Overdiagnosis in Lung Cancer Screening can be Reduced to a Low, Manageable Level via a Multilayered Strategy Involving Perfecting Reporting Systems, Restricting Screening to High-Risk Groups, Developing Better Risk Stratification Models, and Improving Management Algorithms

2016 ◽  
Vol 23 (1) ◽  
pp. 113-115
Author(s):  
Eduardo J. Mortani Barbosa
Thorax ◽  
2018 ◽  
Vol 74 (3) ◽  
pp. 247-253 ◽  
Author(s):  
Joan E Walter ◽  
Marjolein A Heuvelmans ◽  
Kevin ten Haaf ◽  
Rozemarijn Vliegenthart ◽  
Carlijn M van der Aalst ◽  
...  

BackgroundThe US guidelines recommend low-dose CT (LDCT) lung cancer screening for high-risk individuals. New solid nodules after baseline screening are common and have a high lung cancer probability. Currently, no evidence exists concerning the risk stratification of non-resolving new solid nodules at first LDCT screening after initial detection.MethodsIn the Dutch-Belgian Randomized Lung Cancer Screening (NELSON) trial, 7295 participants underwent the second and 6922 participants the third screening round. We included participants with solid nodules that were registered as new or <15 mm³ (study detection limit) at previous screens and received additional screening after initial detection, thereby excluding high-risk nodules according to the NELSON management protocol (nodules ≥500 mm3).ResultsOverall, 680 participants with 1020 low-risk and intermediate-risk new solid nodules were included. A total of 562 (55%) new solid nodules were resolving, leaving 356 (52%) participants with a non-resolving new solid nodule, of whom 25 (7%) were diagnosed with lung cancer. At first screening after initial detection, volume doubling time (VDT), volume, and VDT combined with a predefined ≥200 mm3 volume cut-off had high discrimination for lung cancer (VDT, area under the curve (AUC): 0.913; volume, AUC: 0.875; VDT and ≥200 mm3 combination, AUC: 0.939). Classifying a new solid nodule with either ≤590 days VDT or ≥200 mm3 volume positive provided 100% sensitivity, 84% specificity and 27% positive predictive value for lung cancer.ConclusionsMore than half of new low-risk and intermediate-risk solid nodules in LDCT lung cancer screening resolve. At follow-up, growth assessment potentially combined with a volume limit can be used for risk stratification.Trial registration numberISRCTN63545820; pre-results.


2020 ◽  
Vol 95 (2) ◽  
pp. 95-103
Author(s):  
Seung Hun Jang

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.


2019 ◽  
Vol 29 (1) ◽  
pp. 19-24
Author(s):  
Wei Hao Kok ◽  
Andrea Ban Yu-Lin ◽  
Shamsul Azhar Shah ◽  
Faisal Abdul Hamid

Background: Lung cancer is the second most common cause of cancer-related death and the third most common cancer in Malaysia. The rising prevalence of lung cancer suggests the need to consider disease screening for early detection, especially in the high-risk population, as it offers the best chance of cure. Objectives: The study aims to determine the willingness of high-risk respondents to participate in a lung cancer screening programme if made available to them, and to determine their attitude towards lung cancer screening and explore factors that might affect participation in a screening programme. Method: This is a cross-sectional, descriptive study over 6 months conducted in adult patients attending medical clinics in Universiti Kebangsaan Malaysia Medical Centre (UKMMC) using face-to-face administered questionnaires. Results: In total 180 respondents were analysed. There were 177 (98.3%) males. Mean age was 59.8 ± 9.1 years. Of the respondents, 138 (76.7%) had poor knowledge about cancer screening. Former smokers comprised 119 (66.1%) of the participants, and 61 (33.9%) were current smokers. In total, 141 (78.3%) respondents indicated willingness to participate in a lung cancer screening programme. Out of this group, 68 (48.2%) respondents were unwilling to pay for the procedure. Only 18 (12.8%) were unwilling to undergo lung cancer treatment if detected early. Conclusions: Awareness about general cancer screening is low. Our study showed that when informed of their high-risk status, respondents were willing to participate in lung cancer screening. There should be more health programmes to promote and raise awareness about lung cancer.


CHEST Journal ◽  
2004 ◽  
Vol 126 (4) ◽  
pp. 749S
Author(s):  
Gregory M. Loewen ◽  
DongFeng Tan ◽  
Donald Klippenstein ◽  
Zachary Grossman ◽  
Enriqueta Nava ◽  
...  

BMJ Open ◽  
2015 ◽  
Vol 5 (7) ◽  
pp. e008254 ◽  
Author(s):  
Noor Ali ◽  
Kate J Lifford ◽  
Ben Carter ◽  
Fiona McRonald ◽  
Ghasem Yadegarfar ◽  
...  

2013 ◽  
Vol 2 ◽  
pp. 114-120 ◽  
Author(s):  
Kinga Kiszka ◽  
Lucyna Rudnicka-Sosin ◽  
Romana Tomaszewska ◽  
Małgorzata Urbańczyk-Zawadzka ◽  
Maciej Krupiński ◽  
...  

Lung Cancer ◽  
2020 ◽  
Vol 148 ◽  
pp. 79-85
Author(s):  
Mark R. Waddle ◽  
Stephen J. Ko ◽  
Jackson May ◽  
Tasneem Kaleem ◽  
Daniel H. Miller ◽  
...  

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