scholarly journals Korean National Lung Cancer Screening

2020 ◽  
Vol 95 (2) ◽  
pp. 95-103
Author(s):  
Seung Hun Jang
Keyword(s):  
Lung Cancer ◽  
Cancer Screening ◽  
High Risk ◽  
Large Scale ◽  
Prediction Models ◽  
Lung Cancer Screening ◽  
Lung Cancer Mortality ◽  
Risk Groups ◽  
Medical Systems ◽  
Selection Of

The results of large-scale clinical studies have shown that the lung cancer mortality rate can be reduced by lung cancer screening using low-dose computed tomography (LDCT) in high-risk populations. Lung cancer screening requires rigorous quality control to ensure that imaging can be introduced into evidence-based medical systems and that results can be effectively delivered to examinees. Cessation of smoking is indispensable for reducing mortality in parallel with lung cancer screening. Pulmonary nodules found in LDCT during the Korean National Lung Cancer Screening are categorized according to their characteristics, size, and time of discovery based on the Lung Imaging Reporting And Data System (Lung-RADS); management guidelines are followed according to categorization. To improve the efficiency of lung cancer screening, studies are currently ongoing to enable selection of high-risk groups using lung cancer prediction models and biomarkers. Based on the risk estimation classification of lung cancer, it is expected that the selection of screening subjects and the screening cycle can be differentiated, which will increase the efficiency of screening, reduce the risk of unnecessary radiation exposure, and reduce the cost of screening.

scholarly journals Democratic and ethical problem of lung cancer screening: exclusion of true high-risk populations. Can it be fixed? Yes

2020 ◽  
Vol 7 (1) ◽  
pp. e000811
Author(s):  
Oluf Dimitri Røe
Keyword(s):  
Lung Cancer ◽  
Cancer Screening ◽  
High Risk ◽  
Prediction Models ◽  
Ethical Problem ◽  
Lung Cancer Screening ◽  
Risk Prediction Models ◽  
High Risk Populations ◽  
Deadly Disease ◽  
Selection Of

Screening a population for a potentially deadly disease, the ultimate goal must be to prevent morbidity and mortality from this disease for the whole population. Unlike breast cancer or cervical cancer screening, where all women are screened after a certain age, CT screening for lung cancer has been based on selection of putative high-risk individuals based on age and smoking cut-off values. The type of selection used leaves too many high-risk individuals behind. The solution is to use only validated risk prediction models for selection.

scholarly journals Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study

PLoS Medicine ◽  
2017 ◽  
Vol 14 (4) ◽  
pp. e1002277 ◽  
Author(s):  
Kevin ten Haaf ◽  
Jihyoun Jeon ◽  
Martin C. Tammemägi ◽  
Summer S. Han ◽  
Chung Yin Kong ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Screening ◽  
Risk Prediction ◽  
Validation Study ◽  
Prediction Models ◽  
Lung Cancer Screening ◽  
Risk Prediction Models ◽  
Selection Of

scholarly journals Development, validation, and evaluation of prediction models to identify individuals at high risk of lung cancer for screening in the English primary care population using the QResearch database: research protocol and statistical analysis plan

2022 ◽  
Author(s):  
Weiqi Liao ◽  
Judith Burchardt ◽  
Carol Coupland ◽  
Fergus Gleeson ◽  
Julia Hippisley-Cox ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Primary Care ◽  
Cancer Screening ◽  
High Risk ◽  
Prediction Models ◽  
Lung Cancer Screening ◽  
Population Based ◽  
Primary Care Population ◽  
Asymptomatic Patients ◽  
Diagnosis Of Lung Cancer

