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
UNKNOWN
Total Enrollment
8000 participants
Study Classification
OBSERVATIONAL
Study Start Date
2017-04-10
Study Completion Date
2018-12-31
Brief Summary
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Lung cancer is by far the leading cause of cancer death and has a lower relative survival rate than other types of cancer because most lung cancers are detected at an advanced stage when they are first diagnosed.
Recently, a randomized control trial suggests that low-dose computed tomography (LDCT) enables an early stage detection and it has been increasingly accepted as an efficient screening method for high-risk individuals to reduce lung cancer mortality.
In 2011, The National Lung Screening Trial (NLST) in the U.S. has produced results that screening high-risk smoking groups (who have at least 30 pack-year smoking history and currently smoke or have quit within the past 15 years) aged 55 to 74 years with LDCT reduced lung cancer mortality by 20%.
Based on the evidence, Korean National Cancer Center has developed and published the guideline of lung cancer screening using LDCT for high-risk populations in 2015. The guideline recommends annual LDCT screening for high-risk smoking groups aged 55 to 74 years, with at least 30 pack-year smoking history and current smokers or past smokers who quit smoking within 15 years.
The Korean Lung Cancer Screening project (K-LUCAS), a nationwide, multicenter, prospective study started to evaluate the effectiveness and feasibility of lung cancer screening with LDCT for considering implementation of a national lung cancer screening program in Korea.
Recently, a randomized control trial suggests that low-dose computed tomography (LDCT) enables an early stage detection and it has been increasingly accepted as an efficient screening method for high-risk individuals to reduce lung cancer mortality.
In 2011, The National Lung Screening Trial (NLST) in the U.S. has produced results that screening high-risk smoking groups (who have at least 30 pack-year smoking history and currently smoke or have quit within the past 15 years) aged 55 to 74 years with LDCT reduced lung cancer mortality by 20%.
Based on the evidence, Korean National Cancer Center has developed and published the guideline of lung cancer screening using LDCT for high-risk populations in 2015. The guideline recommends annual LDCT screening for high-risk smoking groups aged 55 to 74 years, with at least 30 pack-year smoking history and current smokers or past smokers who quit smoking within 15 years.
The Korean Lung Cancer Screening project (K-LUCAS), a nationwide, multicenter, prospective study started to evaluate the effectiveness and feasibility of lung cancer screening with LDCT for considering implementation of a national lung cancer screening program in Korea.
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Detailed Description
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◎ Objective
This study is to evaluate the effectiveness and feasibility of lung cancer screening with LDCT for considering implementation of a national Lung Cancer Screening Program in Korea.
◎ Recruiting procedure
K-LUCAS involves 14 general hospitals located nationwide. The participants in K-LUCAS are recruited from the visitors in these hospitals for receiving national cancer screenings or smoking cessation services. The candidates are evaluated based on the questionnaire that is completed in prior to the national cancer screenings or smoking cessation services. Invitations will be sent to those candidates who meet our selection criteria to take part in LDCT lung cancer screening. Advertising to public including the information both of screening benefit and harm will be held in hospitals, newspaper, local bus stations and subways.
In addition to the criteria-based participant selection, a lung cancer risk prediction model will be adopted to improve the effectiveness of participant selection. The lung cancer risk prediction model considers various lung cancer risk factors in addition to age, smoking history and smoking quit duration which are already examined in the inclusion criteria. The model evaluates drinking amount, physical activity, family history of cancer, past history of lung disease and so on, in participant selection.
◎ Screening procedure
If the candidate meets the selection criteria or is approved by risk prediction model, investigators carefully explain the benefits or harms of the LDCT screening and offer them to participate in a LDCT lung cancer screening. If the candidate agrees on screening participation, an informed consent form is obtained and LDCT screening date is scheduled and confirmed. K-LUCAS also provides a smoking cessation counselling to current smokers on revisiting for the result counselling. A follow-up call is made after 6 months from the LDCT screening in order to assess smoking cessation status following LDCT screening.
◎Reporting LDCT results
The LDCT screening results are evaluated by radiologists in accordance with Lung imaging reporting and data system (Lung-RADS).
Network-based computer-aided detection (CAD) system will be used in K-LUCAS to assist reducing diagnostic errors and increasing lung nodule detection sensitivity.
This study is to evaluate the effectiveness and feasibility of lung cancer screening with LDCT for considering implementation of a national Lung Cancer Screening Program in Korea.
◎ Recruiting procedure
K-LUCAS involves 14 general hospitals located nationwide. The participants in K-LUCAS are recruited from the visitors in these hospitals for receiving national cancer screenings or smoking cessation services. The candidates are evaluated based on the questionnaire that is completed in prior to the national cancer screenings or smoking cessation services. Invitations will be sent to those candidates who meet our selection criteria to take part in LDCT lung cancer screening. Advertising to public including the information both of screening benefit and harm will be held in hospitals, newspaper, local bus stations and subways.
