Literature DB >> 24481763

Lung cancer screening: the radiologist's perspective.

Mathias Prokop1.   

Abstract

Lung cancer is the leading cause of cancer death worldwide and accounts for more deaths than breast, prostate, colon, and pancreatic cancers combined. A distinct minority (15%) of lung cancers are diagnosed at an early stage; 5-year survival (all lung cancers) approximates 15%. Randomized, controlled trials in the 1960s and 1970s found that chest radiographic screening did not confer a survival benefit for high-risk patients. Recently, however, the randomized, controlled National Lung Screening Trail (NLST) provided category 1 evidence that low-dose computed tomography (CT) screening conferred a significant survival benefit for screened individuals: lung cancer-specific mortality was reduced by 20% after 6.5 years of follow-up; even all-cause mortality decreased by 6%. The positive outcome triggered many national medical societies in the United States to recommend lung cancer screening in high-risk individuals. However, the favorable results of the NLST trial have not yet been reproduced. Currently, nine randomized, controlled trials are being or have been performed in various European countries. In contrast to the NLST study, three published European studies found no benefit from low-dose CT scanning in at-risk patients. Additional studies are required to establish the benefit and risks associated with repetitive low-dose CT for screening at-risk patients. Many unanswered questions remain. Who should be screened and how often? What is the appropriate workup when lesions are noted in asymptomatic individuals? What is the risk of cumulative radiation exposure from repetitive low-dose CT scans? What is the responsibility of health care personnel to evaluate nonpulmonary issues detected by CT (e.g., coronary calcifications). In this review, we address these and other questions that arise. Further, implementation of screening programs may be logistically difficult, require additional personnel and computer software, and will incur significant health care costs. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Entities:  

Mesh:

Year:  2014        PMID: 24481763     DOI: 10.1055/s-0033-1363455

Source DB:  PubMed          Journal:  Semin Respir Crit Care Med        ISSN: 1069-3424            Impact factor:   3.119


  8 in total

1.  Lung Cancer Screening Using Low Dose CT Scanning in Germany. Extrapolation of results from the National Lung Screening Trial.

Authors:  Andreas Stang; Martin Schuler; Bernd Kowall; Kaid Darwiche; Hilmar Kühl; Karl-Heinz Jöckel
Journal:  Dtsch Arztebl Int       Date:  2015-09-18       Impact factor: 5.594

2.  ESR/ERS white paper on lung cancer screening.

Authors:  Hans-Ulrich Kauczor; Lorenzo Bonomo; Mina Gaga; Kristiaan Nackaerts; Nir Peled; Mathias Prokop; Martine Remy-Jardin; Oyunbileg von Stackelberg; Jean-Paul Sculier
Journal:  Eur Radiol       Date:  2015-05-01       Impact factor: 5.315

3.  ESR/ERS white paper on lung cancer screening.

Authors:  Hans-Ulrich Kauczor; Lorenzo Bonomo; Mina Gaga; Kristiaan Nackaerts; Nir Peled; Mathias Prokop; Martine Remy-Jardin; Oyunbileg von Stackelberg; Jean-Paul Sculier
Journal:  Eur Respir J       Date:  2015-04-30       Impact factor: 16.671

4.  β-Catenin signaling pathway regulates cisplatin resistance in lung adenocarcinoma cells by upregulating Bcl-xl.

Authors:  Jin Zhang; Jie Liu; Hui Li; Jun Wang
Journal:  Mol Med Rep       Date:  2016-02-05       Impact factor: 2.952

5.  A liquid biopsy for bronchopulmonary/lung carcinoid diagnosis.

Authors:  Mark Kidd; Irvin M Modlin; Ignat Drozdov; Harry Aslanian; Lisa Bodei; Somer Matar; Kyung-Min Chung
Journal:  Oncotarget       Date:  2017-12-29

6.  Energy Dispersive X-ray (EDX) microanalysis: A powerful tool in biomedical research and diagnosis.

Authors:  Manuel Scimeca; Simone Bischetti; Harpreet Kaur Lamsira; Rita Bonfiglio; Elena Bonanno
Journal:  Eur J Histochem       Date:  2018-03-15       Impact factor: 3.188

7.  Computer-aided detection of pulmonary nodules: a comparative study using the public LIDC/IDRI database.

Authors:  Colin Jacobs; Eva M van Rikxoort; Keelin Murphy; Mathias Prokop; Cornelia M Schaefer-Prokop; Bram van Ginneken
Journal:  Eur Radiol       Date:  2015-10-06       Impact factor: 5.315

8.  Development and clinical application of deep learning model for lung nodules screening on CT images.

Authors:  Sijia Cui; Shuai Ming; Yi Lin; Fanghong Chen; Qiang Shen; Hui Li; Gen Chen; Xiangyang Gong; Haochu Wang
Journal:  Sci Rep       Date:  2020-08-12       Impact factor: 4.379

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.