Background and research aim: Lung cancer is a research priority in the UK. Early diagnosis of lung cancer can improve patients' survival outcomes. The DART-QResearch project is part of a larger academic-industrial collaborative initiative, using big data and artificial intelligence to improve patient outcomes with thoracic diseases. There are two general research aims in the DART-QResearch project: (1) to understand the natural history of lung cancer, (2) to develop, validate, and evaluate risk prediction models to select patients at high risk for lung cancer screening. Methods: This population-based cohort study uses the QResearch database (version 45) and includes patients aged between 25 and 84 years old and without a diagnosis of lung cancer at cohort entry (study period: 1 January 2005 to 31 December 2020). The team conducted a literature review (with additional clinical input) to inform the inclusion of variables for data extraction from the QResearch database. The following statistical techniques will be used for different research objectives, including descriptive statistics, multi-level modelling, multiple imputation for missing data, fractional polynomials to explore non-linear relationships between continuous variables and the outcome, and Cox regression for the prediction model. We will update our QCancer (lung, 10-year risk) algorithm, and compare it with the other two mainstream models (LLP and PLCOM2012) for lung cancer screening using the same dataset. We will evaluate the discrimination, calibration, and clinical usefulness of the prediction models, and recommend the best one for lung cancer screening for the English primary care population. Discussion: The DART-QResearch project focuses on both symptomatic presentation and asymptomatic patients in the lung cancer care pathway. A better understanding of the patterns, trajectories, and phenotypes of symptomatic presentation may help GPs consider lung cancer earlier. Screening asymptomatic patients at high risk is another route to achieve earlier diagnosis of lung cancer. The strengths of this study include using large-scale representative population-based clinical data, robust methodology, and a transparent research process. This project has great potential to contribute to the national cancer strategic plan and yields substantial public and societal benefits through earlier diagnosis of lung cancer.

scholarly journals The UK Lung Cancer Screening Trial: a pilot randomised controlled trial of low-dose computed tomography screening for the early detection of lung cancer

2016 ◽  
Vol 20 (40) ◽  
pp. 1-146 ◽  
Author(s):  
John K Field ◽  
Stephen W Duffy ◽  
David R Baldwin ◽  
Kate E Brain ◽  
Anand Devaraj ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Lung Cancer ◽  
Cancer Screening ◽  
High Risk ◽  
Controlled Trial ◽  
Lung Cancer Screening ◽  
Lung Cancer Mortality ◽  
Cancer Screening Trial ◽  
The Uk ◽  
Screening Trial

BackgroundLung cancer kills more people than any other cancer in the UK (5-year survival < 13%). Early diagnosis can save lives. The USA-based National Lung Cancer Screening Trial reported a 20% relative reduction in lung cancer mortality and 6.7% all-cause mortality in low-dose computed tomography (LDCT)-screened subjects.ObjectivesTo (1) analyse LDCT lung cancer screening in a high-risk UK population, determine optimum recruitment, screening, reading and care pathway strategies; and (2) assess the psychological consequences and the health-economic implications of screening.DesignA pilot randomised controlled trial comparing intervention with usual care. A population-based risk questionnaire identified individuals who were at high risk of developing lung cancer (≥ 5% over 5 years).SettingThoracic centres with expertise in lung cancer imaging, respiratory medicine, pathology and surgery: Liverpool Heart & Chest Hospital, Merseyside, and Papworth Hospital, Cambridgeshire.ParticipantsIndividuals aged 50–75 years, at high risk of lung cancer, in the primary care trusts adjacent to the centres.InterventionsA thoracic LDCT scan. Follow-up computed tomography (CT) scans as per protocol. Referral to multidisciplinary team clinics was determined by nodule size criteria.Main outcome measuresPopulation-based recruitment based on risk stratification; management of the trial through web-based database; optimal characteristics of CT scan readers (radiologists vs. radiographers); characterisation of CT-detected nodules utilising volumetric analysis; prevalence of lung cancer at baseline; sociodemographic factors affecting participation; psychosocial measures (cancer distress, anxiety, depression, decision satisfaction); and cost-effectiveness modelling.ResultsA total of 247,354 individuals were approached to take part in the trial; 30.7% responded positively to the screening invitation. Recruitment of participants resulted in 2028 in the CT arm and 2027 in the control arm. A total of 1994 participants underwent CT scanning: 42 participants (2.1%) were diagnosed with lung cancer; 36 out of 42 (85.7%) of the screen-detected cancers were identified as stage 1 or 2, and 35 (83.3%) underwent surgical resection as their primary treatment. Lung cancer was more common in the lowest socioeconomic group. Short-term adverse psychosocial consequences were observed in participants who were randomised to the intervention arm and in those who had a major lung abnormality detected, but these differences were modest and temporary. Rollout of screening as a service or design of a full trial would need to address issues of outreach. The health-economic analysis suggests that the intervention could be cost-effective but this needs to be confirmed using data on actual lung cancer mortality.ConclusionsThe UK Lung Cancer Screening (UKLS) pilot was successfully undertaken with 4055 randomised individuals. The data from the UKLS provide evidence that adds to existing data to suggest that lung cancer screening in the UK could potentially be implemented in the 60–75 years age group, selected via the Liverpool Lung Project risk model version 2 and using CT volumetry-based management protocols.Future workThe UKLS data will be pooled with the NELSON (Nederlands Leuvens Longkanker Screenings Onderzoek: Dutch–Belgian Randomised Lung Cancer Screening Trial) and other European Union trials in 2017 which will provide European mortality and cost-effectiveness data. For now, there is a clear need for mortality results from other trials and further research to identify optimal methods of implementation and delivery. Strategies for increasing uptake and providing support for underserved groups will be key to implementation.Trial registrationCurrent Controlled Trials ISRCTN78513845.FundingThis project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full inHealth Technology Assessment; Vol. 20, No. 40. See the NIHR Journals Library website for further project information.

