation 2003/878/EC

Study record dates

Study Major Dates

• Study Start (Estimated): July 1, 2024
• Primary Completion (Estimated): December 1, 2027
• Study Completion (Estimated): December 1, 2027

Study Registration Dates

• First Submitted: May 16, 2024
• First Submitted That Met QC Criteria: June 19, 2024
• First Posted (Actual): June 25, 2024

Study Record Updates

• Last Update Posted (Actual): June 25, 2024
• Last Update Submitted That Met QC Criteria: June 19, 2024
• Last Verified: June 1, 2024

More Information

Terms related to this study

• Keywords: Lung Cancer; Risk factors; Lung cancer screening; LDCT
• Additional Relevant MeSH Terms: Respiratory Tract Diseases; Neoplasms; Lung Diseases; Neoplasms by Site; Respiratory Tract Neoplasms; Thoracic Neoplasms; Lung Neoplasms
• Other Study ID Numbers: LUCIA

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No