In addition to the criteria-based participant selection, a lung cancer risk prediction model will be adopted to improve the effectiveness of participant selection. The lung cancer risk prediction model considers various lung cancer risk factors in addition to age, smoking history and smoking quit duration which are already examined in the inclusion criteria. The model evaluates drinking amount, physical activity, family history of cancer, past history of lung disease and so on, in participant selection.
◎ Screening procedure
If the candidate meets the selection criteria or is approved by risk prediction model, investigators carefully explain the benefits or harms of the LDCT screening and offer them to participate in a LDCT lung cancer screening. If the candidate agrees on screening participation, an informed consent form is obtained and LDCT screening date is scheduled and confirmed. K-LUCAS also provides a smoking cessation counselling to current smokers on revisiting for the result counselling. A follow-up call is made after 6 months from the LDCT screening in order to assess smoking cessation status following LDCT screening.
◎Reporting LDCT results
The LDCT screening results are evaluated by radiologists in accordance with Lung imaging reporting and data system (Lung-RADS).
Network-based computer-aided detection (CAD) system will be used in K-LUCAS to assist reducing diagnostic errors and increasing lung nodule detection sensitivity.
Conditions
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Lung Cancer
Study Design
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Observational Model Type
COHORT
Study Time Perspective
PROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
* Age : 55-74 years old
* Smoking history of at least 30 pack-years
1. current smokers
2. past smokers who quit smoking within 15 years
* Age : 50-74 years old
* Smoking history of at least 20 pack-years
1. current smokers
2. past smokers who quit smoking within 15 years
* Smoking history of at least 30 pack-years
1. current smokers
2. past smokers who quit smoking within 15 years
* Age : 50-74 years old
* Smoking history of at least 20 pack-years
1. current smokers
2. past smokers who quit smoking within 15 years
Exclusion Criteria
* Lung cancer diagnosed and treated
* Inability to move without help (ECOG status 2 or higher)
* Have been treating regularly for tuberculosis, pneumonia and interstitial lung disease
* Treated for any cancer within the last 5 years (\*Exception: Thyroid cancer, Skin cancer)
* A chest CT examination less than 6 months
* Inability to move without help (ECOG status 2 or higher)
* Have been treating regularly for tuberculosis, pneumonia and interstitial lung disease
* Treated for any cancer within the last 5 years (\*Exception: Thyroid cancer, Skin cancer)
* A chest CT examination less than 6 months
Minimum Eligible Age
55 Years
Maximum Eligible Age
74 Years
Eligible Sex
ALL
Accepts Healthy Volunteers
No
Sponsors
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Korean Association for Lung Cancer
UNKNOWN
Sponsor Role
collaborator
The Korean Society of Radiology
UNKNOWN
Sponsor Role
collaborator
The Korea Academy of Tuberculosis and Respiratory diseases
UNKNOWN
Sponsor Role
collaborator
The Korean Academy of Family Medicine
UNKNOWN
Sponsor Role
collaborator
The Korean Society for Preventive Medicine
UNKNOWN
Sponsor Role
collaborator
National Cancer Center, Korea
OTHER_GOV
Sponsor Role
lead
Responsible Party
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Yeol Kim
Principal investigator
Responsibility Role
PRINCIPAL_INVESTIGATOR
Locations
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National Cancer Center
Goyang-si, Gyeonggi-do, South Korea
Site Status
RECRUITING
Countries
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South Korea
Central Contacts
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Facility Contacts
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References
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National Lung Screening Trial Research Team; Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, Gareen IF, Gatsonis C, Marcus PM, Sicks JD. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011 Aug 4;365(5):395-409. doi: 10.1056/NEJMoa1102873. Epub 2011 Jun 29.
Reference Type
BACKGROUND
Fintelmann FJ, Bernheim A, Digumarthy SR, Lennes IT, Kalra MK, Gilman MD, Sharma A, Flores EJ, Muse VV, Shepard JA. The 10 Pillars of Lung Cancer Screening: Rationale and Logistics of a Lung Cancer Screening Program. Radiographics. 2015 Nov-Dec;35(7):1893-908. doi: 10.1148/rg.2015150079. Epub 2015 Oct 23.
Reference Type
BACKGROUND
Pedersen JH, Sorensen JB, Saghir Z, Flotten O, Brustugun OT, Ashraf H, Strand TE, Friesland S, Koyi H, Ek L, Nyren S, Bergman P, Jekunen A, Nieminen EM, Gudbjartsson T. Implementation of lung cancer CT screening in the Nordic countries. Acta Oncol. 2017 Oct;56(10):1249-1257. doi: 10.1080/0284186X.2017.1329592. Epub 2017 Jun 1.
