Korean Lung Cancer Screening Project

NCT03394703 | Unknown DMC

• 1 other identifier: klucas2017
• Study Type: observational
• Target: 8,000
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Lung Cancer

Keywords

Lung cancer; screening; Low-dose Computed Tomography; Smokers

Outcome Measures

Primary Outcomes (4)

• Early stage lung cancer detection rate

  2 years

• False positive rate

  2 years

• Cost-effectiveness of screening

  Lung cancer screening cost per QALY

  2 years

• Complications of diagnostic procedure

  2 years

Secondary Outcomes (3)

• Participation rate among eligible criteria

  2 years

• Positve rate of LDCT diagnosis reporting system in Korean population

  2 years

• Effectiveness of quality control of screening units by network-based, computer-aided detection (CAD) system

  2 years

Eligibility Criteria

• Age: 55 Years - 74 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

High-risk smoking groups of current smokers and past smokers

You may qualify if:

• Age : 55-74 years old
• Smoking history of at least 30 pack-years
• current smokers
• past smokers who quit smoking within 15 years
• Age : 50-74 years old
• Smoking history of at least 20 pack-years
• current smokers
• past smokers who quit smoking within 15 years

You may not qualify if:

• 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

Sponsors & Collaborators

• National Cancer Center, Korea: lead
• Korean Association for Lung Cancer: collaborator
• The Korean Society of Radiology: collaborator
• The Korea Academy of Tuberculosis and Respiratory diseases: collaborator
• The Korean Academy of Family Medicine: collaborator
• The Korean Society for Preventive Medicine: collaborator

Study Sites (1)

National Cancer Center

Goyang-si, Gyeonggi-do, 10408, South Korea

RECRUITING

Related Publications (13)

• 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.

  PMID: 21714641 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.

  PMID: 26495797 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.

  PMID: 28571524 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.

  PMID: 28360223 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.

  PMID: 28377492 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.

  PMID: 28073150 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.

  PMID: 28185635 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.

  PMID: 28710339 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.

  PMID: 28170394 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.

  PMID: 28625633 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.

  PMID: 21892105 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.

  PMID: 33241512 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.

  PMID: 32286195 DERIVED

Related Links

• American Cancer Society. Cancer Facts and Figures 2017.
• Related Info
• Related Info

MeSH Terms

Conditions

Lung Neoplasms

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases

Central Study Contacts

Yeol Kim, MD, PhD

CONTACT

82-31-920-1753; drheat@ncc.re.kr

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER GOV
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal investigator

Study Record Dates

• First Submitted: December 19, 2017
• First Posted: January 9, 2018
• Study Start: April 10, 2017
• Primary Completion: December 31, 2017
• Study Completion: December 31, 2018
• Last Updated: January 9, 2018

Record last verified: 2018-01

Data Sharing

• IPD Sharing: Will not share

Locations

KR (1)