scholarly journals Correction: Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study

PLoS Medicine ◽  
2020 ◽  
Vol 17 (9) ◽  
pp. e1003403
Author(s):  
Kevin ten Haaf ◽  
Jihyoun Jeon ◽  
Martin C. Tammemägi ◽  
Summer S. Han ◽  
Chung Yin Kong ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Screening ◽  
Risk Prediction ◽  
Validation Study ◽  
Prediction Models ◽  
Lung Cancer Screening ◽  
Risk Prediction Models ◽  
Selection Of

scholarly journals P1.03-046 Selection of Subjects at High-Risk for LDCT Lung Cancer Screening Using a Molecular Panel: Results by the ITALUNG Biomarker Study

2017 ◽  
Vol 12 (1) ◽  
pp. S570-S571
Author(s):  
Francesca Carozzi ◽  
Laura Carrozzi ◽  
Fabio Falaschi ◽  
Andrea Lopes Pegna ◽  
Mario Mascalchi ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Screening ◽  
High Risk ◽  
Lung Cancer Screening ◽  
Selection Of

scholarly journals Safety and Effectiveness of Lung Cancer Screening Using Low-dose Computed Tomography Scan in High-risk Individuals: A Comprehensive Review

2021 ◽  
Author(s):  
Sara Mohamadi ◽  
Rajabali Daroudi ◽  
Mohamadreza Mobinizadeh
Keyword(s):  
Computed Tomography ◽  
Lung Cancer ◽  
Cancer Screening ◽  
High Risk ◽  
Cancer Mortality ◽  
Lung Cancer Screening ◽  
Lung Cancer Mortality ◽  
Comprehensive Review ◽  
Incidence And Mortality ◽  
Technical Specifications

Context: Lung cancer is the most important cause of cancer mortality. Given the incidence and mortality of this disease, the implementation of preventive interventions is necessary. Objectives: The present study investigated the effectiveness of one of the most important interventions of lung cancer screening with lowdose computed tomography (LDCT) in high-risk individuals. Evidence Acquisition: The present study was an applied study performed as a comprehensive review. For the assessment of safety, studies on the technical specifications of computed tomography scans and issues related to the safety of applying this device were searched using keywords in medical databases. For the evaluation of clinical effectiveness, a comprehensive review of health technology assessment studies, systematic review studies, and screening guidelines was performed. Results: Based on 15 studies extracted for the safety issue, the diagnosis of harmless tumors, false positives cases and Unnecessary invasive complementary interventions, and possible negative effects of radiation exposure are discussable safety issues. Based on the synthesis of 16 studies on effectiveness, lung cancer screening intervention using LDCT was determined to reduce lung cancer mortality by 15 - 20% and mortality from other causes by 0 - 6%. Additionally, the incidence of this disease in its upper stages decreases significantly. Conclusions: Lung cancer screening using LDCT does not threaten the health of individuals seriously and, in comparison to nonintervention is more clinically effective and will lead to a statistically significant reduction in lung cancer mortality and increase in the timely diagnosis of this disease.  

Sign in / Sign up

Export Citation Format

Share Document