Reference Type
BACKGROUND
Yousaf-Khan U, van der Aalst C, de Jong PA, Heuvelmans M, Scholten E, Walter J, Nackaerts K, Groen H, Vliegenthart R, Ten Haaf K, Oudkerk M, de Koning H. Risk stratification based on screening history: the NELSON lung cancer screening study. Thorax. 2017 Sep;72(9):819-824. doi: 10.1136/thoraxjnl-2016-209892. Epub 2017 Mar 30.
Reference Type
BACKGROUND
Paci E, Puliti D, Lopes Pegna A, Carrozzi L, Picozzi G, Falaschi F, Pistelli F, Aquilini F, Ocello C, Zappa M, Carozzi FM, Mascalchi M; the ITALUNG Working Group. Mortality, survival and incidence rates in the ITALUNG randomised lung cancer screening trial. Thorax. 2017 Sep;72(9):825-831. doi: 10.1136/thoraxjnl-2016-209825. Epub 2017 Apr 4.
Reference Type
BACKGROUND
Han SS, Ten Haaf K, Hazelton WD, Munshi VN, Jeon J, Erdogan SA, Johanson C, McMahon PM, Meza R, Kong CY, Feuer EJ, de Koning HJ, Plevritis SK. The impact of overdiagnosis on the selection of efficient lung cancer screening strategies. Int J Cancer. 2017 Jun 1;140(11):2436-2443. doi: 10.1002/ijc.30602.
Reference Type
BACKGROUND
Al Mohammad B, Brennan PC, Mello-Thoms C. A review of lung cancer screening and the role of computer-aided detection. Clin Radiol. 2017 Jun;72(6):433-442. doi: 10.1016/j.crad.2017.01.002. Epub 2017 Feb 6.
Reference Type
BACKGROUND
Brain K, Carter B, Lifford KJ, Burke O, Devaraj A, Baldwin DR, Duffy S, Field JK. Impact of low-dose CT screening on smoking cessation among high-risk participants in the UK Lung Cancer Screening Trial. Thorax. 2017 Oct;72(10):912-918. doi: 10.1136/thoraxjnl-2016-209690. Epub 2017 Jul 14.
Reference Type
BACKGROUND
Ten Haaf K, Tammemagi MC, Bondy SJ, van der Aalst CM, Gu S, McGregor SE, Nicholas G, de Koning HJ, Paszat LF. Performance and Cost-Effectiveness of Computed Tomography Lung Cancer Screening Scenarios in a Population-Based Setting: A Microsimulation Modeling Analysis in Ontario, Canada. PLoS Med. 2017 Feb 7;14(2):e1002225. doi: 10.1371/journal.pmed.1002225. eCollection 2017 Feb.
Reference Type
BACKGROUND
Yang SC, Lai WW, Lin CC, Su WC, Ku LJ, Hwang JS, Wang JD. Cost-effectiveness of implementing computed tomography screening for lung cancer in Taiwan. Lung Cancer. 2017 Jun;108:183-191. doi: 10.1016/j.lungcan.2017.04.001. Epub 2017 Apr 4.
Reference Type
BACKGROUND
McMahon PM, Kong CY, Bouzan C, Weinstein MC, Cipriano LE, Tramontano AC, Johnson BE, Weeks JC, Gazelle GS. Cost-effectiveness of computed tomography screening for lung cancer in the United States. J Thorac Oncol. 2011 Nov;6(11):1841-8. doi: 10.1097/JTO.0b013e31822e59b3.
Reference Type
BACKGROUND
Kim H, Kim HY, Goo JM, Kim Y. External validation and comparison of the Brock model and Lung-RADS for the baseline lung cancer CT screening using data from the Korean Lung Cancer Screening Project. Eur Radiol. 2021 Jun;31(6):4004-4015. doi: 10.1007/s00330-020-07513-1. Epub 2020 Nov 25.
Reference Type
DERIVED
Kim H, Kim HY, Goo JM, Kim Y. Lung Cancer CT Screening and Lung-RADS in a Tuberculosis-endemic Country: The Korean Lung Cancer Screening Project (K-LUCAS). Radiology. 2020 Jul;296(1):181-188. doi: 10.1148/radiol.2020192283. Epub 2020 Apr 14.
Reference Type
DERIVED
Related Links
Access external resources that provide additional context or updates about the study.
http://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/cancer-facts-figures-2017.html
American Cancer Society. Cancer Facts and Figures 2017.
Other Identifiers
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klucas2017
Identifier Type: -
Identifier Source: org_study_id
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